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Lithofacies and Petrophysical Properties of Mesaverde Tight-Gas Sandstones in Western U.S. Basins: a short course
Alan P. Byrnes formerly Kansas Geological Survey- now Chesapeake Energy Robert M. Cluff John C. Webb Daniel A. Krygowski Stefani D. Whittaker The Discovery Group, Inc
2009 AAPG Annual Convention Short course #1 6 June 2009, Denver, Colorado
Cluff: Introduction and Overview
Lithofacies and Petrophysical Lithofacies and Petrophysical Properties of Mesaverde TightProperties of Mesaverde Tight--Gas Gas Sandstones in Western U.S. Basins: Sandstones in Western U.S. Basins: a short coursea short courseAlan P. Byrnes Alan P. Byrnes
formerlyformerly Kansas Geological SurveyKansas Geological Survey--now Chesapeake Energynow Chesapeake Energy
Robert M. Cluff Robert M. Cluff John C. Webb John C. Webb Daniel A. Krygowski Daniel A. Krygowski Stefani D. Whittaker Stefani D. Whittaker
The Discovery Group, IncThe Discovery Group, Inc
Denver, ColoradoAAPG ACE 2009: Denver Colorado 11
2009 AAPG Annual Convention2009 AAPG Annual ConventionShort course #1Short course #16 June 2009, Denver, Colorado6 June 2009, Denver, Colorado
Short course agendaShort course agenda8:008:00--8:308:30 Project overview, Bob CluffProject overview, Bob Cluff8:308:30--10:0010:00 Lithofacies and geology of the Lithofacies and geology of the
Mesaverde Group, John WebbMesaverde Group, John Webb10 0010 00 10 1510 15 b eakb eak10:0010:00--10:1510:15 breakbreak10:1510:15--noonnoon Porosity & permeability of Mesaverde Porosity & permeability of Mesaverde
tight gas sands, Alan Byrnestight gas sands, Alan Byrnesnoonnoon--1:00p1:00p lunchlunch1:001:00--2:302:30 Pc, resistivity, and relative Pc, resistivity, and relative
perm of Mesaverde, Alan Byrnesperm of Mesaverde, Alan Byrnes2:302:30--2:452:45 breakbreak2:452:45--4:154:15 Log evaluation of the Mesaverde Dan Log evaluation of the Mesaverde Dan
AAPG ACE 2009: Denver Colorado 2
2:452:45--4:154:15 Log evaluation of the Mesaverde, Dan Log evaluation of the Mesaverde, Dan Krygowski, Stefani Whittaker, Krygowski, Stefani Whittaker, & Bob Cluff& Bob Cluff
4:154:15--4:304:30 discussion, Q&A perioddiscussion, Q&A period
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Cluff: Introduction and Overview
Project title:Analysis of Critical Permeability, Capillary and Electrical Properties for Mesaverde Tight Gas Sandstones
US DOE # DE-FC26-05NT42660US DOE # DE-FC26-05NT42660from Western U.S. Basins
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website: http://www.kgs.ku.edu/mesaverdewebsite: http://www.kgs.ku.edu/mesaverde
Project overviewProject overviewProject proposal submitted on 21 March 2005 in Project proposal submitted on 21 March 2005 in response to DOE solicitation DEresponse to DOE solicitation DE--PS26PS26--04NT4272004NT42720DOE award DEDOE award DE--FC26FC26--05NT42660 in October 2005 05NT42660 in October 2005
for $411K DOE funds/$103K industry cofor $411K DOE funds/$103K industry co--shareshareDiscovery Group inDiscovery Group in--kind contribution of manpower and kind contribution of manpower and facilitiesfacilities
2 ½ year study with no2 ½ year study with no--cost extensioncost extensionAlan P. Byrnes, Principal InvestigatorAlan P. Byrnes, Principal InvestigatorUniversity of Kansas Center for Research was theUniversity of Kansas Center for Research was the
AAPG ACE 2009: Denver Colorado 4
University of Kansas Center for Research was the University of Kansas Center for Research was the umbrella contracting organizationumbrella contracting organization
Kansas Geological Survey and The Discovery Group, coKansas Geological Survey and The Discovery Group, co--participating research contractorsparticipating research contractors
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Cluff: Introduction and Overview
Team MembersTeam Members
University of KansasUniversity of Kansas--Kansas Geological SurveyKansas Geological SurveyAlan P. Byrnes (Principal Investigator)Alan P. Byrnes (Principal Investigator)Support Team Members: Support Team Members: John Victorine, Ken Stalder, Daniel S. Osburn, John Victorine, Ken Stalder, Daniel S. Osburn, Andrew Knoderer, Owen Metheny, Troy Andrew Knoderer, Owen Metheny, Troy Hommertzheim, Joshua P. ByrnesHommertzheim, Joshua P. Byrnes
The Discovery Group, Inc.The Discovery Group, Inc.
AAPG ACE 2009: Denver Colorado 5
The Discovery Group, Inc.The Discovery Group, Inc.Robert M. Cluff (coRobert M. Cluff (co--Principal Investigator)Principal Investigator)John C. Webb, Daniel A. Krygowski, Stefani WhittakerJohn C. Webb, Daniel A. Krygowski, Stefani Whittaker
Future Gas SupplyFuture Gas Supply
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Lower 48 unconventional gas sources will meet nearly 50% of US demand (Caruso, EIA, 2008)
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Cluff: Introduction and Overview
Future Gas SupplyFuture Gas Supply
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While tight gas sandstones represent over half of unconventional supply (Caruso, EIA, 2008)
Production Projected to Increase from Rocky Production Projected to Increase from Rocky Mountain RegionMountain Region
Tcf)
Gas
Pro
duct
ion
(
AAPG ACE 2009: Denver Colorado 8
(US EIA, 2004)Date
Annu
al
AAPG ACE Short Course 1: 06.06.2009 4 of 217
Cluff: Introduction and Overview
Lower 48 Technically Recoverable ResourcesLower 48 Technically Recoverable Resources
peN
atur
al G
as T
y
AAPG ACE 2009: Denver Colorado 9
Tcf (US EIA, 2004)
PGC Rocky Mountain Gas ResourcesPGC Rocky Mountain Gas Resources
KmvShallow Resources (0Shallow Resources (0--15,000 ft)15,000 ft) 99,167 Bcf99,167 BcfDeep Resources (15,000Deep Resources (15,000--30,000 ft)30,000 ft) 24,429 Bcf24,429 Bcf
Total Traditional ResourcesTotal Traditional Resources 123,596 Bcf123,596 BcfCoalbed Gas ResourcesCoalbed Gas Resources 63,273 Bcf63,273 BcfTotal Recoverable ResourcesTotal Recoverable Resources 186,869 Bcf186,869 Bcf
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Data source: Potential Gas Committee (2003)
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Cluff: Introduction and Overview
Why pick the Mesaverde?Why pick the Mesaverde?Tight gas sandstones (TGS) represent Tight gas sandstones (TGS) represent
72% (342 TCF) of the projected unconventional gas 72% (342 TCF) of the projected unconventional gas resource (474 TCF). resource (474 TCF). Rocky Mountain TGS are 70% of the total TGS resource Rocky Mountain TGS are 70% of the total TGS resource base (241 Tcf; USEIA 2004)base (241 Tcf; USEIA 2004)base (241 Tcf; USEIA, 2004) base (241 Tcf; USEIA, 2004) and the Mesaverde Group represents the main gas and the Mesaverde Group represents the main gas productive sandstone unit in the Rocky Mtn. TGS basinsproductive sandstone unit in the Rocky Mtn. TGS basinsand the largest shallow (<15,000 ft) target. and the largest shallow (<15,000 ft) target.
Understanding of reservoir properties and accurate Understanding of reservoir properties and accurate tools for formation evaluation are needed for:tools for formation evaluation are needed for:
assessment of the regional gas resourceassessment of the regional gas resourcej ti f f t lj ti f f t l
AAPG ACE 2009: Denver Colorado 11
projection of future gas supplyprojection of future gas supplyexploration programsexploration programsoptimizing development programsoptimizing development programs
Project objectivesProject objectivesThe project provides petrophysical tools that The project provides petrophysical tools that address fundamental questions concerning address fundamental questions concerning
gas flow critical gas saturation Sgc=gas flow critical gas saturation Sgc=ff (lithofacies(lithofaciesgas flow, critical gas saturation, Sgcgas flow, critical gas saturation, Sgc ff (lithofacies, (lithofacies, Pc, architecture)Pc, architecture)capillary pressure, Pc=capillary pressure, Pc=ff (P), Pc=(P), Pc=f f (lithofacies, k, (lithofacies, k, φφ, , architecture)architecture)electrical properties, m* & n*electrical properties, m* & n*facies and upscaling issuesfacies and upscaling issues
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wireline log interpretation algorithmswireline log interpretation algorithmsproviding a webproviding a web--accessible database of advanced accessible database of advanced rock properties. rock properties.
AAPG ACE Short Course 1: 06.06.2009 6 of 217
Cluff: Introduction and Overview
Specific research objectivesSpecific research objectivesexplore nature of critical gas saturation, capillary explore nature of critical gas saturation, capillary pressure, and electrical properties of Mesaverde pressure, and electrical properties of Mesaverde tight gas sandstonestight gas sandstonesh d th ith it bilit dh d th ith it bilit dhow do these vary with porosity, permeability, and how do these vary with porosity, permeability, and lithofacies?lithofacies?better understanding of minimum gas saturation better understanding of minimum gas saturation required for gas flowrequired for gas flowimprove log calculations through better corrections improve log calculations through better corrections for conductive solids/surface effectsfor conductive solids/surface effectsaddress the lack of adequate public domainaddress the lack of adequate public domain
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address the lack of adequate public domain address the lack of adequate public domain databases covering petrophysics of tight gas databases covering petrophysics of tight gas sandstonessandstones
lots of proprietary data out there, numerous publications lots of proprietary data out there, numerous publications with partial datasets, but nothing integrated to work withwith partial datasets, but nothing integrated to work with
TasksTasksTask 1. Research Management PlanTask 1. Research Management PlanTask 2. Technology Status AssessmentTask 2. Technology Status AssessmentTask 3. Acquire Data and MaterialsTask 3. Acquire Data and Materials
Subtask 3.1. Compile published advanced properties dataSubtask 3.1. Compile published advanced properties dataSubtask 3.2. Compile representative lithofacies core and logs from major basinsSubtask 3.2. Compile representative lithofacies core and logs from major basinsSubtask 3.3. Acquire logs from sample wells and digitizeSubtask 3.3. Acquire logs from sample wells and digitize
Task 4. Measure Rock PropertiesTask 4. Measure Rock PropertiesppSubtask 4.1. Measure basic properties (k, Subtask 4.1. Measure basic properties (k, φφ, GD) and select advanced population, GD) and select advanced populationSubtask 4.4. Measure critical gas saturationSubtask 4.4. Measure critical gas saturationSubtask 4.3. Measure inSubtask 4.3. Measure in--situ and routine capillary pressuresitu and routine capillary pressureSubtask 4.4. Measure electrical propertiesSubtask 4.4. Measure electrical propertiesSubtask 4.5. Measure geologic and petrologic propertiesSubtask 4.5. Measure geologic and petrologic propertiesSubtask 4.6. Perform standard logs analysisSubtask 4.6. Perform standard logs analysis
Task 5. Build Database and WebTask 5. Build Database and Web--based Rock Catalogbased Rock CatalogSubtask 5.1. Compile published and measured data into Oracle databaseSubtask 5.1. Compile published and measured data into Oracle databaseSubtask 5.2. Modify existing webSubtask 5.2. Modify existing web--based software to provide GUI data accessbased software to provide GUI data access
Task 6. Analyze WirelineTask 6. Analyze Wireline--log Signature and Analysis Algorithmslog Signature and Analysis AlgorithmsSubtask 6 1 Compare log and core propertiesSubtask 6 1 Compare log and core properties
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Subtask 6.1. Compare log and core propertiesSubtask 6.1. Compare log and core propertiesSubtask 6.2. Evaluate results and determine logSubtask 6.2. Evaluate results and determine log--analysis algorithm inputsanalysis algorithm inputs
Task 7. Simulate ScaleTask 7. Simulate Scale--dependence of Relative Permeabilitydependence of Relative PermeabilitySubtask 7.1. Construct basic bedform architecture modelsSubtask 7.1. Construct basic bedform architecture modelsSubtask 7.2. Perform numerical simulation of flow for basic bedform architectureSubtask 7.2. Perform numerical simulation of flow for basic bedform architecture
Task 8. Technology TransferTask 8. Technology Transfer
AAPG ACE Short Course 1: 06.06.2009 7 of 217
Cluff: Introduction and Overview
Research strategyResearch strategycompile all available published advanced compile all available published advanced rock properties (Pc, FRF, Krg, rock properties (Pc, FRF, Krg, compressibility, etc.)compressibility, etc.)compressibility, etc.)compressibility, etc.)collect 300+ core plug samples from 20 to collect 300+ core plug samples from 20 to 25 wells across 5 major basins25 wells across 5 major basinssample full range of rock types, porosity and sample full range of rock types, porosity and permeability found in Mesaverde throughout permeability found in Mesaverde throughout the Rockiesthe Rockies
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the Rockiesthe RockiesKmv is widespread, lots of core available, Kmv is widespread, lots of core available, representative example for most TGS problemsrepresentative example for most TGS problems
SamplingSampling
44 wells in 6 44 wells in 6 basinsbasinsdescribeddescribed
Wind River
PowderRiver
Wyomingdescribed described 7000 ft core 7000 ft core (digital)(digital)2200 core 2200 core samplessamples120120--400 400 advanced advanced
titi
Green River
Washakie
Utah
N
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properties properties samplessamples
PiceanceUintaColorado
Utah
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Cluff: Introduction and Overview
Number of wells by basinNumber of wells by basin
8
10
12
Wel
ls Industry-contributionUSGS Core Library
0
2
4
6
8
n r
Num
ber
of W
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Gre
enRi
ver
Pice
ance
Pow
der
Rive
r
Uin
ta
Was
haki
e
Was
hakie
(San
dW
ash)
Win
d Ri
ver
Basin
Core Plugs by BasinCore Plugs by Basin
500
600
700
e Pl
ugs
0
100
200
300
400
r e a e r r
Num
ber o
f Cor
e
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Gre
ater
Gre
en R
ive r
Was
haki
e
Uin
ta
Pic
eanc
e
Win
d R
iver
Pow
der
Riv
er
Basin
AAPG ACE Short Course 1: 06.06.2009 9 of 217
Cluff: Introduction and Overview
Sampling by depthSampling by depth
Depth Histogram
0 160.180.20
80%90%100%
0 020.040.060.080.100.120.140.16
Frac
tion
10%20%30%40%50%60%70%80%
AAPG ACE 2009: Denver Colorado 19
0.000.02
1000
2000
3000
4000
5000
6000
7000
8000
9000
1000
011
000
1200
013
000
1400
015
000
1600
017
000
Depth (ft)
0%10%
Property Property distributionsdistributions
Petrophysical property Petrophysical property distributions are generally distributions are generally normal or lognormal or log--normalnormalS bS b di t ib tidi t ib ti ff 5
10
15
20
25
30
35
40
45
50
Perc
ent o
f Pop
ulat
ion
(%)
AllGreen RiverPiceancePowder RiverSand WashUintahWind RiverWashakie
SubSub--distributions = distributions = f f (basin, lithofacies, (basin, lithofacies, marine/nonmarine/non--marine, etc.)marine, etc.)
30
40
50
60
sin
Popu
latio
n
Green RiverPiceancePowder RiverUintahWind River
0
5
1E-7
- 1E
-6
1E-6
- 1E
-5
1E-5
- 1E
-4
0.00
01-0
.001
0.00
1-0.
01
0.01
-0.1
0.1-
1
1-10
10-1
00
100-
1,00
0
In situ Klinkenberg Permeability (mD)
P
25
30
35
40
45
ulat
ion
(%)
AllGreen RiverPiceancePowder RiverSand WashUintah
AAPG ACE 2009: Denver Colorado 20
0
10
20
30
2.58-2.60
2.60-2.62
2.62-2.64
2.64-2.66
2.66-2.68
2.68-2.70
2.70-2.72
2.72-2.74
Grain Density (g/cc)
Perc
ent o
f Bas Washakie
Sand Wash
0
5
10
15
20
0-2
2-4
4-6
6-8
8-10
10-1
2
12-1
4
14-1
6
16-1
8
18-2
0
20-2
2
22-2
4
In situ Porosity (%)
Perc
ent o
f Pop
u UintahWind RiverWashakie
AAPG ACE Short Course 1: 06.06.2009 10 of 217
Cluff: Introduction and Overview
Core descriptionCore description
rock typing at 0.5 ft rock typing at 0.5 ft frequency to match frequency to match q yq ylog data resolutionlog data resolutionlithology, color, grain lithology, color, grain size, sed structuressize, sed structuressample locationssample locationsimportant cementsimportant cementsd iti ld iti l
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depositional depositional environmentsenvironments
Digital core descriptionDigital core description
To provide lithologic input to To provide lithologic input to equations and predict equations and predict lithology from logs used 5lithology from logs used 5lithology from logs used 5 lithology from logs used 5 digit systemdigit system
1 basic type (Ss, Ls, coal)1 basic type (Ss, Ls, coal)2 grain size/sorting/texture2 grain size/sorting/texture3 consolidation3 consolidation4 sedimentary structure4 sedimentary structure5 cement mineralogy5 cement mineralogy
P t tiP t ti tt
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Property continuum Property continuum -- not not mnemonic or substitution mnemonic or substitution ciphercipherSimilar to system used in Similar to system used in our 1994 and subsequent our 1994 and subsequent studiesstudies
AAPG ACE Short Course 1: 06.06.2009 11 of 217
Cluff: Introduction and Overview
PetrographyPetrography
~150 advanced ~150 advanced properties smpls wereproperties smpls were
40X
properties smpls were properties smpls were petrographically petrographically characterizedcharacterizedrepresentative photos at representative photos at several magnificationsseveral magnificationspoint countspoint counts
AAPG ACE 2009: Denver Colorado 23
Williams PA 424, 6148.8’ 152769.9% 2.66 g/cc Ka=0.0237 mD
100X
Core analysis programCore analysis programGeologic description of cores and rock types Geologic description of cores and rock types (Webb)(Webb)WireWire--line log analysis of all project wells over Kmv line log analysis of all project wells over Kmv (Krygowski and Whittaker)(Krygowski and Whittaker)Collect plugs for basic properties (minimum 300 Collect plugs for basic properties (minimum 300 samples, we actually collected ~2200) (Byrnes)samples, we actually collected ~2200) (Byrnes)
routine porosity and permeabilityroutine porosity and permeabilityporosity and permeability at reservoir stressporosity and permeability at reservoir stressgrain densitygrain density
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Select a subSelect a sub--set of 120set of 120--400 samples for advanced 400 samples for advanced core analyses (Byrnes)core analyses (Byrnes)
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Cluff: Introduction and Overview
“Routine” core analysis“Routine” core analysis
Routine porosity and permeabilityRoutine porosity and permeabilityInIn--situ porosity and permeabilitysitu porosity and permeabilityP l ibilit (113 l )P l ibilit (113 l )Pore volume compressibility (113 smpls)Pore volume compressibility (113 smpls)
200200--4000 psi NCS4000 psi NCSdetermined new equations fordetermined new equations for
Klinkenberg correctionKlinkenberg correctionstress dependent porositystress dependent porosityt d d t bilitt d d t bilit
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stress dependent permeabilitystress dependent permeability
1
10
100
rmea
bilit
y Council GroveMesaverde/Frontier
Prior workPrior work
0.0001
0.001
0.01
0.1
n si
tu K
linke
nber
g Pe
r(m
d)
AAPG ACE 2009: Denver Colorado 26
0.000010.001 0.01 0.1 1 10 100
Routine Air Permeability (md)
In
logkik = 0.0588 (logkair)3 –0.187 (logkair)2 +1.154 logkair - 0.159
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Cluff: Introduction and Overview
SCAL workSCAL workroutine and routine and in situin situ mercury capillary pressure mercury capillary pressure investigate Pc as function of lithology,investigate Pc as function of lithology, φφ, K , K
sample span range of basins, K, lithologysample span range of basins, K, lithology
investigate stress sensitivity of Pcinvestigate stress sensitivity of Pcmost MICP curves are run under lab conditionsmost MICP curves are run under lab conditionswe expect Pc to be confining stress sensitivewe expect Pc to be confining stress sensitive120 “high120 “high--low” pairs of plugs run using highly similar plugs low” pairs of plugs run using highly similar plugs selected from selected from φφ--K dataK data
look at relationship between initial saturation and look at relationship between initial saturation and
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residual gas saturation (“scanning curves”)residual gas saturation (“scanning curves”)only published data are for conventional rocksonly published data are for conventional rocksran mercury curves for this projectran mercury curves for this project
Mesaverde, Frontier capillary Mesaverde, Frontier capillary pressure vs. permeabilitypressure vs. permeability
300
350
r (ft)
10 md1 md0.1 md0.01 md
100
150
200
250
t abo
ve F
ree
Wat
er
0.01 md0.001 md
AAPG ACE 2009: Denver Colorado 28
0
50
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0Water Saturation (fraction)
~Hei
ght
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Cluff: Introduction and Overview
Pc hysteresisPc hysteresis
NonNon--wetting residual wetting residual saturation to saturation to
Drainage-ImbibitionCycles
23
4
5
imbibition Snwr = imbibition Snwr = f f (Snwi)(Snwi)this was a “freebie” this was a “freebie” added to the project added to the project planplan
1
Midale Dol
AAPG ACE 2009: Denver Colorado 29(after Larson & Morrow, 1981)
φ = 23%
SCAL workSCAL workroutine and routine and in situin situ mercury capillary mercury capillary pressurepressuredrainage critical gas saturationdrainage critical gas saturationdrainage critical gas saturationdrainage critical gas saturation
AAPG ACE 2009: Denver Colorado 30
AAPG ACE Short Course 1: 06.06.2009 15 of 217
Cluff: Introduction and Overview
Why is Sgc important?Why is Sgc important?
0.1
1
bilit
y
P = 1.7Sgc = f (kik)
0.0001
0.001
0.01
Gas
Rel
ativ
e Pe
rmea
P = f (kik)Sgc = 10%
AAPG ACE 2009: Denver Colorado 31
2 alternative views of what happens at high 2 alternative views of what happens at high Sw, which is correct?Sw, which is correct?
0.000010 10 20 30 40 50 60 70 80 90 100
Water Saturation
Saturation at capillary equilibrium for Saturation at capillary equilibrium for breakthrough pressure (Hg experiment)breakthrough pressure (Hg experiment)
60
Pc
20
30
40
50
atio
n at
Bre
akth
roug
h in
Eq
uilib
rium
(%)
AAPG ACE 2009: Denver Colorado 32
0
10
0 10 20 30 40 50 60Critical Saturation at Breakthrough (%)
Satu
r
proof of concept dataset, 2005
AAPG ACE Short Course 1: 06.06.2009 16 of 217
Cluff: Introduction and Overview
SCAL workSCAL workroutine and routine and in situin situ mercury capillary mercury capillary pressurepressuredrainage critical gas saturationdrainage critical gas saturationdrainage critical gas saturationdrainage critical gas saturationcementation and saturation exponentscementation and saturation exponentscation exchange capacity using multication exchange capacity using multi--salinity salinity methodmethod
AAPG ACE 2009: Denver Colorado 33
When F and When F and φφ are plotted logare plotted log--loglog
1000 m= 3m= 2
but not this!
F10
100m= 1
We’ve seen this before,
but not this!
AAPG ACE 2009: Denver Colorado 34
φlog F = -m log φ
10.01 0.1 1
AAPG ACE Short Course 1: 06.06.2009 17 of 217
Cluff: Introduction and Overview
ProductsProductswebweb--based database with output as XLS files, based database with output as XLS files, graphical output, reports and presentationsgraphical output, reports and presentations
organized by data type and by area, wellorganized by data type and by area, wellhtt // k k d / d /htt // k k d / d /http://www.kgs.ku.edu/mesaverde/http://www.kgs.ku.edu/mesaverde/http://www.discoveryhttp://www.discovery--group.com/projects_doe.htmgroup.com/projects_doe.htm
methods for improved log calculationsmethods for improved log calculationsindustry talks, short courses, & forthcoming industry talks, short courses, & forthcoming publicationspublicationsso here we go..........so here we go..........
AAPG ACE 2009: Denver Colorado 35
AAPG ACE Short Course 1: 06.06.2009 18 of 217
Webb: Lithofacies and Reservoir Quality
Influence of Lithofacies and DiagenesisInfluence of Lithofacies and Diagenesison Reservoir Quality of the Mesaverdeon Reservoir Quality of the Mesaverdeon Reservoir Quality of the Mesaverde on Reservoir Quality of the Mesaverde
Group, Piceance Basin, ColoradoGroup, Piceance Basin, Colorado
John WebbJohn WebbDisco er Gro p Den er CODisco er Gro p Den er CO
Denver, Colorado
Discovery Group, Denver, CODiscovery Group, Denver, CO
AAPG Short Course no. 1, Denver, COAAPG Short Course no. 1, Denver, CO
June 6, 2009June 6, 2009
11
OutlineOutline
Data collection procedures and methodsData collection procedures and methodsDi it l k l ifi ti tDi it l k l ifi ti tDigital rock classification systemDigital rock classification systemThin section preparation and petrographyThin section preparation and petrographyExample from the Piceance basinExample from the Piceance basinPaleogeography and depositional environmentsPaleogeography and depositional environmentsLithofacies and porosity/permeability relationshipsLithofacies and porosity/permeability relationshipsDetrital composition and diagenesisDetrital composition and diagenesisPorosity distributionPorosity distributionInfluence of diagenesis on reservoir qualityInfluence of diagenesis on reservoir quality
2
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Webb: Lithofacies and Reservoir Quality
AcknowledgementsAcknowledgementsIndustry Partners:Industry Partners:
Bill Barrett Corporation Bill Barrett Corporation -- Steve CumellaSteve Cumella
EnCana USA, Piceance Teams EnCana USA, Piceance Teams -- Brendan Curran, Brendan Curran, Mike Dempsey, Danielle Mike Dempsey, Danielle StricklerStrickler
ExxonMobil, Piceance Basin TeamExxonMobil, Piceance Basin TeamDonDon YurewiczYurewicz HollieHollie KelleherKelleherDon Don YurewiczYurewicz, , HollieHollie Kelleher Kelleher
Williams Production Williams Production -- Lesley EvansLesley Evans
3
AcknowledgementsAcknowledgementsContractors and Government:Contractors and Government:
ElitigraphicsElitigraphics –– Peter Peter HutsonHutson
Triple O Slabbing Triple O Slabbing -- Butch OliverButch Oliver
USGS Personnel USGS Personnel -- Phil Nelson, Mark KirschbaumPhil Nelson, Mark Kirschbaum
USGS C R h C tUSGS C R h C tUSGS Core Research CenterUSGS Core Research CenterTom Michalski, Betty Adrian (current director)Tom Michalski, Betty Adrian (current director)Jeannine Honey, John Rhodes, Josh Hicks, Jeannine Honey, John Rhodes, Josh Hicks, Terri Huber, Richard Nunn, Devon Terri Huber, Richard Nunn, Devon ConnelyConnely
4
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Webb: Lithofacies and Reservoir Quality
Core sampling and descriptionCore sampling and description
Cut 1” diameter plugs from butt portions of Cut 1” diameter plugs from butt portions of slabbedslabbedcore, using water cooled diamond drill bitcore, using water cooled diamond drill bitLocation of core plugs to 0.1 footLocation of core plugs to 0.1 footDigital rock typing of each core plug (lithology, grain Digital rock typing of each core plug (lithology, grain size, porosity, sedimentary structures, cementation)size, porosity, sedimentary structures, cementation)Scanned core slab images and handScanned core slab images and hand--held digital held digital photos for core plug locations and documentation of photos for core plug locations and documentation of lithology and sedimentary structureslithology and sedimentary structurest o ogy a d sed e ta y st uctu est o ogy a d sed e ta y st uctu esCore descriptions from slabbed core when possibleCore descriptions from slabbed core when possible
5
Core sampling and descriptionCore sampling and description
Logged lithology, grain size, matrix porosity, Logged lithology, grain size, matrix porosity, sedimentary structures, fractures, trace fossils, sedimentary structures, fractures, trace fossils, contact relationships and digital rock type atcontact relationships and digital rock type atcontact relationships and digital rock type at contact relationships and digital rock type at minimum ½ foot intervalsminimum ½ foot intervalsComparator for grain size determinationComparator for grain size determinationHClHCl for identification of calcareous cementsfor identification of calcareous cementsLegacy core analysis data and whole core Legacy core analysis data and whole core photographs on file at USGS CRC or from current photographs on file at USGS CRC or from current well operatorswell operatorswell operatorswell operators
6
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Barrett Last Dance 43C Barrett Last Dance 43C –– Typical Core ChartTypical Core Chart
7
Digital Core Digital Core DescriptionDescription
Sampling designed to Sampling designed to sample across allsample across allsample across all sample across all lithofacieslithofacies5 digit system5 digit system
basic type (Ss, Ls, coal)basic type (Ss, Ls, coal)grain size/sorting/texturegrain size/sorting/textureConsolidation/porosityConsolidation/porositysedimentary structuresedimentary structurecement mineralogycement mineralogy
Provides lithology Provides lithology log log traces and quantitative traces and quantitative variables for multivariate variables for multivariate analysisanalysis
8
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Digital Rock TypesDigital Rock Types
10xxx Shale11xxx Silty shale12xxx V shaly sandstone
Grain size/sorting/ shaliness Visible porosity
xx0xx 0-2%, unfracturedxx1xx 0-2% fractured
2 3 10% f ’d12xxx V shaly sandstone,siltstone
13xxx Shaly sandstone14xxx VF sandstone15xxx F sandstone16xxx M sandstone17xxx C sandstone18xxx VC/Matrix
supported cgl.
xx2xx 3-10%, unfrac’dxx3xx 3-10%, frac’dxx4xx 3-10%, highly fracxx5xx >10%, unfrac’dxx6xx >10%, frac’dxx7xx >10%, unfrac’dxx8xx V high, weak
consolidationxx9xx Unconsolidatedpp g
19xxx Conglomerate
05000 Volcanic ash2xxxx Limestone30000 Coal
xx9xx Unconsolidated
Porosity/ Resistivity logs
GR/Porosity/ Resistivity logs9
Digital Rock Types, cont.Digital Rock Types, cont.
Cementxxxx0 Pyrite
1 Sid i
Sedimentary struc’sxxx0x Vertical dikexxx1x Bioturbatedxxx2x Contorted xxxx1 Siderite
xxxx2 Phosphatexxxx3 Anhydrite xxxx4 Dolomitexxxx5 Calcitexxxx6 Quartzxxxx7 Authigenic clayxxxx8 Carbonaceousxxxx9 No pore filling
xxx2x Contortedxxx3x Discontinuous
laminationsxxx4x Continuous
laminationsxxx5x Flaser beddedxxx6x Ripple laminatedxxx7x Trough & planar
tabular crossbeds xxxx9 No pore fillingDensity/ Resistivity/ PE logs
10
xxx8x Planar laminated, low angle cross bedded
xxx9x Massive beddedShaliness, vertical and lateral permeability
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15277 - Medium sandstone withmoderate porosity, not fractured,trough cross bedded,clay cementedclay cemented
11
Utility of digital rock typing, continuedUtility of digital rock typing, continued
Excellent match with GR log traces, core gammaExcellent match with GR log traces, core gammaPrecise depth shifting of core analysis dataPrecise depth shifting of core analysis dataD t t i fl f i i d h liD t t i fl f i i d h liDemonstrates influence of grain size and shaliness on Demonstrates influence of grain size and shaliness on porosity and permeabilityporosity and permeabilityAllowed improvement of equations used to calculate Allowed improvement of equations used to calculate Archie Archie SwSw, total and effective porosity and significantly , total and effective porosity and significantly improved estimates of permeabilityimproved estimates of permeabilityRock types are not restricted to a specific depositional Rock types are not restricted to a specific depositional environmentenvironmentLog analysis identified detrital shale component, but Log analysis identified detrital shale component, but failed to identify details of grain size and sedimentary failed to identify details of grain size and sedimentary structuresstructures
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Correlation of lithofacies and core Correlation of lithofacies and core analysis data to analysis data to wirelinewireline logslogs
13
Utility of digital rock typingUtility of digital rock typing
Track statistical distribution of lithofacies for Track statistical distribution of lithofacies for sampling and core analysis datasampling and core analysis dataProvides quantitative variables for multivariate Provides quantitative variables for multivariate analysisanalysisThe simple variation in grain density from basin to The simple variation in grain density from basin to basin indicates that differences in detrital basin indicates that differences in detrital composition of sediment, depositional environment, composition of sediment, depositional environment, burial history and diagenesis among basins burial history and diagenesis among basins requires separate treatment of basins for requires separate treatment of basins for assessment of reservoir qualityassessment of reservoir quality
14
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Grain densities of the Grain densities of the Mesaverde GroupMesaverde Group
60
atio
nGreen River
10
20
30
40
50en
t of B
asin
Pop
ula Green River
PiceancePowder RiverUintahWind RiverWashakieSand Wash
0
10
2.58-2.60
2.60-2.62
2.62-2.64
2.64-2.66
2.66-2.68
2.68-2.70
2.70-2.72
2.72-2.74
Grain Density (g/cc)
Perc
15
Thin section preparationThin section preparationBlueBlue--dyed epoxy, low viscosity, slow curedyed epoxy, low viscosity, slow cureVacuum and pressure impregnation in warm Vacuum and pressure impregnation in warm ovenovenovenovenPolished surfaces of billet and mounted Polished surfaces of billet and mounted slideslideDual carbonate stained for nonferroan (red) Dual carbonate stained for nonferroan (red) and ferroan carbonate (various shades of and ferroan carbonate (various shades of blue)blue)blue)blue)Stained for potassium feldspar (KStained for potassium feldspar (K--spar is spar is yellow)yellow)Cover slipsCover slips
16
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Thin section petrographyThin section petrography
Nikon and Nikon and LeitzLeitz petrographic microscopespetrographic microscopesConventional film and digital photography, Conventional film and digital photography, representative magnifications and detailed representative magnifications and detailed featuresfeatures300 point counts per sample, automated 300 point counts per sample, automated point count stagepoint count stageCalculations in Excel, graphic plots in Calculations in Excel, graphic plots in g p pg p pQuattro Pro and Excel spreadsheetsQuattro Pro and Excel spreadsheets
17
Utility of thin section petrographyUtility of thin section petrographyDetrital compositionDetrital composition
ProvenanceProvenanceRadioactive components for GR matchRadioactive components for GR matchRadioactive components for GR matchRadioactive components for GR matchBulk density of constituent grainsBulk density of constituent grains
CementsCementsBulk density of constituent cement (calcite, Bulk density of constituent cement (calcite, dolomite, pyrite, clay)dolomite, pyrite, clay)
Distribution of clayDistribution of clayDistribution of clayDistribution of clayDetrital Detrital -- laminated, structural, dispersed laminated, structural, dispersed (burrowing)(burrowing)Clay cements Clay cements –– porepore--lining, porelining, pore--bridging or bridging or disperseddispersedClay mineralogy (visual morphology)Clay mineralogy (visual morphology) 18
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Utility of thin section petrographyUtility of thin section petrographyDiagenesisDiagenesis
Assess the effect of compaction and pressure Assess the effect of compaction and pressure solutionsolutionDocument changes in detrital grains or rock Document changes in detrital grains or rock fabricfabric
Porosity distributionPorosity distributionMesoporosity, microporosity, moldic and Mesoporosity, microporosity, moldic and intragranular porosityintragranular porosityCompare relative abundance of Meso vs. MicroCompare relative abundance of Meso vs. Micro
FracturesFracturesAssess the importance of microfracturesAssess the importance of microfracturesIdentify fracture cementsIdentify fracture cements
19
Paleogeography of Mesaverde Group, Paleogeography of Mesaverde Group, Uinta and Piceance BasinsUinta and Piceance Basins
Early Clagget time, Mancos Shale Middle Judith River time,
Iles Formation (Rollins, Cozette and Corcoran Ss)
Middle Bear Paw time,Williams Fork Formation
McGookey, et al., 1972
approx 80 mya
approx 73 mya
approx 70 mya20
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Depositional environments of the Depositional environments of the MesaverdeMesaverde
Shallow marine and shoreline environments, Shallow marine and shoreline environments, including lagoonal bayincluding lagoonal bay fill and coastalfill and coastalincluding lagoonal, bayincluding lagoonal, bay--fill and coastal fill and coastal marshmarshTidal delta, tidal channel, mudflat and tidally Tidal delta, tidal channel, mudflat and tidally influenced coastal streamsinfluenced coastal streamsCoal swamps (raised mire) and coastal plainCoal swamps (raised mire) and coastal plainFl i l h l i l di tid ll i fl dFl i l h l i l di tid ll i fl dFluvial channel, including tidally influencedFluvial channel, including tidally influencedAbandoned channel and overbank/splayAbandoned channel and overbank/splayPaleosolsPaleosols, rooted horizons, air fall ash and , rooted horizons, air fall ash and lacustrine to shallow marine limestonelacustrine to shallow marine limestone
21
Example: The Piceance BasinExample: The Piceance Basin
Core analysis: Core analysis: RoutineRoutine -- 629 samples, SCAL629 samples, SCAL -- 46 samples46 samplesRoutine Routine 629 samples, SCAL 629 samples, SCAL 46 samples46 samples
Mercury invasion and imbibition curves for 8 Mercury invasion and imbibition curves for 8 samplessamplesCore description and petrography : Core description and petrography :
6 wells, 2 shallow bore holes, 1168’ core, 46 thin 6 wells, 2 shallow bore holes, 1168’ core, 46 thin section point counts section point counts
L l iL l iLog analysis:Log analysis:Modern log suites for 5 wells, various vintages and Modern log suites for 5 wells, various vintages and format for format for 11 older well and 2 shallow bore holesolder well and 2 shallow bore holes
22
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Mesaverde Group cores, Piceance BasinMesaverde Group cores, Piceance Basin
W Fuels 21011-5 Moon Lake White River Dome
EM WR T63X-2G
Chevron 33-34MWX-2 BBC LD 43C-3-792
Moon Lake
USGS BC 1
White River Dome
Love Ranch
Grand Valley
Parachute
RulisonMamm Creek
FR M30-2-96W WRD
Wms PA 424-34
23
Stratigraphic distribution of samples, Stratigraphic distribution of samples, Piceance BasinPiceance Basin
33-34
USGS Coal Resources, #1 Book Cliffs outcrop core
10,500 ft5700 ft4,600 ft
3,500 ft
8,100 ft
6,500 ft 6,600 ft
250 ft
6,300 ft
24
8200 ft
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Barrett Last Dance 43C Barrett Last Dance 43C –– Shallow Marine/CoastalShallow Marine/Coastal
25
Barrett Last Dance 43C Barrett Last Dance 43C –– Coastal MudstonesCoastal Mudstones
26
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Barrett Last Dance 43C Barrett Last Dance 43C –– FluvialFluvial
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Lithofacies Lithofacies -- Influence of grain size and shaliness on Influence of grain size and shaliness on porosity and permeabilityporosity and permeability
100
Phi/K Crossplot Mesaverde Group, Piceance Basin
0.01
0.1
1
10
bien
t Per
mea
bilit
y, in
mD
11XXX12XXX13XXX14XXX15XXX16XXX
28
0.0001
0.001
0 5 10 15 20
Amb
Ambient Porosity, percent
16XXX17XXX
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10
100m
D
Phi/K Crossplot Mesaverde Group, Piceance Basin
0.01
0.1
1
Ambi
ent P
erm
eabi
lity,
in m
11XXX
0.0001
0.001
0 5 10 15 20
Ambient Porosity, percent29
10
100
mD
Phi/K Crossplot Mesaverde Group, Piceance Basin
0.01
0.1
1
Ambi
ent P
erm
eabi
lity,
in m
12XXX
0.0001
0.001
0 5 10 15 20
Ambient Porosity, percent30
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10
100m
D
Phi/K Crossplot Mesaverde Group, Piceance Basin
0.01
0.1
1
Ambi
ent P
erm
eabi
lity,
in m
13XXX
0.0001
0.001
0.0 5.0 10.0 15.0 20.0
Ambient Porosity, percent31
10
100
mD
Phi/K Crossplot Mesaverde Group, Piceance Basin
0.01
0.1
1
Ambi
ent P
erm
eabi
lity,
in m
14XXX
0.0001
0.001
0 5 10 15 20
Ambient Porosity, percent32
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10
mD
Phi/K Crossplot Mesaverde Group, Piceance Basin
0.01
0.1
1
Ambi
ent P
erm
eabi
lity,
in m
15XXX
0.0001
0.001
0 5 10 15 20
Ambient Porosity, percent33
10
mD
Phi/K Crossplot Mesaverde Group, Piceance Basin
0.01
0.1
1
Ambi
ent P
erm
eabi
lity,
in m
16XXX17XXX
0.0001
0.001
0 5 10 15 20
Ambient Porosity, percent34
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10
mD
Phi/K Crossplot Mesaverde Group, Piceance Basin
0.01
0.1
1
Ambi
ent P
erm
eabi
lity,
in m
16XXX17XXX
0.0001
0.001
0 5 10 15 20
Ambient Porosity, percent35
Phi/K Crossplot Mesaverde Group, Piceance BasinFine Grained Ss (15xxx)
Influence of burial on porosity and permeability of lithofaciesInfluence of burial on porosity and permeability of lithofacies
0.1
1
10
100
bien
t Per
mea
bility, in mD
250 ‐ 3999 ft
4000 ‐ 6999 ft
7000 ‐ 10,000 ft
0.001
0.01
0 5 10 15 20 25
Amb
Ambient Porosity, percent36
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Phi/K Crossplot Mesaverde Group, Piceance BasinMedium Grained Ss (16xxx)
Influence of burial on porosity and permeability of lithofaciesInfluence of burial on porosity and permeability of lithofacies
0.1
1
10
100
ability, in m
D
250 ‐ 3999 ft
4000 ‐ 6999 ft
7000 ‐ 10,000 ft
0.001
0.01
0 5 10 15 20 25
Ambien
t Per
mea
Ambient Porosity, percent37
Detrital Composition of SandstonesDetrital Composition of Sandstonesin the Mesaverde Groupin the Mesaverde GroupWhy do we care? Because detrital composition has Why do we care? Because detrital composition has an effect on diagenesis and porosity preservation.an effect on diagenesis and porosity preservation.
In the Mesaverde, quartzose sandstones are In the Mesaverde, quartzose sandstones are preferentially subject to pressure solution preferentially subject to pressure solution compaction and quartz overgrowth cementation compaction and quartz overgrowth cementation (clay cementation may retard overgrowths)(clay cementation may retard overgrowths)
Feldspathic sandstones suffer compaction by grain Feldspathic sandstones suffer compaction by grain rearrangement and brittle rearrangement and brittle deformation, accompanied by clay cement. deformation, accompanied by clay cement.
38
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Detrital Composition of SandstonesDetrital Composition of Sandstonesin the Mesaverde Groupin the Mesaverde Group
Other alterations include dissolution of framework Other alterations include dissolution of framework grains (Kgrains (K--spar and carbonate rock spar and carbonate rock g (g ( ppfragments), resulting in moldic porosity.fragments), resulting in moldic porosity.
Ductile deformation of shale, carbonaceous Ductile deformation of shale, carbonaceous material, volcanic rock fragments and micaceous material, volcanic rock fragments and micaceous grains, brittle deformation of feldsparsgrains, brittle deformation of feldspars
39
Detrital Composition of SandstonesDetrital Composition of Sandstonesin the Mesaverde Groupin the Mesaverde Group
Composition ranges from litharenite to feldspathic Composition ranges from litharenite to feldspathic litharenite lithic arkose sublitharenitelitharenite lithic arkose sublitharenite subarkosesubarkoselitharenite, lithic arkose, sublitharenite, litharenite, lithic arkose, sublitharenite, subarkosesubarkoseand quartzareniteand quartzareniteRock fragments include volcanic, sedimentary and Rock fragments include volcanic, sedimentary and metamorphic grainsmetamorphic grainsVolcanic rock fragments are commonly Volcanic rock fragments are commonly altered, resulting in replacement by altered, resulting in replacement by clayclay silicificationsilicification and partial to complete dissolutionand partial to complete dissolutionclay, clay, silicificationsilicification and partial to complete dissolutionand partial to complete dissolutionSedimentary rock fragments include Sedimentary rock fragments include shale/mudstone, chert and carbonate grainsshale/mudstone, chert and carbonate grains
40
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41
42
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43
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
3544.9
3555.4
Detrital Composition, Barrett Last Dance 43C
Williams Fork Fm
3577.6
4004.3
4013.3
4393.6
4416.6
Top Gas 4363 ft
44
5715.4
6042.4
6337.1
Quartz Feldspar Lithic
Cameo Coal zone
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0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
5734.1
5838.6
5852.3
6536.3
Detrital Composition, MWX‐2
Williams Fork Fm
6542.2
6550.3
7085.5
7133.5
7264.5
7272.8
7276.2Cozette Ss
45
7851.3
7877.5
7880.1
8106.9
8117.9
Quartz Feldspar Lithic
Corcoran Ss
Cozette Ss
SRF – Sedimentary rock fragmentsVRF V l i k f tVRF – Volcanic rock fragmentsPRF – Plutonic rock fragmentsQM – Quartzose metamorphic MRF – Micaceous metamorphic
46
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0.0 5.0 10.0 15.0 20.0 25.0
3544.9
3555.4
Lithic Population, Barrett Last Dance 43C
Williams Fork Fm
3577.6
4004.3
4013.3
4393.6
4416.6
Top Gas 4363 ft
47
5715.4
6042.4
6337.1
Chert Shale Dolostone Volcanic
Cameo Coal zone
0 5 10 15 20 25
5734.1
5838.6
5852.3
6536.3
Lithic Population, MWX‐2
Williams Fork Fm
6542.2
6550.3
7085.5
7133.5
7264.5
7272.8
7276.2Cozette Ss
48
7851.3
7877.5
7880.1
8106.9
8117.9
Chert Shale Limestone Dolostone Volcanic
Corcoran Ss
Cozette Ss
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Cement Distribution in the Mesaverde GroupCement Distribution in the Mesaverde Group
PorePore--lining clay cementslining clay cementsChlorite (common to abundant)Chlorite (common to abundant)MixedMixed--layer illitelayer illite--smectite (sparse to moderate)smectite (sparse to moderate)
PorePore--filling cementsfilling cementsSiderite (trace)Siderite (trace)Pyrite (trace to sparse)Pyrite (trace to sparse)NonNon--ferroan calcite (sparse)ferroan calcite (sparse)Quartz overgrowth (trace to abundant)Quartz overgrowth (trace to abundant)Ferroan calcite and ferroan dolomite (sparse to common)Ferroan calcite and ferroan dolomite (sparse to common)Albite (grain replacement and moldAlbite (grain replacement and mold--filling)filling)Kaolinite (sparse in one sample in Book Cliff outcrop)Kaolinite (sparse in one sample in Book Cliff outcrop)
49
0 5 10 15 20 25
3544.9
3555.4
Cement Types, Barrett Last Dance 43C
Williams Fork Fm
3577.6
4004.3
4013.3
4393.6
4416.6
Top Gas 4363 ft
50
5715.4
6042.4
6337.1
Quartz Og Fe Calcite Chlorite and ML/IS
Cameo Coal zone
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0 5 10 15 20 25 30 35
5734.1
5838.6
5852.3
6536.3
Cement Types, MWX‐2
Williams Fork Fm
6542.2
6550.3
7085.5
7133.5
7264.5
7272.8
7276.2Cozette Ss
7851.3
7877.5
7880.1
8106.9
8117.9
Quartz Og Fe Calcite Chlorite and ML/IS
Cozette Ss
Corcoran Ss
51
Porosity Distribution in the Mesaverde GroupPorosity Distribution in the Mesaverde Group
MesoporosityMesoporosityPore throat apertures <2 micron, > 0.5 micron radiusPore throat apertures <2 micron, > 0.5 micron radiusIntergranular pores, primary and secondary Intergranular pores, primary and secondary Moldic pores (partly and completely dissolved Moldic pores (partly and completely dissolved feldspars, carbonate and volcanic rock fragments (large feldspars, carbonate and volcanic rock fragments (large aspect ratio, pore body/pore throat)aspect ratio, pore body/pore throat)
MicroporosityMicroporosityPore throat apertures <0.5 micron, >0.1 micron radius Pore throat apertures <0.5 micron, >0.1 micron radius PP li i dli i d filli l tfilli l tPorePore--lining and porelining and pore--filling clay cementfilling clay cementIntragranular micropores (altered VRF, clay pellets, shale Intragranular micropores (altered VRF, clay pellets, shale rock fragments, clay and carbonaceous matrix)rock fragments, clay and carbonaceous matrix)
52
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Porosity Distribution in the Mesaverde GroupPorosity Distribution in the Mesaverde Group
NanoporosityNanoporosityPore throat apertures <0.1 micron radiusPore throat apertures <0.1 micron radiusTypical of mudstones, clayTypical of mudstones, clay--sized intergranular, common in sized intergranular, common in d t it l l b t i ld t it l l b t i ldetrital clay or carbonaceous materialdetrital clay or carbonaceous material
FracturesFracturesMacroscopic Macroscopic Microscopic (primarily crushed feldspars or chert, partings Microscopic (primarily crushed feldspars or chert, partings or separations at quartz overgrowth boundaries)or separations at quartz overgrowth boundaries)
53
54Interparticle and intercrystalline Mesoporosity
Interparticle and intraparticleMicroporosity
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0 5 10 15 20 25
3544.9
3555.4
Porosity Distribution, Barrett Last Dance 43C
Williams Fork Fm
3577.6
4004.3
4013.3
4393.6
4416.6
Top Gas 4363 ft
55
5715.4
6042.4
6337.1
BP sBP Mo clfBP
Cameo Coal zone
0 2 4 6 8 10 12
5734.1
5838.6
5852.3
6536.3
Porosity Distribution, MWX‐2
Williams Fork Fm
6542.2
6550.3
7085.5
7133.5
7264.5
7272.8
7276.2Cozette Ss
7851.3
7877.5
7880.1
8106.9
8117.9
BP sBP Mo clfBP
Corcoran Ss
Cozette Ss
56
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57
Porosity Networks in the Mesaverde GroupPorosity Networks in the Mesaverde Group
Type IType IConventional porosity Conventional porosity –– Primary intergranular and Primary intergranular and modified intergranular (e.g. quartz overgrowth modified intergranular (e.g. quartz overgrowth cement, secondary intergranular)cement, secondary intergranular)Lacking clay cementLacking clay cementMesoporosity >> MicroporosityMesoporosity >> MicroporosityPhi=high, K=high, low Swi, efficient drainage, low to Phi=high, K=high, low Swi, efficient drainage, low to moderate Pc entry pressuremoderate Pc entry pressure
Type IIType IIIntergranular and moldic Intergranular and moldic –– May include primary May include primary intergranular and secondary intergranular intergranular and secondary intergranular Trace to absent clay cementTrace to absent clay cementMesoporosity >> MicroporosityMesoporosity >> MicroporosityPhi=high, K=moderate , low to moderate Swi, elevated Phi=high, K=moderate , low to moderate Swi, elevated SrgSrg, moderate Pc entry pressure, moderate Pc entry pressure 58
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Porosity Networks in the Mesaverde GroupPorosity Networks in the Mesaverde Group
Type IIIType IIIRestricted intergranular Restricted intergranular –– ClayClay--lined pores and pore lined pores and pore throats, some moldic and claythroats, some moldic and clay--filled intergranular filled intergranular microporositymicroporositymoderate to common clay cementmoderate to common clay cementMicroporosity Microporosity >> MesoporosityMesoporosityPhi=moderate, K=low, moderate to high Swi, elevated Phi=moderate, K=low, moderate to high Swi, elevated SrgSrg, increased Pc entry pressure, increased Pc entry pressure
Type IVType IVMicrointergranularMicrointergranular –– ClayClay--filled intergranular poresfilled intergranular poresModerate to common clay cementModerate to common clay cementMicroporosity >> MesoporosityMicroporosity >> MesoporosityHigh Swi, Phi=moderate to low, K=low to extremely High Swi, Phi=moderate to low, K=low to extremely low, elevated low, elevated SrgSrg, increased Pc entry pressure, increased Pc entry pressure
59
Porosity Networks in the Mesaverde GroupPorosity Networks in the Mesaverde Group
Type VType VNanointergranularNanointergranular–– Typical of mudstones, clayTypical of mudstones, clay--sized sized intergranular, common clay or carbonaceous materialintergranular, common clay or carbonaceous materialMicroporosity onlyMicroporosity onlyPhi=moderate to low, K=low to extremely low, high Phi=moderate to low, K=low to extremely low, high Swi, extremely high pore entry pressureSwi, extremely high pore entry pressure
60
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Type I (shallow burial)
Porosity consists of well connected primary and secondary intergranular mesopores, sparse moldic pores, quartz overgrowth cement.
Quartz cement is sparse.
Lack of pore-lining clay cement reduces Swi and improves relative permeability.
40X
100X
USGS CB #1 Book Cliffs, 255.8’ Rock type 15567Porosity 24.8% amb., Rhob2.64 g/cc Ka=137.62 mD Kins=112.2 mD
61
Type I (moderate burial)
Porosity consists of moderately connected primary and secondary intergranular mesopores and traces of pore-lining chlorite clay containing microporosity
40X
microporosity.
Quartz cement and ferroan calcite are sparse.
Lack of pore-lining clay cement reduces Swi and improves relative permeability.
100X
Barrett Last Dance 43C, 3544.9’ Rock type 16277Porosity 11.4% Rhob 2.65 g/cc Ka=0.8716 mD Kins=0.4287 mD
62
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Type II
Porosity consists of poorly to moderately connected moldic and secondary intergranular mesopores with traces of pore-lining ML/IS(?) clay, containing microporosity.clay, containing microporosity.
Quartz cement is prominent, ferroan calcite is sparse.
Pore-lining clay cement begins to increase Swi and reduce relative permeability.
40X
Williams PA 424, 6148.8’ Rock type 15276Porosity 9.9% Rhob 2.66 g/cc Ka=0.0237 mD Kins=0.0076 mD
100X 63
Type III
Porosity consists of clay-lined intergranular pores, pore throats are occluded by clay cement, causing elevated Swi, reduced relative permeability and i d P t
40X
increased Pc entry pressure.
Cements include chlorite or ML-IS clay, traces of nonferroan or ferroan calcite, traces of quartz overgrowths.
Inhomogeneous packing and over-sized intergranular pores
100X
Williams PA 424, 4600.3’ Rock type 15297Porosity 12.2% Rhob 2.65 g/cc Ka=0.0178 mD Kins=0.0019 mD
over sized intergranular pores indicate the development of secondary intergranular porosity.
64
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Type III
Porosity consists of clay-lined intergranular pores, pore throats are occluded by clay cement, which causes elevated Swi, reduced relative permeability
d i d P t
400X
and increased Pc entry pressure
Cements include chlorite or ML-IS clay, traces of nonferroan or ferroan calcite, traces of quartz overgrowths.
Inhomogeneous packing and over-sized intergranular pores
400X, XP
over sized intergranular pores indicate the development of secondary intergranular porosity.
.
65
Williams PA 424, 4600.3’ Rock type 15297Porosity 12.2% Rhob 2.65 g/cc Ka=0.0178 mD Kins=0.0019 mD
Type IV
Porosity consists almost entirely of sparse, poorly connected, clay-filled intergranular microporosity.
Quartz cement is prominent
40X
Quartz cement is prominent, ferroan calcite is sparse.
Pore-filling clay cement causes elevated Swi, reduced relative permeability and increased Pc entry pressure.
100X
Williams PA 424, 4686.4’ Rock type 15286Porosity 7.9% Rhob 2.65 g/cc Ka=0.0211 mD Kins=0.0031 mD
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Type V
Porosity consists entirely of sparse, poorly connected microporosity within interparticle voids of mudstone and shale matrix.
Cements include siderite, ferroan calcite and pyrite. Organic matter is locally common.
Abundant clay causes highly elevated Swi, severely reduced permeability and elevated Pc entry pressure.
64X
CER MWX-2, 7085.5’ Rock type 11299Porosity 2.4% Rhob 2.70 g/cc Ka=0.0020 mD Kins=0.00004 mD
p
67160X
100
n mD
Porosity types, Mesaverde, Piceance basin
0.1
1
10
Perm
eability, ambien
t, in
Type I
Type II
Type III
Type IV
Type V
0.001
0.01
0 5 10 15 20 25
P
Porosity, ambient, in percent
68
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100
mD
Porosity types, Mesaverde, Piceance basin250 ‐ 3999 ft minimum burial
0.1
1
10
ermeability, ambien
t, in
m
Type I
Type II
Type III
Type IV
Type V
0.001
0.01
0 5 10 15 20 25
Pe
Porosity, ambient, in percent
69
100
mD
Porosity types, Mesaverde Group, Piceance basin4,000 ‐ 6,999 ft minimum burial
0.1
1
10
ermeability, ambien
t, in
m
Type I
Type II
Type III
Type IV
Type V
0.001
0.01
0 5 10 15 20 25
Pe
Porosity, ambient, in percent
70
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100
mD
Porosity types, Mesaverde Group, Piceance basin7,000 ‐ 10,000 ft minimum burial
0.1
1
10
ermeability, ambien
t, in
m
Type I
Type II
Type III
Type IV
Type V
0.001
0.01
0 5 10 15 20 25
Pe
Porosity, ambient, in percent
71
Diagenetic alterations in the MesaverdeDiagenetic alterations in the Mesaverde
Compaction, ductile and brittle deformationCompaction, ductile and brittle deformationClay cements, primarily chlorite and MLClay cements, primarily chlorite and ML--ISISQuartz overgrowthsQuartz overgrowthsNonferroan calciteNonferroan calciteDissolution of calcite or other precursor cementsDissolution of calcite or other precursor cementsFerroan calcite and ferroan dolomite cementsFerroan calcite and ferroan dolomite cementsReplacement of KReplacement of K--spar by ferroan calcite and spar by ferroan calcite and albite formation of moldic porosityalbite formation of moldic porosityalbite, formation of moldic porosityalbite, formation of moldic porosityDissolution of carbonate rock fragmentsDissolution of carbonate rock fragments
72
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Brittle deformation of K-spar and Pore-lining clay cement – Chlorite, ferroan calcite pore fill
73
Pore-filling chlorite cement with continued burial 74
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Pore-lining clay cement – ML/IS 75
Pore-lining clay cement – ML/IS 76
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Pore-lining clay cement – ML/IS 77
Inhomogeneous packing and relics of calcite cement indicate secondary intergranular porosity
78
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Relic of calcite cement and adjacent secondary intergranular porosity 79
Secondary intergranular pores mimic size and shape of neighboring cement-filled areas 80
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Secondary porosity, created by dissolution of framework grains81
Secondary porosity, created by dissolution of framework grains82
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Secondary porosity, created by dissolution of carbonate framework grains
83
Alteration of potassium feldspar 84
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Alteration of potassium feldspar and VRF’s 85
Alteration of potassium feldspar 86
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Alteration of plagioclase feldspar 87
Alteration of plagioclase feldspar 88
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Alteration of volcanic rock fragments89
Influence of depositional environment on detrital composition 90
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Influence of depositional environment on detrital composition 91
Influence of depositional environment on diagenesis 92
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Pore-filling chlorite in a quartzose sandstone 93
Pore-filling chlorite in a quartzose sandstone 94
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ConclusionsConclusionsRock typing is useful tool for lithofacies Rock typing is useful tool for lithofacies analysis and directing statistical sampling.analysis and directing statistical sampling.Grain size and shale content are the primaryGrain size and shale content are the primaryGrain size and shale content are the primary Grain size and shale content are the primary influences on reservoir qualityinfluences on reservoir qualityCompaction and cementation by clay Compaction and cementation by clay (primarily chlorite and ML(primarily chlorite and ML--IS), quartz and IS), quartz and ferroan calcite further reduce porosity and ferroan calcite further reduce porosity and permeabilitypermeabilityMatrix porosity in the Mesaverde Group Matrix porosity in the Mesaverde Group consists of both primary and secondary consists of both primary and secondary intergranular, moldic and clayintergranular, moldic and clay--filled filled microporositymicroporosity
95
Conclusions, continuedConclusions, continued
Mesofractures, microfractures on the scale of Mesofractures, microfractures on the scale of individual grains and overgrowth partings areindividual grains and overgrowth partings areindividual grains, and overgrowth partings are individual grains, and overgrowth partings are also presentalso presentPorosity type and distribution of clay cements Porosity type and distribution of clay cements help explain the variation of permeability for a help explain the variation of permeability for a given value of porositygiven value of porosityLog analysis is complicated by the presence Log analysis is complicated by the presence g y p y pg y p y pof chlorite clay cement (more on that later…)of chlorite clay cement (more on that later…)
96
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Analysis of Critical Permeability, Capillary Pressure and Electrical Properties for Mesaverde Tight Gas Sandstones from Western
http://www.kgs.ku.edu/mesaverde
Gas Sandstones from Western U.S. Basins
DOE Contract DE-FC26-05NT42660
http://www.discovery-group.com
97
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Analysis of Critical Permeability, Capillary and Electrical Properties
for Mesaverde Tight Gas Sandstones f W t U S B i
Analysis of Critical Permeability, Capillary and Electrical Properties
for Mesaverde Tight Gas Sandstones f W t U S B ifrom Western U.S. Basins from Western U.S. Basins
US DOE # DE-FC26-05NT42660US DOE # DE-FC26-05NT42660http://www.kgs.ku.edu/mesaverdehttp://www.kgs.ku.edu/mesaverde
Core Analysis• Porosity & Grain Density
– Lithologic and other controls– Routine helium– In situ– Pore Volume Compressibility
• Saturation & Capillary Pressure– Routine Analysis (retort, Dean-Stark)– Air-brine, oil-brine, air-mercury– Drainage, imbibition– Centrifuge, Porous-plate, Hg intrusion
I t f i l T ip y
• Permeability– Routine Air– Klinkenberg– Crack & Capillary– Liquid– In situ– Effective & Relative
• Gas oil Oil water Gas water
– Interfacial Tension– Contact Angle– Wettability– Threshold Pressure
• Enhanced Oil Recovery– Chemical (polymer, surfactant, caustic)– Miscible (CO2, N2, Enriched Gas)– Thermal (Steam, Combustion)
• Electrical & Acoustic Properties• Gas-oil, Oil-water, Gas-water• Drainage, imbibition• Steady-state, unsteady-state• Single-phase stationary• Parameters influencing kr
– T, Poverburden, wettability, pore architecture, capillary number
– Fluid Sensitivity
• Electrical & Acoustic Properties – Archie Electrical Properties
• Cementation & Saturation Exponent, Cation Exchange
– Vp & Vs• Rock Mechanics
– Young’s Modulus, Poisson’s Ratio, Bulk Modulus
– Fracture Pressure
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• All petrophysical properties are
• All petrophysical properties are
• X - Composition (broad definition)– Classification (sandstone,
limestone, etc.)– Compositional (mineralogy)– Textural (sorting-grain size
• X - Composition (broad definition)– Classification (sandstone,
limestone, etc.)– Compositional (mineralogy)– Textural (sorting-grain size
PVTXtproperties are physical-chemical in nature and dependent on:
• P – Pressure– Confining/pore
properties are physical-chemical in nature and dependent on:
• P – Pressure– Confining/pore
– Textural (sorting-grain size distribution, roundness, angularity)
– Sedimentologic (bedding, heterogeneity, architecture)
– Porosity/ pore size distribution
– Fluid
– Textural (sorting-grain size distribution, roundness, angularity)
– Sedimentologic (bedding, heterogeneity, architecture)
– Porosity/ pore size distribution
– Fluid• V- Volume/Scale• T – Temperature• t – time/history
(hysteresis)
• V- Volume/Scale• T – Temperature• t – time/history
(hysteresis)
FluidFluid
Always consider at what conditions a property was measured and over what range of conditions the measured property value is valid
PorosityPorosity
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Core Analysis• Porosity
– Classification– Lithologic & other controls– Routine helium– In situ
l ibili
• Saturation & Capillary Pressure– Routine Analysis (retort, Dean-Stark)– Air-brine, oil-brine, air-mercury– Drainage, imbibition– Centrifuge, Porous-plate, Hg intrusion
f i l i– Pore volume compressibility– Wireline-log Analysis
• Permeability– Routine Air– Klinkenberg– Crack & Capillary– Liquid– In situ– Effective & Relative
– Interfacial Tension– Contact Angle– Wettability– Threshold Pressure
• Enhanced Oil Recovery– Chemical (polymer, surfactant,
caustic)– Miscible (CO2, N2, Enriched Gas)– Thermal (Steam, Combustion)Effective & Relative
• Gas-oil, Oil-water, Gas-water• Drainage, imbibition• Steady-state, unsteady-state• Single-phase stationary• Parameters influencing kr
– T, Poverburden, wettability, pore architecture, capillary number
– Fluid Sensitivity
( , )• Electrical & Acoustic Properties
– Archie Electrical Properties• Cementation & Saturation
Exponent, Cation Exchange– Vp & Vs
• Rock Mechanics– Young’s Modulus, Poisson’s Ratio, Bulk
Modulus– Fracture Pressure
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Porosity Types - Classifications
Intraparticle φVuggy φ
Transparticle φF t φ
Various Porosity Nomenclature – genesis, size distribution, flow contribution
Nano <0.1 μmMicro 01.-0.5 μm
Micro φIneffective φ
Vuggy φSecondary φ
Fracture φ Meso 0.5-2 μmMacro 2-10 μmMega 10-100 μm
Interparticle φPrimary φEffective φ
Porosity DefinitionPorosity, n. The ratio of void space to the bulk volume of rock containing that void spacePorosity, n. The ratio of void space to the bulk volume of rock containing that void space
φi=isolatedφc=connected = φcmicro+φcmacro+φboundφ d 0
φ = Vp/(Vp+Vg)
Connected φ
Isolated φ (minor)
φcmacro= connected, >0.5μmφcmicro= connected, <0.5μm, not boundφbound = connected, bound to clay or
surface, water of hydration
• Total φtotal = φc+φi= φcmacro+φcmicro+φbound+φi
• Effective1 φ = φ (excludes φ )
micro φbound-water φ
• Effective1 φeff = φc (excludes φi)• Effective2 φeff = φcmacroi+φmicro (exc φi,
φbound)• Effective3 φeff = φcmacro+φi+φcmicro (exc
φbound)• Effective4 φeff = φcmacro (exc
φi,φcmicro,φbound)
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Packing & Sorting Control on Porosity
(after Bear , 19
Porosity independent of sizeHighly dependent on sorting & packing
Secondary Porosity - Transfer
• Feldspar grain dissolution
t dcreates secondary porosity but removed material often reprecipitates in nearby pore
k li ispace as kaolinite or smectite
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Porosity Measurement• Core Analysis
– Helium Boyle’s law - Dry sample, measure bulk volume, injected gas measures grain volume - measures φc, does not measure φi and may not measure some φbound
– Crushed sample He pycnometer – dry crushed sample material is measured by Boyle’s Law technique measures φBoyle s Law technique, measures φt
– Liquid Resaturation – dry sample is weighed,saturated with liquid of know density and weighed saturated, weight difference measures φc, does not measure φi and may not measure some φbound
– Summation of Fluids – two pieces of native core, one is weighed, crushed, retorted for oil&water content, and weighed; second has bulk volume measured and mercury injected into gas pore space, fluid saturations and porosity calculated for combined volumes – measures combination of φt and φc
– Nuclear Magnetic Resonance – integrated NMR signal is measured on t t d l φsaturated sample – measures φt
• Wireline Logs– Density (ρma- ρb)/ (ρma- ρliq)– Sonic (Δt- Δtma)/(Δtfluid- Δtma)– ResistivityF = a/φm
– NMR– Neutron
Core Analysis Data
Core Analysis Data
Helium Porosimeter Precision• Vg = (Vr +Vc) -P1g/P2gVr
(after Ruth & Pohjoisrinne
Properly performed error in grain volume measurement should be < +0.001 cc
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Porosity Error -Interlaboratory Calibration
• Dotson et al (1951) Avg φ Error = + 0.5• Thomas and Pugh (1988) Maximum “acceptable” deviation =
+ 0 5; 65% of labs in 1987 met that quality assurance criteria+ 0.5; 65% of labs in 1987 met that quality assurance criteria• Quality reviewed data in TGS +0.25 pu (Hunt & Luffel, 1988)
Permeability Permeabilityto air, md Ambient Overburden to air, md Ambient Overburden
Xmean 248 19.0 18.5 261 18.7 18.2Berea Sandstone Samples
1-inch diameter 1.5 -inch diameterPorosity (%) Porosity (%)
std dev 24 0.5 0.4 22 0.4 0.1
Xmean 111 18.9 18.6 120 19.1 19.2std dev 24 0.8 0.6 22 0.8 0.4
Xmean 3.2 14.0 13.8 3 13.8 13.7std dev 0.9 0.6 0.5 0.7 0.7 0.7
Alundum Samples
Bedford Limestone Samples
Interlaboratory comparison - 25 labs (Sprunt et al , 1990)
Routine Porosity Distribution
Routine Porosity Histogram
0.14
0.16
0.18
atio
n
0.02
0.04
0.06
0.08
0.10
0.12
Frac
tion
of P
opul
a
0.000-2 2-4 4-6 6-8 8-10 10-12 12-14 14-16 16-18 18-20 20-22 22-24
Routine Helium Porosity (%)
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Porosity Distribution by Basin
0 30
0.35
0.40
0.45at
ion
Al l BasinsGreater Green RiverWashakieUintaPiceanceWind River
0.05
0.10
0.15
0.20
0.25
0.30
Frac
tion
of P
opul
a
Powder River
• Distribution influenced by sampling – not normally distributed
0.000-2 2-4 4-6 6-8 8-10 10-12 12-14 14-16 16-18 18-20 20-22 22-24
Routine Helium Porosity (%)
Porosity Statistics by Basin All Greater Wind Powder
Basins Green Washakie Uinta Piceance River RiverRiver
Mean 7.1 7.3 9.5 6.1 6.1 5.8 13.2ea 3 9 5 6 6 5 8 3Median 6.2 4.6 8.7 5.9 6.1 5.5 15.1St Dev 5.1 6.4 5.4 4.2 3.8 3.3 4.5Minimum 0.0 0.0 0.0 0.0 0.0 0.0 2.6Maximum 24.9 23.6 23.8 22.2 24.9 13.2 16.9Kurtosis 0.7 -0.4 -0.4 1.1 4.5 -0.8 1.0Skewness 1.0 1.0 0.5 0.9 1.4 0.1 -1.5Count 2209 568 395 539 596 83 28
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Statistics of Paired SamplesPorosity Histogram
0.400.450.50
atio
n
0.80.91.0
0.050.100.150.200.250.300.35
Frac
tion
of P
opul
a
0.10.20.30.40.50.60.7
• Histogram of ratio of paired plug porosities to mean porosity of plug pair. n = 652 x2= 1304
0.00
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
Paired Plugs Porosity Ratio
0.0
Grain Density Grain Density Histogram
0.25
0.30
latio
n
0.00
0.05
0.10
0.15
0.20
Frac
tion
of P
opul
• Mesaverde grain density is normally distributed for entire population (n=2200)
<2.56 2.56-2.58
2.58-2.60
2.60-2.62
2.62-2.64
2.64-266
2.66-2.68
2.68-2.70
2.70-2.72
> 2.72
Grain Density (g/cc)
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Mesaverde Grain Density All Greater Wind Powder
Basins Green Washakie Uinta Piceance River RiverRiver
Mean 2.653 2.648 2.660 2.639 2.660 2.673 2.679Median 2.654 2.645 2.662 2.649 2.661 2.673 2.674St D 0 040 0 029 0 034 0 052 0 038 0 029 0 026
• Statistically meaningful differences exist among
St Dev 0.040 0.029 0.034 0.052 0.038 0.029 0.026Minimum 2.30 2.50 2.47 2.30 2.35 2.51 2.60Maximum 2.84 2.77 2.79 2.80 2.84 2.73 2.75Kurtosis 15.1 2.6 3.7 13.2 14.0 10.2 3.9Skewness -2.00 0.28 -0.18 -2.82 -1.19 -1.87 -0.28Count 2184 566 393 532 583 82 28
basins• Low density minerals: carbonaceous fragments
(1.2-1.4 g/cc), K-feldspar (2.57 g/cc), Illite/smectite (2.60 g/cc)
Grain Density by Basin
Grain Density Histogram
0.50
0.60
latio
n All BasinsGreater Green RiverWashakie
0.00
0.10
0.20
0.30
0.40
Frac
tion
of P
opul Washakie
UintaPiceanceWind RiverPowder River
<2.56 2.56-2.58
2.58-2.60
2.60-2.62
2.62-2.64
2.64-266
2.66-2.68
2.68-2.70
2.70-2.72
> 2.72
Grain Density (g/cc)
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Generic Porosity vs Confining Pressure
(after Byrnes, 1994)
Crack Compressibility• Crack porosity is far more
compressible than normal intergranular porosity
• Walsh & Grosenbaugh (1979) developed a model for fracture
ibili h h d llcompressibility that matches data well and can be expressed, as shown by Ostersen for low-k sandstones, by a linear porosity change with logarithmic change in stress
(after Walsh & Grosenba
(after Ostensen, 1983)
(after Walsh & Grosenba
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Stress-Dependence of Porosity
0.9
1.0ro
sity
0.5
0.6
0.7
0.8
Frac
tion
of Ii
nitia
l Por
• Crossplot of fraction of initial pore volume versus net confining stress for 113 Mesaverde samples. Every sample exhibits a log-linear relationship though slopes and intercepts differ.
0.410 100 1000 10000
Net Confining Pressure (psi)
Pore Volume CompressibilityCformation = ΔVpore/Vpore
Δpσz
Stress field defined by σx, σy, σz
σhydro = K1σz – K2Pinital + K3 (Pinitial-P)Effective stress equation:
K1 = (σx+σy+σz)/3σz; lithostatic stressesK2 = (1-Cb/Cgr); Biot α – effect of pore pressure
σy
σx
Cf ti = K3 Ch d K2 (1 Cb/Cgr); Biot α effect of pore pressureK3 = K2 ((1+ν)/(3-3ν)); effect of pore pressure change, “uniaxial correction”; ν=Poisson’s ratio
Cformation K3 Chydro
Rock Type K1 K2 K3Consolidated Sandstone 0.85 0.80 0.45Friable Sandstone 0.90 0.90 0.60Unconsolidated Sandston 0.95 0.95 0.75Carbonate 0.85 0.85 0.55
(after Yale et al, 1993)
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Type Compressibility CurvesUnconsolidated Friable Consolidated
A -0.00002805 0.0001054 -0.00002399B 300 500 300C 0.1395 -0.225 0.0623D 0.0001183 -0.00001103 0.00004308
Cf = A(σ-B)C + D
σ=K1Pover-K2Pi+K3(Pi-P)
30
40
50
60
me
Com
pres
sibi
lity
psi/1
0^6)
UnconsolidatedFriableConsolidated
0
10
20
0 2,000 4,000 6,000 8,000 10,000
Effective Lab Stress (psi)
Pore
Vol
um (
(after Yale et al, 1993)
Pore Volume Compressibility
-0.05
0.00
nge
Slo
pe
(
-0.25
-0.20
-0.15
-0.10
lativ
e Po
re V
olum
e C
han
1/ps
i)
• Crossplot of slope of log-linear curves in Figure 4.1.6 with porosity. • The relationship between the slope and porosity can be expressed: • Slope = -0.00549 -0.155/φ0.5
-0.300 2 4 6 8 10 12 14 16 18 20 22 24
Routine Helium Porosity (%)
Rel
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Pore Volume Compressibility
1.25
1.30
1.35
Cha
nge
i)
1.05
1.10
1.15
1.20
1.25R
elat
ive
Pore
Vol
ume
CIn
terc
ept (
1/ps
i
• Crossplot of intercept of log-linear curves in Figure 4.1.6 with porosity. The relationship between the intercept and porosity can be expressed:
• Intercept = 0.013 φ + 1.08
1.000 2 4 6 8 10 12 14 16 18 20 22 24
Routine Helium Porosity (%)
Pore Volume Compressibility
• The above equations result in a power-law relationship between pore volume p pcompressibility and net effective confining pressure of a form:
log10 β = C log10 Pe + D• The slope and intercept of the pore volume
compressibility relations can be predicted using:C = -1.035 + 0.106/φ0.5
D = 4.857 φ-0.038
AAPG ACE Short Course 1: 06.06.2009 81 of 217
Byrnes: Porosity, Permeability, and Compressibility
-0.98
-0.97
-0.96
-0.95
Com
pres
sibi
lity
-op
e (1
/psi
)
4.554.604.654.704.754.80
Com
pres
sibi
lity
-In
terc
ept
log10 β = C log10 Pe + D
-1.02
-1.01
-1.00
-0.99
0 5 10 15 20 25Routine Porosity (%)
log
Pore
Vol
ume
CPr
essu
re S
l
4.254.304.354.404.454.50
0 5 10 15 20 25Routine Porosity (%)
log
Pore
Vol
ume
Pres
sure
log10 β C log10 Pe + D• Where:
C = -1.035 + 0.106/φ0.5
D = 4.857 φ-0.038
Pore Volume Compressibility
1000
y (1
0^6/
psi)
10
100
re V
olum
e C
ompr
essi
bilit
y
φ = 21%φ = 18%φ = 15%φ = 12%φ = 8%φ = 6%φ = 4%φ 2%
β =10^[(-1.035+0.106/φ0.5)*log10 Pe+(4.857φ-0.038)]
1100 1000 10000
Net Effective Confining Stress (psi)
Por φ = 2%
AAPG ACE Short Course 1: 06.06.2009 82 of 217
Byrnes: Porosity, Permeability, and Compressibility
In situ vs. Routine Porosity• φi/φo = A logPe + B
φi/φo Slope = A = -0.00549 – 0.155/φ0.5
φi/φo Intercept = B = 1.045 + 0.128/φ φi/φo Intercept B 1.045 0.128/φ
Where: φi = porosity at defined effective in situ stress Pe, φo = reference initial porosityPe = effective confining stressA and B are empirical constants that vary with rock
iproperties
In situ vs. Routine Porosity
1618202224
000
psi (
%)
Mesaverde StudyT ravis PeakMesaverde/FrontierClinton/MedinaLinear (Mesaverde Study)
02468
101214
0 2 4 6 8 10 12 14 16 18 20 22 24
Poro
sity
at P
e =
4,0
All Studies: φi = A φroutine + BMesaverde Study: φi = 0.96 φroutine – 0.73
Travis Peak: φi = 0.95 φroutine – 0.3Mesavrd/Frontier φi = 0.998 φroutine – 0.8Clinton/Medina: φi = 0.966 φroutine + 0.02
0 2 4 6 8 10 12 14 16 18 20 22 24
Routine Porosity (%)
Travis Mesaverde/ Clinton/ MesaverdePeak Frontier Medina Study
A > 0.950 0.998 0.966 0.960B > -0.300 -0.800 0.020 -0.734
Routine Porosity2.0 1.6 1.2 2.0 1.2
24.0 22.5 23.2 23.2 22.3
In situ Porosity (%)
AAPG ACE Short Course 1: 06.06.2009 83 of 217
Byrnes: Porosity, Permeability, and Compressibility
Porosity from Wireline Logs
• Densitye s y• Neutron• Sonic• NMR• NMR
PermeabilityPermeability
AAPG ACE Short Course 1: 06.06.2009 84 of 217
Byrnes: Porosity, Permeability, and Compressibility
Core Analysis• Porosity & Grain Density
– Lithologic & other controls– Routine helium– In situ– Pore volume compressibility
• Saturation & Capillary Pressure– Routine Analysis (retort, Dean-Stark)– Air-brine, oil-brine, air-mercury– Drainage, imbibition– Centrifuge, Porous-plate, Hg intrusion
f i l iPore volume compressibility• Permeability
– Routine Air– Klinkenberg– Crack & Capillary– Liquid– In situ– Effective & Relative
– Interfacial Tension– Contact Angle– Wettability– Threshold Pressure
• Enhanced Oil Recovery– Chemical (polymer, surfactant, caustic)– Miscible (CO2, N2, Enriched Gas)– Thermal (Steam, Combustion)
• Electrical & Acoustic Properties• Gas-oil, Oil-water, Gas-water• Drainage, imbibition• Steady-state, unsteady-state• Single-phase stationary• Parameters influencing kr
– T, Poverburden, wettability, pore architecture, capillary number
– Fluid Sensitivity
• Electrical & Acoustic Properties – Archie Electrical Properties
• Cementation & Saturation Exponent, Cation Exchange
– Vp & Vs• Rock Mechanics
– Young’s Modulus, Poisson’s Ratio, Bulk Modulus
– Fracture Pressure
Original Darcy Flow Measurement
Q = k A dPµ dhµ dh
Analogs in Electric and heat flow
i = 1 A dVd dxd dx
dQ = KH A dTdx
AAPG ACE Short Course 1: 06.06.2009 85 of 217
Byrnes: Porosity, Permeability, and Compressibility
Evolution of Permeability Modelingk=fr2/8
K=Φ/(FsAs2) x (L/La)2
(after CoreLab, 1978)(after Dullien, 1992)
Current Permeability Modeling• Permeability
controlled by:y– pore body size– pore throat size– distribution– connectivity– larger-scale
architecture
AAPG ACE Short Course 1: 06.06.2009 86 of 217
Byrnes: Porosity, Permeability, and Compressibility
Comparison of Sandstone Pore Volume Distribution Measured by Hg Porosimetry
and Photomicroscopy
(after Dullien & Dhawan, 1974)
Liquid Permeability
Q = k A dPµ dL
(liquid)
Q = Volumetric Flow rate (cc/sec)K = Permeability (Darcies)A = Cross-sectional area (cm2)dP = Pressure differential (atm)m = fluid viscosity (centipoise)dL = Length (cm)
(after CoreLab, 1978)
Q = k A (P12-P2
2)µ 2PbzdL
(gas)
AAPG ACE Short Course 1: 06.06.2009 87 of 217
Byrnes: Porosity, Permeability, and Compressibility
Permeability Definitions• Absolute Permeability (k) – Permeability of rock 100%
saturated with fluid of interest• Effective Permeability (keg, keo, kew) – Permeability to fluid
of interest when other fluids are also present in pore space• Relative Permeability (krg, kro, krw) – ke/k, Ratio of effective
to absolute permeability (reference for absolute may be effective at some condition, e.g. keo,Sw/keo,Swi)
• In situ – under reservoir conditions• Klinkenberg – Corrected for low pressure gas slippage
effects• Air – Permeability to air uncorrected for Klinkenberg y g
effect• Routine – Air permeability, generally measured with a
confining stress of less than ~500 psi
Permeability Determination• Full-diameter
– Influenced by microfractures– Averages response of
individual beds
• Probe mini-permeability– Fast– Allows high sampling
densityindividual beds– Possible drilling mud invasion– Less biased
• Plug– Precisely accurate– Possible sampling bias– May miss important beds
y– Accurate for k > 1md
• Chip– Low accuracy– Severe sampling bias
• Percussion Sidewall– Shattereday ss po ta t beds
• Drilled Sidewall– Greater sampling uncertainty– Similar to plug
– Under- and over-estimates properties
• Cuttings– Rarely used– Surface-to volume issues– Sever sampling bias
AAPG ACE Short Course 1: 06.06.2009 88 of 217
Byrnes: Porosity, Permeability, and Compressibility
Klinkenberg Gas Slip
Gaskgas = kliq (1+4cl/r) = kliq (1+b/P)
measurable fluid velocity at wall
LiquidWhere;c = proportionality factor ~ 1l = mean free path at Pr = radius of capillaryb = proportionality constant
=f(r,l,kliq)P = pressure (atm)
Zero fluid velocity at wall
measurable fluid velocity at wall
10
100
or (p
si) Heid et al, 1950
Jones & Owens, 1981 - low k
p ( )Since b is a function of pore radius, mean free path at P, and liquid permeability it can vary from one low k sample to another but values are generally consistent with the Heid et al (1950) graph shown
(after Heid et al, 1950)
0.01
0.1
1
1E-04 0.001 0.01 0.1 1 10 100 1000Klinkenberg Permeability (md)
Klin
kenb
erg
b fa
ctb = 0.867 kliq
-0.33
b = 0.777 kliq-
0.39
General Correlation of Klinkenberg b Factor and Permeability
100
psi) Heid et al, 1950
Jones & O w ens 1981 - low k
0 .1
1
10
kenb
erg
b fa
ctor
( Jones & O w ens , 1981 - low k
b = 0 867 k -0.33
b = 0.777 kliq-0.39
0.011E-04 0 .001 0 .01 0 .1 1 10 100 1000
Klinkenberg Permeability (md)
Klin
k b = 0.867 kliq0.33
AAPG ACE Short Course 1: 06.06.2009 89 of 217
Byrnes: Porosity, Permeability, and Compressibility
Correlation between Gas Slip-factor, b, and Permeability
(after Sampath & Keighin, 1982)
In situ Klinkenberg Permeability
10
100
1000
b fa
ctor
(atm
)
0.1
1
10
1E-08 1E-07 1E-06 1E-05 0.0001 0.001 0.01 0.1 1 10 100 1000
In situ Klinkenberg Permeability (mD)
Klin
kenb
erg
b
k k (1 + 4 L/ ) k (1+b/P)
b = 0.851 kik-0.34 (Present Study)
b = 0.867 kliq-0.33 (Jones & Owens)
b = 0.777 kliq-0.39 (Heid)
kgas = kliquid (1 + 4cL/r) = kliquid (1+b/P) Gas
Liquid
kgas = gas permeability at pore pressurekliquid is liquid permeability and = Klinkenberg permeability kklinkc = proportionality constant (~ 1)L = mean free path of gas molecule at pore pressurer = pore radiusb = proportionality constant (=f(c, L, r))P = pore pressure (atm)
AAPG ACE Short Course 1: 06.06.2009 90 of 217
Byrnes: Porosity, Permeability, and Compressibility
10
100
mea
bilit
ySandstone
Carbonate
Measured Insitu Klinkenberg vs Air Permeability
kik =0.685kia 1.12
0.01
0.1
1
u K
linke
nber
g Pe
rm(m
d)
R2 = 0.98
0.0001
0.001
0.0001 0.001 0.01 0.1 1 10 100In situ Air Permeability (md)
In s
itu
(after Byrnes, 2003)
Comparison of Klinkenberg Prediction Models
1
md)
Byrnes, 2003Jones & Owens, 1981
0.0001
0.001
0.01
0.1
kenb
erg
Perm
eabi
lity
(m
kklink = 0.685 kair1.12
0.000010.00001 0.0001 0.001 0.01 0.1 1
Air Permeability (md)
Klin
J&O (1980): kklink = 10^(-0.0398 logkair2+1.067logkair-0.0825)
valid for upstream pressure = 100 psi
AAPG ACE Short Course 1: 06.06.2009 91 of 217
Byrnes: Porosity, Permeability, and Compressibility
Effect of Partial Water Saturation on Gas Slip
(after Sampath & Keighin, 1982)
“Averaging” Permeability Data• Permeability is a vector• Pseudo-Permeability is
direction dependent
• End-member models– Series Flow
direction dependent• Pseudo-Permeability
“averaging” is a function of flow model (3-D arrangement) assumed– Dependent on geomodel and
assumptions of smaller scale
– Parallel Flow– Random Flow– Vertical flow constraint
• Permeability is frequently scale dependentassumptions of smaller scale
permeability distribution dependent
AAPG ACE Short Course 1: 06.06.2009 92 of 217
Byrnes: Porosity, Permeability, and Compressibility
Typical distributions of Porosity and Permeability
SeriesFlow
Permeability ArchitectureEnd Members
Parallel
HeterogeneousFlow
No vertical cross-flowVertical crossflow
kv=0, kv=Ckh
ParallelFlow
AAPG ACE Short Course 1: 06.06.2009 93 of 217
Byrnes: Porosity, Permeability, and Compressibility
0.01 md 100 mdKarith = 1.010 mdKgeom = 0.011 md
Karith = 99.000 mdKgeom = 91.201 md
• In parallel flow the high perm drives the system• In series flow the low perm drives the system• Cross-flow influences parallel flow in closed systems (see Simulation Section)
0.01 md
100 md
100 md
0.01 md
Flow
100
ft
1 ft0.
01 m
d
0.01
md
100
md
100
md
100
md
0.01
md Kharm = 0.990 md
Kgeom = 91.201 mdKharm = 0.010 mdKgeom = 0.011 md
Core Plug Sampling with Bedding
C
BeddingPlanes
C - Suitable
A - Unsuitable
B – PossiblyB – Possibly suitable
AAPG ACE Short Course 1: 06.06.2009 94 of 217
Byrnes: Porosity, Permeability, and Compressibility
Fraction of Upper Layer Thickness to Total hickness = 0.3
Model of Measured vs Composite Permeability for Layered Samples
Permeability-Porosity Equation : k = 3.65 x 10-5 e(0.68 Φ)
Upper Base Porosity Upper Base Average Permeability Measured RatioLayer Layer Difference Layer Layer Porosity for Average Permeability Measured/
Porosity Porosity Permeability Permeability Porosity Composite(%) (%) (%) (md) (md) (%) (md) (md) Permeability
0 14 14 0.0000365 0.497 9.8 0.0286 0.348 12.22 14 12 0.000142 0.497 10.4 0.0430 0.348 8.14 14 10 0.000554 0.497 11.0 0.0646 0.348 5.46 14 8 0.00216 0.497 11.6 0.0972 0.349 3.68 14 6 0.00841 0.497 12.2 0.146 0.350 2.4
10 14 4 0.0327 0.497 12.8 0.220 0.358 1.612 14 2 0.128 0.497 13.4 0.331 0.386 1.214 14 0 0.497 0.497 14.0 0.497 0.497 1.016 14 -2 1.94 0.497 14.6 0.747 0.929 1.218 14 -4 7.54 0.497 15.2 1.124 2.61 2.320 14 -6 29.4 0.497 15.8 1.690 9.16 5.421 14 -7 58.0 0.497 16.1 2.072 17.7 8.622 14 -8 114 0.497 16.4 2.541 34.7 13.623 14 -9 226 0.497 16.7 3.116 68.1 21.924 14 -10 446 0.497 17.0 3.821 134.1 35.1
Parallel Beds and Sampling• When sample contains
parallel beds of different k the measured k at the average porosity is
10
100
cula
ted
md) 30
35
40&
Upp
er
(%)
Measured Permeability - KmeasCalculated Permeability - KcalcRatio Kmeas/KcalcUpper Bed Porosity
average porosity is always greater than the k calculated for the composite of the individual beds
0.01
0.1
1
Mea
sure
d or
Cal
cPe
rmea
bilit
y (
0
5
10
15
20
25
Rat
io K
mea
s/K
calc
B
ed P
oros
ity
10
ed 35
40
pper
Measured Permeability - KmeasCalculated Permeability - KcalcRatio Kmeas/KcalcUpper Bed Porosity
9 10 11 12 13 14 15 16 17Average Porosity (%)
0.001
0.01
0.1
1
7 8 9 10 11 12 13Average Porosity (%)
Mea
sure
d or
Cal
cula
tePe
rmea
bilit
y (m
d)
0
5
10
15
20
25
30
Rat
io K
mea
s/K
calc
& U
pB
ed P
oros
ity (%
)
Upper Bed Porosity
AAPG ACE Short Course 1: 06.06.2009 95 of 217
Byrnes: Porosity, Permeability, and Compressibility
General Lithologic Controls on the Effect of Overburden Pressure on Permeability
Effect of Confining Pressure on Permeablity
• Early work by Thomas and Ward (1972) Shows the 0.9
1.0
ility
Shows the characteristic decrease in permeability with increasing confining pressure exhibited by low-permeability sandstones
• Samples from Gas buggy well, Pictured 0 2
0.3
0.4
0.5
0.6
0.7
0.8
on o
f Ini
tial P
erm
eabi
buggy well, Pictured Cliffs Fm Rio Arriba Co., NM and Wagon Wheel well, Ft. Union Fm, Sublette Co., WY
0.0
0.1
0.2
0 1000 2000 3000 4000 5000 6000
Confining Pressure (psi)
Frac
ti
AAPG ACE Short Course 1: 06.06.2009 96 of 217
Byrnes: Porosity, Permeability, and Compressibility
Effect of Confining Pressure on Spirit River and Cotton Valley Permeability
(after Walls, 1982)
Permeability Response to Confining Stress for Varying Crack Aspect Ratios
(after Brower & Morrow, 1983)
k/ki = {1-(16(1-n2)cLc)/(9(1-2n)pwi)s}3
AAPG ACE Short Course 1: 06.06.2009 97 of 217
Byrnes: Porosity, Permeability, and Compressibility
Model Type Model Equation .Noncrack Capillary tube k/ki = (1-2s/E)4
Noncrack Gangi, grain, 1978 k/ki = {1-2{3p(1-n2)s/4E}2/3}4
Crack Jones &Owens, 1980 k/ki = {1-Slog(Pk/1000)}3
2 3
Models of Stress Dependent Permeability(after Ostensen, 1983)
Crack Brower & Morrow, 1983 k/ki = {1-(16(1-n2)cLc)/(9(1-2n)pwi)s}3
Asperity Gangi, bed of nails, 1978 k/ki = {1-(s/lE)e}3
Asperity Walsh, exp. dist., 1981 k = Ls3/12 {ln[(nE(prcs3)1/2)/(2(1-n2)s)]}3
Asperity Ostensen, Gauss.,1983 k = 0.76Ls3/12 {ln[(2.48E(s/rc)1/2)/(3p1.5(1-n2)s)]}2
Council Grove LimestonesMesaverde & Frontier
(after Jones &* Owens, 1980) (after Byrnes et al, 2001)
Sheet-like Pores in Travis Peak Sandstone
Transmitted light, 100X Fluorescent epoxy
8,275 ft, k = 0.007 md; SFE Well 2, Waskom Field, Harrison Co., TX(after Soeder & Chowdiah, 1990)
AAPG ACE Short Course 1: 06.06.2009 98 of 217
Byrnes: Porosity, Permeability, and Compressibility
Pressure and Pore Throats
20
25en
cy
High P
Low P
5
10
15
e Si
ze F
requ
e(%
)Low P
0
5
0.01 0.1 1Pore Throat Diameter (um)
Pore
In situ vs Routine Permeability
10
100
eabi
lity Council Grove
Mesaverde/Frontier
0 001
0.01
0.1
1
Klin
kenb
erg
Perm
e(m
d)
logkik = 0.0588 (logkair)3
0.00001
0.0001
0.001
0.001 0.01 0.1 1 10 100Routine Air Permeability (md)
In s
itu K –0.187 (logkair)2
+1.154 logkair - 0.159
AAPG ACE Short Course 1: 06.06.2009 99 of 217
Byrnes: Porosity, Permeability, and Compressibility
Known for many years that lowKnown for many years that low--K K sandstones are stress sensitivesandstones are stress sensitivey = -0.0088x3 - 0.0716x2 + 1.3661x - 0.4574
22
3
(mD
)
Stress dependence of permeability
sandstones are stress sensitivesandstones are stress sensitiveGeneralized = Generalized = f f (P(Pporepore, Lith), Lith)1997 Byrnes equation:1997 Byrnes equation:kkikik = 10^[1.34 (logk= 10^[1.34 (logkairair) ) -- 0.6] 0.6] This study:This study:kkikik = 10^[0.0088 (logk= 10^[0.0088 (logkairair))33 -- 0.072 0.072 (logk(logkairair))22+ 1.37 logk+ 1.37 logkairair +0.46]+0.46]
R2 = 0.9262
-6
-5
-4
-3
-2
-1
0
1
g In
situ
Klin
kenb
erg
Perm
eabi
lity
Statistically similar except for k > Statistically similar except for k > 1 mD1 mDno meaningful stress dependence no meaningful stress dependence over 10 mDover 10 mD
-7-7 -6 -5 -4 -3 -2 -1 0 1 2 3
log Routine Air Permeability Ppore = 100 psi (mD)
log
Permeablity Distribution
0.25
0.30
0.35
pula
tion
0.00
0.05
0.10
0.15
0.20
001-
001
001-
001
001-
001
001-
001
0.01
1-0.
1
0.1-
1
1-10
-100
1000
Frac
tion
of P
op
Distribution of in situ Klinkenberg permeability measured at 26.7 MPa (4,000 psi) net effective stress for all samples
0.00
000
0.00
00
0.00
000.
000
0.00
00.
00
0.00 0.0
0.00
1-0
0.01 0 1
10-
100-
1
In situ Klinkenberg Permeability (mD)
AAPG ACE Short Course 1: 06.06.2009 100 of 217
Byrnes: Porosity, Permeability, and Compressibility
In situ Klinkenberg Permeability Histogram
0 40
0.50
0.60pu
latio
n All BasinsGreater Green RiverWashakieUinta
0.00
0.10
0.20
0.30
0.4000
01-
0001
0001
-00
01
0001
-00
01
0001
-0.
001
-0.0
1
01-0
.1
0.1-
1
1-10
0-10
0
-100
0
Frac
tion
of P
op PiceanceWind RiverPowder River
Distribution of in situ Klinkenberg permeability measured at 26.7 MPa (4,000 psi) net effective stress by basin
0.00
000.
000
0.00
00.
00
0.00 0.0
0.0 0
0.00
1
0.0 10
100-
In situ Klinkenberg Permeability (mD)
Permeability Statistics All Greater Wind Powder
Basins Green Washakie Uinta Piceance River RiverRiver
Mean logk -2.60 -2.49 -2.03 -2.66 -2.95 -3.44 -1.88Median logk -2.93 -3.15 -2.46 -2.86 -3.03 -3.36 -2.21St Dev log 1.58 1.94 1.78 1.36 1.13 0.69 1.39Minimum logk -6.19 -6.19 -5.66 -5.33 -5.23 -5.11 -4.29Maximum logk 2.31 2.31 2.08 1.88 2.05 -1.98 0.55Kurtosis 0.62 -0.54 -0.39 0.17 4.02 -0.49 -0.38Skewness 1.05 0.79 0.76 0.74 1.48 -0.01 0.50Count 2143 555 373 529 577 81 28Mean 0.0025 0.0032 0.0094 0.0022 0.0011 0.0004 0.0133Median 0.0012 0.0007 0.0035 0.0014 0.0009 0.0004 0.0062St Dev 37.9 87.4 59.9 23.0 13.4 4.9 24.5Minimum 0.000001 0.000001 0.000002 0.000005 0.000006 0.000008 0.000051Maximum 206.0 206.0 121.0 76.2 112.2 0.010 3.53a u 06 0 06 0 0 6 0 0 0 3 53Kurtosis 0.62 -0.54 -0.39 0.17 4.02 -0.49 -0.38Skewness 1.05 0.79 0.76 0.74 1.48 -0.01 0.50Count 2143 555 373 529 577 81 28
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Byrnes: Porosity, Permeability, and Compressibility
Permeability Histogram
0 140.160.180.20
latio
n
0 70.80.91.0
0 000.020.040.060.080.100.120.14
Frac
tion
of P
opu
0 00.10.20.30.40.50.60.7
• Histogram of ratio of paired plug in situ Klinkenberg permeabilities to mean permeability of plug pair. n = 634 x2 = 1268
0.00
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
3.0
4.0
5.0 >6
Paired Plugs Permeability Ratio
0.0
Permeability vs Porosity
• Permeability a function of:• Permeability a function of:• Permeability a function of:Grain sizeShale bed architecturePore-throat sizePorosityDiagenetic alteration (including cementation)
• Permeability a function of:Grain sizeShale bed architecturePore-throat sizePorosityDiagenetic alteration (including cementation)g ( g )
• Porosity is optimal predictor parametric with lithofacies
g ( g )
• Porosity is optimal predictor parametric with lithofacies
AAPG ACE Short Course 1: 06.06.2009 102 of 217
Byrnes: Porosity, Permeability, and Compressibility
Permeability as a Function of Grain Size and Sorting
(after Jonas & McBride, 1977)
Influence of Grain Size on Permeability
(from Shanley, 2004)
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Byrnes: Porosity, Permeability, and Compressibility
Permeability vs. Porosity by Grain Size
1
10
100
1000
000
psi,
mD
)
0.000001
0.00001
0.0001
0.001
0.01
0.1
Klin
kenb
erg
Perm
eabi
lity
(4,
X(4-9)XXX
X3XXX
X(0-2)XXX
• Generally subparallel trends increasing in porosity range and permeability at porosity with increasing grain size
• Influence of other variables significant
0.00000010 2 4 6 8 10 12 14 16 18 20 22 24
In situ calc Porosity (%)
K
Dispersed Clay Types in Sandstones Affecting Flow
Discrete ParticleKaolinite
Pore-LiningChlorite
Pore-BridgingIllite
(after Neasham, 1977)
Kaolinite ChloriteMontmorillonite
IlliteMixed-Layer
AAPG ACE Short Course 1: 06.06.2009 104 of 217
Byrnes: Porosity, Permeability, and Compressibility
Influence of Clay types on Permeability
Discrete-particle, pore-lining and pore-bridging Kaolinite, Chlorite, and Illite can each result in permeability decrease by a factor of 1-0.03, 0.2-0.01, and 0.06-0.003, respectively
(after Wilson, 1981)
Discrete Particles-Pore Lining Kaolinite
American Hunter Old Road 8360’ (courtesy John Webb)
AAPG ACE Short Course 1: 06.06.2009 105 of 217
Byrnes: Porosity, Permeability, and Compressibility
Pore Lining Clays
Chlorite
Mixed-Layer Illite-Smectite
American HunterOld Road 5490 ft
(courtesy John Webb)
Illite - Pore Bridging
AAPG ACE Short Course 1: 06.06.2009 106 of 217
Byrnes: Porosity, Permeability, and Compressibility
Permeability vs Porosity• Generalized trend kik = 10[0.3φi-4.75] with 10X error• Different k-φ trends among basins due to lithologic variation• Beyond common k↑ with grain size↑, lithologic influence changes with porosity -
nonlinear
1000
0.001
0.01
0.1
1
10
100
rmea
bilit
y (4
,000
psi
, mD
)
Green RiverPiceancePowder River
0.0000001
0.000001
0.00001
0.0001
0 2 4 6 8 10 12 14 16 18 20 22 24In situ calc Porosity (%)
Klin
kenb
erg
Per
UintahWashakieWind RiverlogK=0.3Phi-3.7logK=0.3Phi-5.7
Permeability vs Porosity• logkik = 0.282φi + 0.182RC2-
5.13 (+4.5X MLRA)• logkik = 0.034φi
2-0.00109φi3 +
0.0032RC2 - 4.13 (+4.1X MNLRA)0.001
0.01
0.1
1
10
100
1000
erm
eabi
lity
(4,0
00 p
si, m
D)
X9XXXX8XXXX7XXXX6XXXX5XXXX4XXXX3XXXX2XXX
( )• Artificial Neural Network +3.3X
0.0001
0.001
0.01
0.1
1
10
100
1000
Pred
icte
d in
situ
Klin
kenb
erg
Perm
eabi
lity
(mD
)
10
100
1000
bilit
y (m
D)
0.0000001
0.000001
0.00001
0.0001
0 2 4 6 8 10 12 14 16 18 20 22 24In situ calc Porosity (%)
Klin
kenb
erg
P X2XXXX1XXX
0.000010.00001 0.0001 0.001 0.01 0.1 1 10 100 1000
Measured in situ Klinkenberg Permeability (mD)
hidden layer: 1Hidden layer nodes: 10
Mean> 8.239 4.280 6.294 hidden layer-Std Dev> 5.260 1.335 2.527 to-output
weightsNode Constant Phii RC2 RC4Constant -0.388
1 -0.760 2.946 -2.027 -6.438 -0.8852 -2.155 4.637 1.279 0.895 2.3233 -4.999 7.901 0.957 3.167 -2.5834 -1.484 -0.307 -1.695 6.175 -0.1545 -4.597 4.582 1.568 0.730 4.0226 -2.609 0.320 -2.201 -2.257 -2.4957 -1.765 -1.843 -1.122 0.145 -3.8598 2.839 -3.146 -9.237 0.264 0.7899 -1.566 1.029 -1.588 -3.390 2.400
10 2.951 0.778 3.316 0.179 -2.136
Input-to-hidden layer weights
0.0000001
0.000001
0.00001
0.0001
0.001
0.01
0.1
1
0 2 4 6 8 10 12 14 16 18 20 22 24Calculated in situ Porosity (%)
in s
itu K
linke
nber
g Pe
rmea
b
1XX9X1XX8X1XX7X1XX6X1XX5X1XX4X1XX3X1XX2X1XX1X1XX0X
AAPG ACE Short Course 1: 06.06.2009 107 of 217
Byrnes: Porosity, Permeability, and Compressibility
Permeability vs Porosity•• Overall trend allows prediction of Overall trend allows prediction of KikKik from porosity with 10X errorfrom porosity with 10X error•• Multivariate linear equations using: 1) porosity, 2) rock class (1Multivariate linear equations using: 1) porosity, 2) rock class (1--3), and for each of three 3), and for each of three
porosity classes separately (0porosity classes separately (0--12%, 1212%, 12--18%, >18%), performed separately for each 18%, >18%), performed separately for each basin, exhibit an average standard error of prediction of: 0basin, exhibit an average standard error of prediction of: 0--12%: 3.612%: 3.6++2.4X; 122.4X; 12--18%: 18%: 3.33.3++3.6X; >18%: 3.1X (for all basins undifferentiated for this high porosity class); 3.6X; >18%: 3.1X (for all basins undifferentiated for this high porosity class); where the range of error for each standard error of prediction indicates the range of where the range of error for each standard error of prediction indicates the range of standard error among basinsstandard error among basinsstandard error among basinsstandard error among basins
•• Beyond common kBeyond common k↑ with grain size↑, ↑ with grain size↑, lithologiclithologic influence changes are complex and influence changes are complex and nonlinearnonlinear
0 01
0.1
1
10
100
1000bi
lity
(4,0
00 p
si, m
D)
Green River
0.0000001
0.000001
0.00001
0.0001
0.001
0.01
0 2 4 6 8 10 12 14 16 18 20 22 24In situ calc Porosity (%)
Klin
kenb
erg
Perm
eab Green River
PiceancePowder RiverUintahWashakieWind RiverlogK=0.3Phi-3.7logK=0.3Phi-5.7
Berea Cotton Valley Canyon
Chacra Wilcox Frontier-Moxa
Cleveland Travis ComparisonCleveland TravisPeak Comparison
of Tight Gas Sand k-fTrends
(from Dutton et al, 1993)
AAPG ACE Short Course 1: 06.06.2009 108 of 217
Byrnes: Porosity, Permeability, and Compressibility
Generalized Tight Gas Sandstone Permeability vs Porosity Trends
10
100m
d) logki = 0.32+0.10 Φi - 5.05+1.48
0.01
0.1
1
itu P
erm
eabi
lity
(
BereaCotton ValleyCanyonFrontier-Moxa ArchWilcoxChacraClevelandTravis PeakMesaverde-GGRB
Data from various sources including Dutton et al, 1993; Byrnes, 2003; Castle and Byrnes, 2005)
0.0001
0.001
0 5 10 15 20 25In situ Porosity (%)
In s Medina
Mesaverde-Uinta
Stressed Permeability Hysteresis• Loading cycles approach similar values near original
reservoir stress• Successive loading cycles cease to exhibit furtherSuccessive loading cycles cease to exhibit further
hysteresis after second loading cycle
(after Thomas & Ward, 1968) (after Warpinski & Teufel, 1990)
AAPG ACE Short Course 1: 06.06.2009 109 of 217
Byrnes: Porosity, Permeability, and Compressibility
Calculating Directional Permeability in Festoon
Cross-Bed Sets
(after Weber, 1982)
Shale Bed Continuity Distribution in Sandstone
Depositional Environmentsp
(after Weber, 1980)
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Byrnes: Porosity, Permeability, and Compressibility
Conclusions•• Grain density, porosity, and permeability measured on ~1500 Grain density, porosity, and permeability measured on ~1500
unique samples and 700 duplicates (5X original proposal)unique samples and 700 duplicates (5X original proposal)•• Core plugs obtained from 44 wells representing approximately Core plugs obtained from 44 wells representing approximately
7,000 feet of described core7,000 feet of described core•• Average grain density for 2200 samples is 2.654+0.033 g/cc Average grain density for 2200 samples is 2.654+0.033 g/cc
((±±1sd) 1sd) –– but grain density distributions differ slightly among basins & but grain density distributions differ slightly among basins &
lithofacieslithofacies. . •• Porosity variance with 1Porosity variance with 1--2 inches (2.52 inches (2.5--5 cm) = 5 cm) = ++10% (1sd)10% (1sd)•• Pore volume compressibility shows a logPore volume compressibility shows a log--linear relationship linear relationship
characteristic of sheet like pores and crackscharacteristic of sheet like pores and cracks
log10 β = C log10 Pe + D where C = -1.035 + 0.106/φ0.5 D = 4.857 φ-0.038
•• Lower porosity rocks exhibit greater pore volume compressibility Lower porosity rocks exhibit greater pore volume compressibility than high porosity rocks consistent with observed than high porosity rocks consistent with observed φφii vsvs φφroutineroutinetrendstrends
Conclusions•• KlinkenbergKlinkenberg slip term “b” consistent with prior trends to 1 slip term “b” consistent with prior trends to 1 μμDD•• Geometric mean permeability = 0.0025 Geometric mean permeability = 0.0025 mDmD, median = 0.0012 , median = 0.0012 mDmD•• Stress dependence of permeability is consistent with prior work Stress dependence of permeability is consistent with prior work
(Byrnes, 1997)(Byrnes, 1997)( y )( y )•• PorosityPorosity--permeability data exhibit two permeability data exhibit two subtrendssubtrends with with
permeability prediction approaching 5X within eachpermeability prediction approaching 5X within each–– Adding rock types or using an ANN model improves perm Adding rock types or using an ANN model improves perm
prediction to 3.3X prediction to 3.3X –– 4X4X•• Multivariate linear equations using: 1) porosity, 2) rock class (1Multivariate linear equations using: 1) porosity, 2) rock class (1--
3), and for each of three porosity classes separately (03), and for each of three porosity classes separately (0--12%, 1212%, 12--18%, >18%), performed separately for each basin, exhibit an 18%, >18%), performed separately for each basin, exhibit an average standard error of prediction of: 0average standard error of prediction of: 0--12%: 3.612%: 3.6++2.4X; 122.4X; 12--18%: 3.318%: 3.3++3.6X; >18%: 3.1X (for all basins undifferentiated for 3.6X; >18%: 3.1X (for all basins undifferentiated for this high porosity class); where the range of error for each this high porosity class); where the range of error for each standard error of prediction indicates the range of standard error standard error of prediction indicates the range of standard error among basinsamong basins
AAPG ACE Short Course 1: 06.06.2009 111 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Saturation &Saturation &Saturation & Capillary
Saturation & Capillary PressurePressure
Water Saturation• Water saturations in reservoir determined
using three basic methodsWi li l– Wireline logs
• Electric logs• NMR logs
– Fluid saturations from core• Routine core• Sponge corep g• High-pressure core• Oil- & low-invasion and water-based mud
– Capillary pressure measurements on core
AAPG ACE Short Course 1: 06.06.2009 112 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Influence of Core Flushing with Water-based Mud on Saturations
(after CoreLab, 1982)
“Averaging” Saturation Data
• Saturation is a scalar Σ S φ •h
i=n
but is dimensionless• Sw should not be
averaged • BVW is averaged and
then converted back to Sw
Swaverage =
Σ φihii=1
i=n
Σ Swi φi •hii=1
Sw(Averaging for a well by thickness)
AAPG ACE Short Course 1: 06.06.2009 113 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Buckles Plot – Piceance Basin
70
80
90
100ai
ton
(%) MWX-1
MWX-2MWX-3Buckles 600Buckles 300
20
30
40
50
60
70
outin
e C
ore
Wat
er S
atur
a
Buckles 240Buckles 180
Trendlines shown represent Sw = Aφ-1.1 where A = 180. 240. and 300, respectively. Differences in trends can be postulated to be due to differences in grainsize and/or clay type/content.
0
10
0 1 2 3 4 5 6 7 8 9 10 11 12 13Routine Core Porosity (%)
Ro
Buckles Plot – Piceance Basin
70
80
90
100
raito
n (%
) 4800-49355475-54855700-58456420-65557080-7180
10
20
30
40
50
60
70
Rou
tine
Cor
e W
ater
Sat
ur 7230-73607800-78908100-8120Buckles 7852-7863Buckles 7848-7877Buckle 7873-7886
• Routine core analysis porosity versus water saturation for the Piceance Basin MWX-2well. Saturation versus porosity trends exhibit commonly observed Buckles power-law relationship. Trendlines for depth intervals 7852-7886 shown represent Sw = Aφ-1.1 where A = 180. 240. and 300, respectively. Differences in trends can be postulated to be due to differences in grainsize and/or clay type/content.
0
10
0 1 2 3 4 5 6 7 8 9 10 11 12 13Routine Core Porosity (%)
R
AAPG ACE Short Course 1: 06.06.2009 114 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Drop Cohesive Forces
Forceout = π r2 ΔPForce = 2π r σσ Forcein = 2π r σAt equilibrium:
Fout=Fin
π r2 ΔP = 2π r σrearranging
σ
σP1
rearrangingΔP = 2σ/r
Where :σ=interfacial tension (dyne/cm)r = radius (cm)
P2
Capillary Pressurerliq = rcap/cosθPc = Pnw Pwr Pc = Pnw-Pw
= 2σ/rliq
= 2σcosθ/rcap
rcap
rliqPnw
Pw q
AAPG ACE Short Course 1: 06.06.2009 115 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Capillary Pressure in Uniformly Variable Capillary
(after Lake, 2005)• Pc = 2τ cosθ/rPc = capillary pressureτ = interfacial tensionθ = contact angler = pore radius
Capillary Rise
Pnw
Pnw
r
Pw
Pw
Pw
Pw* Pw* Pw*
h
hh
Pnw
FreeWaterLevelPnw=Pw
Pnw
Pw-Pnw = (ρw-ρnw) h g
Water
AAPG ACE Short Course 1: 06.06.2009 116 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Capillary Pressure Equations• Pc = 2τ cosθ/r
where:P ill
• H = Pcres . (σbrine-σoil,gas) x 0.433
Where:H = height above free water levelPc = capillary pressure
τ = interfacial tensionθ = contact angler = pore radius
Pcres = Pcair-Hg τcosθres
τcosθair-hg
H height above free water levelPcres = reservoir capillary pressurePcair-Hg = air-mercury Pcσbrine = specific density of brine (g/cc)σoil,gas = specific density of oil or gas (g/cc)0.433 = conversion from density (g/cc)
to pressure gradient (psi/ft)
water
P
r = 2τ cosθ/PcH
rH
rB
oil
PhH
PwH
PhB
PwB
Capillary Pressure Equations• Pc = 2τ cosθ/r• r = 2τ cosθ/Pc
h
• H = Pcres .(σbrine-σoil,gas) x 0.433
• Pcres = Pcair Hg τcosθreswhere:Pc = capillary pressureτ = interfacial tensionθ = contact angler = pore radius
Pcres Pcair-Hg τcosθres
τcosθair-hg
AAPG ACE Short Course 1: 06.06.2009 117 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Dep
th
(after Doveton, 1999)
Capillary Pressure MeasurementMercury Injection Porous Plate
Centrifuge
• Air-mercury• Air-brine• Oil-brine• Gas-oil
• Drainage• Imbibition
AAPG ACE Short Course 1: 06.06.2009 118 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Mercury Capillary Pressure
(after Jennings, 1981)
Capilary Pressure Measurement
• Three different i H
high-P fluid
In situ Mercury Intrusion Unconfined (routine) Mercury Intrusion
air-Hg measurements– Unconfined
(n=150)– In situ
• Drainage-
Res
ista
nce
Ref
eren
ceC
ell
hi h P
Cor
e P
lug
hi h P
Cor
e Pl
ug
gimbibition (n=37)
• Drainage only (n=90)
• NES = 4000 psi
high -Pcore holder
mercury in
electricinsulator
Pressuretransducer
high -Pcore holder
mercury in
Pressuretransducer
AAPG ACE Short Course 1: 06.06.2009 119 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Unconfined Capillary Pressure
78000
900010000
C ill P
30004000
50006000
7000
Air-Hg Capillary Pressure (psia)
• Capillary Pressure Varies with Lithofacies and associated pore size distribution and
0 10 20 30 40 50 60 70 80 90 100
01000
2000
Wetting Phase Saturation (%)
permeability
Capillary 1000
10000
ssur
e (p
sia)
Capillary Pressure Varies with Lithofacies and associated
pore size distribution
100
ercu
ry In
ject
ion
Pres 0.00025md
0.00049md0.0012md0.0017md0.0018md0.0030md0.0040md0.0057md0.0085md0.012md0.013md0.032md0.046md0.085md0.25md0.41md0.56md
100 10 20 30 40 50 60 70 80 90 100
Wetting Phase Saturation (%)
Me 0.56md
0.84md2.24md
AAPG ACE Short Course 1: 06.06.2009 120 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Normalizing Capillary Pressures• Capillary pressure curves change with permeability and
porosity• To predict water saturation from capillary pressure it is
necessary to either– Know the specific conditions at a given point and use a appropriate
measured capillary pressure– Construct a synthetic capillary pressure curve for the conditions at the
point– Develop a relation between a normalized capillary pressure function
and saturation• Two principal approaches for normalization or synthetic curve
iconstruction:– Leverett “J” function (Leverett, 1941)– Unpublished normalization of Brooks-Corey l function (Brooks and
Corey, 1964)• Fractal model extension of B-C
Leverett J function• J(Sw) = CPc (k/φ)0.5/τcosθ
– J = dimensionless Pc function, function of SwSw
– C = conversion constant = 0.2166– Pc = capillary pressure (psi)
– τcosθ = interfacial tension (dyne/cm) X cosine of the contact angle (degrees)
– k = permeability (md)
– φ = porosity (fraction)
AAPG ACE Short Course 1: 06.06.2009 121 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Basic Leverett J Function• At its simplest a Leverett J
function is constructed by plotting taking a series of capillary pressure curves forcapillary pressure curves for samples of different porosity and permeability and plotting the J value versus the water saturation
• From the cross-plot a curve is constructed that honors th d tthe data
• For some formationsSw = -Alog10J + B
• Valid J<1; For J>1 then Sw=Swi
•A problem with the Leverett J function is the wide variance in saturation that occurs near the “irreducible” water saturation which is the saturation of principal interest for many analyses
Leverett J Adjustment for Swi• Because of the problem that Leverett J functions can have
near the “irreducible” water saturation (Swi) aspects of the Brooks-Corey method have been adopted to improve the J-S l ti b li i f S iSw correlation by normalizing for Swi
• Water saturation is normalized using:– Swe = (Sw-Swi)/(1-Swi) where Swe = effective water saturation,
Sw = water saturation at any given Pc and Swi = “irreducible” water saturation
– Method is dependent on criteria for defining Swi• Plot of J versus log Swe is generally linear with a constant
slope, λ, and an intercept, J*, related to the J function normalized threshold entry pressure.
• The calculation of water saturation requires knowledge or back-calculation of Swi:
J = J* Swe(1/λ)
AAPG ACE Short Course 1: 06.06.2009 122 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Normalization: Leverett J Function• J function
works poorly for mixed 7
8
90.00025md0.00049md0.0012md0 0017mdfor mixed
lithofacies and between basins
• Does work OK for single lithofacies in a small area
3
4
5
6
7
Leve
rett
J Fu
nctio
n
0.0017md0.0018md0.0030md0.0040md0.0057md0.0085md0.012md0.013md0.032md0.046md0.085md0 25mdsmall area
0
1
2
0 10 20 30 40 50 60 70 80 90 100
Wetting Phase Saturation (%)
0.25md0.41md0.56md0.84md2.24md
Normalized Brooks-Corey• Brooks and Corey (1966) showed that a log-log
plot of Pc versus Swe often exhibits a linear trend with slope λ and intercept equal to the thresholdwith slope, λ, and intercept equal to the threshold entry pressure
• logSwe = -λlogPc + λlogPce for Pc>Pce– Pc=capillary pressure– Pce = threshold entry pressure– Swe = (Sw-Swi)/(1-Swi)– λ = slope of log-log plot
Capillary pressure parameters, λ and Pce, are correlated with permeability and/or porosity to develop Pc curves
AAPG ACE Short Course 1: 06.06.2009 123 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Normalization: Brooks-Corey Capillary Pressure
• Transform taking logarithm of Pc and Sw• λ represents pore throat size distribution• Standard unimodal curves can be reduced
to intercept (Pce = extrapolated threshold 2000
3000
4000
5000
6000
7000
8000
9000
10000
Hg
Cap
illar
y Pr
essu
re (p
sia)
entry) and slope (λ)0
1000
2000
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air
-
10000
ssur
e (p
sia)
Pc = 1.54E+07Sw-2.05
R2 = 0.997
1000
10000
y Pr
essu
re (p
sia)
Pceλ
100
1000
0 10 20 30 40 50 60 70 80 90 100
Wetting Phase Saturation (%)
Air
-Hg
Cap
illar
y Pr
es
100
1000
10 100
Wetting Phase Saturation (%)
Air
-Hg
Cap
illar
y
Change in Methane Density with Pressure and Temperature
0.300.32
ρ=0.03861-0.0003331T+5.943*10-5P-4.287*10-9P2+1.226*10-13P3
0 080.100.120.140.160.180.200.220.240.260.28
hane
Den
sity
(g/c
c) Pressure (psia)12000
11000
10000
9000
8000
7000
6000
5000
4000
3000
0.000.020.040.060.08
90 100 110 120 130 140 150 160 170 180 190 200 210 220 230
Temperature (deg F)
Met
h 3000
2000
1000
AAPG ACE Short Course 1: 06.06.2009 124 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Brine Density vs P-T-XBw = (1 +ΔVwp)x(1-ΔVwT); Bw =FVFw
γw = 1+ 6.95x10-6 XTDS; γw = specific gravity, X mg/l
ΔVwT = -1.0001x10-2 + 1.339x10-4T+5.5065x10-7T2
ΔVwp = -1.953x10-9pT-1.7283x10-13p2T-3.5892x10-7p-2.2534x10-10p2
ρw = γw/Bw
1.05
1.10
1.15
1.20
1.25
1.30
ensi
ty (g
/cc)
65 F, 15 psi
65 F 1000 psi
65 F, 5000 psi
65 F, 10000 psi
100 F, 15 psi
100 F, 1000 psi
100 F, 5000 psi
100 F, 10000 psi
200 F, 15 psi
200 F, 1000 psi
200 F, 5000 psi
0.90
0.95
1.00
0 50 100 150 200 250 300
Total Dissolved Solids (mg/l/1000)
De , p
200 F, 10000 psi
300 F, 15 psi
300 F, 1000 psi
300 F, 5000 psi
300 F, 10000 psi
Discrepancy in High P,T Methane-Water Interfacial Tension
• IFT data of Hough, Raza, and Wood (1951) hibi IFT 70
80
(1951) exhibits IFT <30 dyne/cm at higher P,T
• Data of Jennings & Newman (1971) exhibit higher values
• J&N data more30
40
50
60
70
Mod
eled
IFT
(dyn
e/cm
)
J&N data more consistent, HRW may have had unknown problem with system elastomer seal contamination
0
10
20
0 10 20 30 40 50 60 70 80HRW Measured IFT (dyne/cm)
J&N
M
AAPG ACE Short Course 1: 06.06.2009 125 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Relationship Between Pore Throat Diameter and Permeability by Lithology
0 445
100
y = 2.61x0.445
R² = 0.9259
0.1
1
10
ore
Thro
at D
iam
eter
(μm
)
Ss lithic
0.001
0.01
0.000001 0.00001 0.0001 0.001 0.01 0.1 1 10 100 1000 10000
Prin
cipa
l Po
Insitu Klinkenberg Permeability (md)
Ss lithicSs arkosicSs quartzoseLs interparticleLs chalkLs moldicLs oomoldic
Relationship Between Pore Throat Diameter and Permeability by Lithology
100
)
Dp = 7.17(k/φ)0.49
R2 = 0.83
0.1
1
10
l Por
e Th
roat
Dia
met
er (μ
m)
Lithology
0.001
0.01
0.000001 0.00001 0.0001 0.001 0.01 0.1 1 10 100 1000
Prin
cipa
Porosity Normalized Permeability (kik/φa, md/%)
LithologySs lithicSs arkosicSs quartzoseLs interparticleLs chalkLs moldicLs oomoldic
AAPG ACE Short Course 1: 06.06.2009 126 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Relationship Between Pore Throat Diameter and Permeability by Lithology
100
m)
Dp = 7.17(k/φ)0.49
R2 = 0.83
0.1
1
10
pal P
ore
Thro
at D
iam
eter
(μm
Lithology
Ss lithic
Ss arkosic
Ss quartzose
Ls interparticle
Ls chalk
Ls moldic
0.001
0.01
0.000001 0.00001 0.0001 0.001 0.01 0.1 1 10 100 1000
Prin
cip
Porosity Normalized Permeability (kik/φa, md/%)
Ls oomoldic
Mesaverde Hi
Mesaverde Lo
Power (Lithology)
Relationship Between Threshold Entry Pressure and Permeability
10000
ry kak
kmk
10
100
1000
rcur
y Th
resh
old
Entr
Pres
sure
(psi
)
kmkkik
y = 64.66x-0.44
R2 = 0.82
1
10
1E-06 0.00001 0.0001 0.001 0.01 0.1 1 10 100
Klinkenberg Permeability (mD)
Air-
Me
AAPG ACE Short Course 1: 06.06.2009 127 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Stress effect on Pc
1
10
100
1000
10000
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air
-Hg
Cap
illar
yPr
essu
re(p
sia)
R091255.9 ftk = 113 mD
= 24.5%φ
1000
10000
ure
(psi
a)
1
10
100
1000
10000
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air-
Hg
Cap
illar
yP
ress
ure
(psi
a)
R7802729.9 ftk = 7.96 mD
= 19.2%φ
1000
10000
ure
(psi
a)
113 mD 8 mD
• no significant difference in high-low pairs at high K
1
10
100
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air-
Hg
Cap
illar
yPr
essu
LD43C4013.25 ftk = 0.190 mD
= 12.9%φ
10
100
1000
10000
Air
-Hg
Cap
illar
yPr
essu
re(p
sia)
10
100
1000
10000
r-Hg
Cap
illar
yP
ress
ure
(psi
a)
1
10
100
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air
-Hg
Cap
illar
yPr
essu
E9466486.4 ftk = 0.637 mD
= 12.2%φ 0.6 mD 0.2 mD
• increasing Pce separation with decreasing K
• merging of curves at 35-50% Sw• smaller pores are in
1
10
100
1000
10000
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air
-Hg
Capi
llary
Pres
sure
(psi
a)
PA4244606.5 ftk = 0.00107 mD
= 12.7%φ
1
10
100
1000
10000
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air
-Hg
Capi
llary
Pres
sure
(psi
a)
B02913672.5 ftk = 0.000065 mD
= 2.6%φ
10 10 20 30 40 50 60 70 80 90 100
Wetting Phase Saturation (%)
A
B02911460.6 ftk = 0.0255 mD
= 4.4%φ
10 10 20 30 40 50 60 70 80 90 100
Wetting Phase Saturation (%)
Ai
E9466530.3 ftk = 0.0416 mD
= 9.5%φ 0.04 mD 0.02 mD
0.001 mD 0.00007 mD
protected pore space
• users of Winland R35 need to adjust for confining stress
• threshold entry pressure is predictable from √K/φ at any
y = 11.77x0.50
R2 = 0.77
y = 11.28x0.50
R2 = 0.930 1
1
10
100
old
Entr
yPo
reD
iam
eter
( μm
)
√K/φ at any confining pressure
• correct unconfined Pce to insitu Pce
0.01
0.1
1E-06 0.00001 0.0001 0.001 0.01 0.1 1 10 100
Klinkenberg Permeability/Porosity (mD/%)
Thre
sho
A
y = 6 75x-0.50
1000
10000
sC
olum
n) to insitu Pce
based on perm change with stress
y = 6.48x-0.50
R2 = 0.77
y = 6.75xR2 = 0.93
1
10
100
1E-06 1E-05 0.0001 0.001 0.01 0.1 1 10 100
Klinkenberg Permeability/Porosity (mD/%)
Thre
shol
dEn
try
Ga
Hei
ght(
ft)
C
AAPG ACE Short Course 1: 06.06.2009 128 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Stress effect on Pc
1
10
100
1000
10000
Air
-Hg
Cap
illar
yPr
essu
re(p
sia)
R091 1
10
100
1000
10000
Air-
Hg
Cap
illar
yP
ress
ure
(psi
a)
R780
y = 11.77x0.50
R2 = 0.77
y = 11.28x0.50
R2 = 0.93
0.01
0.1
1
10
100
1E-06 0.00001 0.0001 0.001 0.01 0.1 1 10 100
Thre
shol
dEn
try
Pore
Dia
met
er( μ
m)
A10 10 20 30 40 50 60 70 80 90 100
Wetting Phase Saturation (%)
R091255.9 ftk = 113 mD
= 24.5%φ
1
10
100
1000
10000
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air-
Hg
Cap
illar
yPr
essu
re(p
sia)
LD43C4013.25 ftk = 0.190 mD
= 12.9%φ
10 10 20 30 40 50 60 70 80 90 100
Wetting Phase Saturation (%)
R7802729.9 ftk = 7.96 mD
= 19.2%φ
100
1000
10000
llary
Pres
sure
(psi
a)
100
1000
10000
lary
Pre
ssur
e(p
sia)
1
10
100
1000
10000
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air
-Hg
Cap
illar
yPr
essu
re(p
sia)
E9466486.4 ftk = 0.637 mD
= 12.2%φ
113 mD 8 mD
0.6 mD 0.2 mD
Klinkenberg Permeability/Porosity (mD/%)A
y = 6.48x-0.50
R2 = 0.77
y = 6.75x-0.50
R2 = 0.93
1
10
100
1000
10000
1E 06 1E 05 0 0001 0 001 0 01 0 1 1 10 100
Thre
shol
dEn
try
Gas
Col
umn
Hei
ght(
ft)
•• threshold entry pressure threshold entry pressure is entirely predictable is entirely predictable from √K/from √K/φφ ratio at any Pratio at any P
1
10
100
1000
10000
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air
-Hg
Capi
llary
Pres
sure
(psi
a)
PA4244606.5 ftk = 0.00107 mD
= 12.7%φ
1
10
100
1000
10000
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air
-Hg
Capi
llary
Pres
sure
(psi
a)
B02913672.5 ftk = 0.000065 mD
= 2.6%φ
1
10
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air
-Hg
Cap
i
B02911460.6 ftk = 0.0255 mD
= 4.4%φ
1
10
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air-
Hg
Cap
il
E9466530.3 ftk = 0.0416 mD
= 9.5%φ 0.04 mD 0.02 mD
0.001 mD 0.00007 mD
1E-06 1E-05 0.0001 0.001 0.01 0.1 1 10 100
Klinkenberg Permeability/Porosity (mD/%)C
Brooks-Corey Slope• PSD expressed by Pcslope• Pcslope = f (k)• Pcslope ↓ with P ↑
Leverett J(Sw) = Pc (k/φ)0.5/τcosθ
Implicitly assumesPcslope = Constant
Poor fit becausePcslope ≠ C = f(k, lith)
y = -0.037Ln(x) + 1.256R2 = 0.052
y = -0.0304Ln(x) + 1.87R2 = 0.0216
2
3
4
5
Cor
ey C
apill
ary
sure
Slo
pe
in situunconfined
0
1
2
1E-05 0.0001 0.001 0.01 0.1 1 10 100 1000In situ Klinkenberg Permeability (mD)
Bro
oks-
CPr
es
AAPG ACE Short Course 1: 06.06.2009 129 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Modeled Pc Curves
Modeled Pc curves
400500600700800900
1000
abov
e fre
e w
ater
(ft) k=0.0001 mD
k=0.001 mDk=0.01 mD
k=0.1 mD
k=1 mD
k=10 mD
0100200300
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0Water Saturation (fraction)
Hei
ght a
Modeled Pc curves
100
1000
ree
wat
er (f
t)
Pc properties evolve
1
10
0.0 0.1 1.0Water Saturation (fraction)
Hei
ght a
bove
fr k=0.0001 mDk=0.001 mD
k=0.01 mD
k=0.1 mDk=1 mD
k=10 mD
Pc properties evolve over time as diagenesis changes porosity and pore architecture
Hysteresis of Capillary Pressure
Drainage-ImbibitionCycles
3
4
5
• Non-wetting residual saturation to imbibition S f(S i)
12
5
Snwr = f(Snwi)
(after Larson & Morrow, 1981)
Midale Dolφ = 23%
AAPG ACE Short Course 1: 06.06.2009 130 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Capillary Pressure Hysteresis in Coarse Sand Pack
(after Klute, 1967)
Drainge-Imbibition
10000r
• what is the residual trapped gas when a reservoir leaks or along a gas migration path?
10
100
1000
0000
ght a
bove
Fre
e W
ater
Leve
l (ft)
Primary DrainageFirst ImbibitionSecondary DrainageSecond ImbibitionTertiary DrainageThird Imbibition
0.1
1
0 10 20 30 40 50 60 70 80 90 100
Wetting Phase Saturation (%)
App
rox.
Hei
AAPG ACE Short Course 1: 06.06.2009 131 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Capillary Pressure
Hysteresis1
10
100
1000
10000
0 10 20 30 40 50 60 70 80 90 100
Wetting Phase Saturation (%)
Air-
Hg
Cap
illar
yP
ress
ure
(psi
a)
Primary DrainageFirst ImbibitionSecondary DrainageSecond ImbibitionTertiary DrainageThird Imbibition
E393 7001.1ft = 17.4% = 28.9 mD
φ
kik
1
10
100
1000
10000
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air-
Hg
Cap
illar
yP
ress
ure
(psi
a)
Primary DrainagePrimary ImbibitionSecond DrainageSecond ImbibitionThird DrainageThird Imbibition
B049 9072.1 ft (A) = 12.3% = 6.74 mD
φ
kik
1000
10000
sure
(psi
a)
Primary DrainagePrimary ImbibitionSecond DrainageSecond ImbibitionThird DrainageThird Imbibition
kik
1000
10000
sure
(psi
a)
Primary DrainagePrimary ImbibitionSecond DrainageSecond ImbibitionThird DrainageThird Imbibition
kikkikkikkikkik
•• Composite primary Composite primary drainage trend drainage trend consistent with consistent with singlesingle--cycle drainagecycle drainage
•• ImibitionImibition curves curves hibi hi h ihibi hi h i
1
10
100
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air-
HgC
apill
ary
Pres
s
E393 7027.2 ft = 15.0% = 1.93 mD
φ
1
10
100
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air
-Hg
Cap
illar
yP
ress
R829 5618.3 ft (B) = 9.2% = 0.287 mD
φ
10
100
1000
10000
r-H
gC
apill
ary
Pre
ssur
e(p
sia)
Primary DrainagePrimary ImbibitionSecond DrainageSecond ImbibitionThird DrainageThird Imbibition
10
100
1000
10000r-
Hg
Cap
illar
yP
ress
ure
(psi
a)
Primary DrainagePrimary ImbibitionSecond DrainageSecond ImbibitionThird DrainageThird Imbibition
exhibit high trappingexhibit high trapping•• Trapped saturation Trapped saturation
increases with increases with increasing initial increasing initial saturationsaturation
10 10 20 30 40 50 60 70 80 90 100
Wetting Phase Saturation (%)
Air
B646 8294.4 ft (B) = 7.6% = 0.022 mD
φ
10 10 20 30 40 50 60 70 80 90 100
Wetting Phase Saturation (%)
Air
S685 6991.2 ft (B) = 8.6% = 0.0063 mD
φ
1
10
100
1000
10000
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air-
HgC
apill
ary
Pres
sure
(psi
a)
Primary DrainagePrimary ImbibitionSecond DrainageSecond ImbibitionThird DrainageThird Imbibition
E458 6404.8 ft (A) = 9.5% = 0.0019 mD
φ
1
10
100
1000
10000
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air
-Hg
Cap
illar
yPr
essu
re(p
sia)
Primary DrainagePrimary ImbibitionSecond DrainageSecond ImbibitionThird DrainageThird Imbibition
KM360 8185.7 ft (B) = 5.9% = 0.00070 mD
φ
Trapping increases with increasing initial saturation
(after Lake 2005)
AAPG ACE Short Course 1: 06.06.2009 132 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Residual Non-wetting Phase Saturation
0.9
1.0
Snw
r)
0.3
0.4
0.5
0.6
0.7
0.8
Non
wet
ting
Phas
e Sa
tura
tion
(S
0.0
0.1
0.2
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Initial Nonwetting Phase Saturation (Snwi)
Res
idua
l N
Residual Gas SaturationC = 1/[(Snwr-Swi)-1/(Snwi-Swi)]Snwr = 1/[C + 1/Snwi]C = 0.55 (min ε); Swi = 0
C = 1/[(Snwr-Swi)-1/(Snwi-Swi)]Snwr = 1/[C + 1/Snwi]C = 0.55 (min ε); Swi = 0
Sample Swirr Land C C Land C Snwr SnwrCondition definition Average Standard Minimum Standard Std Error
Error Error Error C=0.55all Swirr = 1-Snwmax 0.57 0.329 0.53 0.077 0.077unconfined Swirr = 1-Snwmax 0.61 0.294 0.59 0.087 0.088hysteresis Swirr = 1-Snwmax 0.61 0.383 0.51 0.056 0.057confined Swirr = 1-Snwmax 0.44 0.249 0.45 0.088 0.085all Swirr = 0 0.73 0.443 0.63 0.073 0.073unconfined Swirr = 0 0.78 0.360 0.71 0.080 0.081hysteresis Swirr = 0 0.75 0.562 0.59 0.057 0.057confined Swirr = 0 0.61 0.316 0.54 0.078 0.078all Swirr = 0, Snwi<70% 0.70 0.054 0.053
0.5
0.6
0.7
0.8
0.9
1.0
g Ph
ase
Satu
ratio
n (S
nwr) unconfined Snwi= 1-Snwmax
unconfined hysteresisLand C =0.59, Swirr=0Land C=0.71, Swirr=0Land C =0.55, Swirr=0
unconfined Swirr = 0, Snwi<70% 0.83 0.062 0.061hysteresis Swirr = 0, Snwi<70% 0.70 0.052 0.051confined Swirr = 0, Snwi<70% 0.50 0.038 0.039
0.0
0.1
0.2
0.3
0.4
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Initial Nonwetting Phase Saturation (Snwi)
Res
idua
l Non
wet
ting
AAPG ACE Short Course 1: 06.06.2009 133 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Residual Saturation
C = 1/[(Snwr-Swi)-1/(Snwi-Swi)]Snwr = 1/[C + 1/Snwi]C = 0.55 (min ε); Swi = 0
C = 1/[(Snwr-Swi)-1/(Snwi-Swi)]Snwr = 1/[C + 1/Snwi]C = 0.55 (min ε); Swi = 0
0.9
1.0
wr) unconfined
confined
0.4
0.5
0.6
0.7
0.8
nwet
ting
Phas
e Sa
tura
tion
(Sn confined
Land C=0.66, Swi=0Land C =0.54, Swi=0
0.0
0.1
0.2
0.3
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Initial Nonwetting Phase Saturation (Snwi)
Res
idua
l Non
Residual Gas Saturation
1
10
100
1000
10000
0 10 20 30 40 50 60 70 80 90 100
Wetting Phase Saturation (%)
Air-
Hg
Cap
illar
yP
ress
ure
(psi
a)
Primary DrainageFirst ImbibitionSecondary DrainageSecond ImbibitionTertiary DrainageThird Imbibition
E393 7001.1ft = 17.4% = 28.9 mD
φ
kik
1
10
100
1000
10000
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air-
Hg
Cap
illar
yP
ress
ure
(psi
a)
Primary DrainagePrimary ImbibitionSecond DrainageSecond ImbibitionThird DrainageThird Imbibition
B049 9072.1 ft (A) = 12.3% = 6.74 mD
φ
kik
1000
10000
re(p
sia)
Primary DrainagePrimary ImbibitionSecond DrainageSecond ImbibitionThird DrainageThird Imbibition
kik
1000
10000
re(p
sia)
Primary DrainagePrimary ImbibitionSecond DrainageSecond ImbibitionThird DrainageThird Imbibition
kikkikkikkikkik
• Snwi and Snwr are ~ = for Sw > 80%• e g for Swi of 30% Swr is ~50%
• Snwi and Snwr are ~ = for Sw > 80%• e g for Swi of 30% Swr is ~50%
0.6
0.7
0.8
0.9
1.0
ase
Satu
ratio
n (S
nwr) unconfined
confinedLand C=0.66, Swi=0Land C =0.54, Swi=0
1
10
100
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air-
HgC
apill
ary
Pres
sur Third Imbibition
E393 7027.2 ft = 15.0% = 1.93 mD
φ
1
10
100
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air
-Hg
Cap
illar
yP
ress
ur Third Imbibition
R829 5618.3 ft (B) = 9.2% = 0.287 mD
φ
10
100
1000
10000
gC
apill
ary
Pre
ssur
e(p
sia)
Primary DrainagePrimary ImbibitionSecond DrainageSecond ImbibitionThird DrainageThird Imbibition
10
100
1000
10000
gC
apill
ary
Pre
ssur
e(p
sia)
Primary DrainagePrimary ImbibitionSecond DrainageSecond ImbibitionThird DrainageThird Imbibition
• e.g., for Swi of 30%, Swr is ~50%• e.g., for Swi of 30%, Swr is ~50%
0.0
0.1
0.2
0.3
0.4
0.5
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0Initial Nonwetting Phase Saturation (Snwi)
Res
idua
l Non
wet
ting
Ph
10 10 20 30 40 50 60 70 80 90 100
Wetting Phase Saturation (%)
Air-
Hg
B646 8294.4 ft (B) = 7.6% = 0.022 mD
φ
10 10 20 30 40 50 60 70 80 90 100
Wetting Phase Saturation (%)
Air-
Hg
S685 6991.2 ft (B) = 8.6% = 0.0063 mD
φ
1
10
100
1000
10000
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air-
HgC
apill
ary
Pres
sure
(psi
a)
Primary DrainagePrimary ImbibitionSecond DrainageSecond ImbibitionThird DrainageThird Imbibition
E458 6404.8 ft (A) = 9.5% = 0.0019 mD
φ
1
10
100
1000
10000
0 10 20 30 40 50 60 70 80 90 100Wetting Phase Saturation (%)
Air
-Hg
Cap
illar
yPr
essu
re(p
sia)
Primary DrainagePrimary ImbibitionSecond DrainageSecond ImbibitionThird DrainageThird Imbibition
KM360 8185.7 ft (B) = 5.9% = 0.00070 mD
φ
AAPG ACE Short Course 1: 06.06.2009 134 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Residual gas
saturation0 7
0.8
0.9
1.0
tion
(Snw
r)
Complete trapping, C=0Vuggy, isolated moldic, C=0.3Mesaverde high C =0.35Mesaverde Ss, C=0.55Mesaverde low, C=0.9Cemented Ss, C=0.7Berea, C=1.7Unconsolidated sucrosic oolitic C=3
• Trapping constant, C consistent with cemented
0.3
0.4
0.5
0.6
0.7
ual N
onw
ettin
g Ph
ase
Satu
rat Unconsolidated, sucrosic, oolitic, C 3
cemented sandstone
0.0
0.1
0.2
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1Initial Nonwetting Phase Saturation (Snwi)
Res
idu
Electrical PropertiesElectrical PropertiesPropertiesProperties
AAPG ACE Short Course 1: 06.06.2009 135 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Wireline log analysis tools
• Lithofacies identification
Permeability - 1Core
0.001 1000unknTimur : Constant Exponent
0.001 1000MDTimur : Variable Exponent
0.001 1000md
1:240 MD
in F
Reservoir ComponentsPorosity
0.4 0V/VPHIX
0.4 0.0V/VOil
0.4 0V/VWater
0.4 0V/VShale
0 2V/V
CPHI
0 0unknWater
Oil
Gas
0 1
Permeability - 2Core
0.001 1000unknTimur : Sw-Sw(Density)
0.001 1000unknTimur : Sw/Sw(Density)
0.001 1000unkn
6400
• Accurate porosity calculation
• Water saturation calculations
06425
64506475
65006525
65506550
MWX2
Resistivity of a simple rock model with straight pores
0 1Porosity0 1Porosity (Φ) RwResistivity
(Ro)The ‘formation factor’ (F) is defined as the ratio Ro/Rw
F = 1/φ
8
AAPG ACE Short Course 1: 06.06.2009 136 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
For a rock with a tortuous pore network ....
F = 1/φmF = 1/φThis is the first Archie equation, where ‘m’ is known as the ‘cementation exponent’
The resistivity of hydrocarbon-bearing rocks
01 Water saturation (Sw)Ro Resistivity (Rt)
The ‘resistivity index’ (I) is defined as the ratio Rt/Ro
I = 1/Sw
Water saturation (Sw)
n
8
AAPG ACE Short Course 1: 06.06.2009 137 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Putting it all together ...the Archie equation
ΦF m=a
=oR
R 1ΦF mRwRR Swo
tI == n
1
φSw= a
m*wRt
1/n( R )
Core measurement of the formation factor, F
core plug
A
L
ro Rw
Φ
p g
AAPG ACE Short Course 1: 06.06.2009 138 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
When F and φ are plotted on logarithmic graph paper ...
1
Φ m= 3
0.1
F
m= 2
m= 1
1 10 100 10000.01
Regional Water Chemistry Database
DOE Contract DE-FC-02NT41437Billingsley et al
Advanced Resources International
Hi t i l D t• Historical Data• 3200 Well Locations
–Greater Green River Basin and Wind River Basin• 8000 Chemical Analyses• Access/Excel Formats
AAPG ACE Short Course 1: 06.06.2009 139 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
m in sandstones Archie (1942) observed the range in value of m in sandstones:1.3 unconsolidated sandstones1.4 - 1.5 very slightly cemented 1.6 - 1.7 slightly cemented1.8 - 1.9 moderately cemented2.0 - 2.2 highly cementedg y
Guyod gave the name “cementation exponent” to m, but noted that the pore geometry controls on m were more complex and went beyond simple cementation
m variability
Core measurements of formation factor andformation factor and porosity in a Cherokee sandstone sample, with a computed value of cementation exponent mfor each core sample from:from:
F = 1/φm
AAPG ACE Short Course 1: 06.06.2009 140 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
30
35
40on
(%)
Archie Cementation Exponents
Mesaverde Frontier
10
15
20
25
erce
nt o
f Pop
ulat
io
Medina
Mesaverde-Frontier
0
5
1.3-
1.4
1.4-
1.5
1.5-
1.6
1.6-
1.7
1.7-
1.8
1.8-
1.9
1.9-
2.0
2.0-
2.1
2.1-
2.2
Archie Cementation Exponent (m, a=1)
P
Water Saturation Calculations
• Archie• Simandoux• Fertl• Dual-Water• Waxman-Smits
AAPG ACE Short Course 1: 06.06.2009 141 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Simandoux• Developed theoretically primarily for
Gulf Coast application
Whereφ = effective porosity
• Rw = water resistivity• Rt = formation true resistivity• Rsh = shale or clay resistivity• Vsh = volume of shale
Fertl• Developed for shaly sandstones in Rocky Mountains
Whereφ = effective porosity
• Rw = water resistivity• Rt = formation true resistivity• Vsh = volume of shale• A = Constant
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Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Dual-Water/Waxman-Smits• (Clavier, Coats, and Dumanoir, 1984)
Swt - SwbS =
Whereφt = total porosity
1 - SwbSw =
• Rwf = formation water resistivity• Rt = formation true resistivity• Rwb = bound water resistivity (Rwa in shales)• Swt = total water saturation• Swb = bound water saturation (various methods for determination
– e.g., Swb = α vq Qv; vq = 0.28 cc/meq25oC, α(XNaCl) ≈ 1
Clay Surface Area & Cation Exchange Capacity
Clay Type Cation Exchange MorphologyPure Clay Clay in Sandstone Capacity (Meq/100g)
Specific Surface
Kaolinite 15-18 0.05-0.20 3-15 BooksFans
Smectite 85-100 0.5-2.0 80-150 Honeycomb
Illite 90-115 1.5-10 10-40 Curled flakes with projecting and fibrous mat
Smectite-Illite
85-115 0.5-10 10-150 Similar to Smectite Illite
(mixed-layer)
& Illite
Chlorite 40-60 0.5-2.0 10-40 Cardhouse, rosette(after Grim, 1968; Gaida et al, 1973)
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Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Waxman and Smits (1969) Calculated Water SaturationWaxman and Smits (1969)
Calculated Water Saturation• Redefined the Archie equation including the• Redefined the Archie equation including the• Redefined the Archie equation including the
influence of conductive claysCo = (1/F*) (Cw + BQv)
• Co = core conductivity at Sw=100% (mho/m)Cw = water conductivity (mho/m)F* = salinity/clay conductivity independent formation factor
• Redefined the Archie equation including the influence of conductive clays
Co = (1/F*) (Cw + BQv)• Co = core conductivity at Sw=100% (mho/m)
Cw = water conductivity (mho/m)F* = salinity/clay conductivity independent formation factorQv = cation exchange capacity of the core (meq/cc)B = specific counter-ion activity [(equiv/l)/(ohm-m)]
• F*/F = (1 + BQv/Cw)
Qv = cation exchange capacity of the core (meq/cc)B = specific counter-ion activity [(equiv/l)/(ohm-m)]
• F*/F = (1 + BQv/Cw)
Waxman-SmitsWater Saturation Calculations
Waxman-SmitsWater Saturation Calculations
• Sw = [(F*Rw) Rt(1+ RwBQv/Sw)]1/n*
• F* = salinity/clay conductivity independent formation factorQv = cation exchange capacity of the core (meq/cc)B = specific counter-ion activity [(equiv/l)/(ohm-m)]
• Qv ≈ CEC(1-φ)ρma/100φ
• Sw = [(F*Rw) Rt(1+ RwBQv/Sw)]1/n*
• F* = salinity/clay conductivity independent formation factorQv = cation exchange capacity of the core (meq/cc)B = specific counter-ion activity [(equiv/l)/(ohm-m)]
• Qv ≈ CEC(1-φ)ρma/100φQv ( φ)ρma φQv ( φ)ρma φ
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Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Waxman-Smits-Thomas
*
w *m*a
=w
RS
⎞⎛
φ*n
w
vw t
w
SBQR1R
⎟⎟⎟
⎠
⎞
⎜⎜⎜
⎝
⎛+
F* = a*/φm* Intrinsic Formation Factor; free of excess conductivity
m* Intrinsic cementation exponent; free of excess conductivityp ; y
n* Intrinsic saturation exponent; free of excess conductivity
Rw Resistivity of brine at temperature (ohm-m)
B Equivalent counterion conductance at temperature (1/ohm-m)/(equiv / liter)
Qv Cation exchange capacity per ml pore space (meq/ml)
Qv Lab Methods• Wet Chemistry
– Utilizes crushed rock with high surface area– Requires sample porosity & grain density toRequires sample porosity & grain density to
compute Qv– Crushing can improperly exposes Qv sites not
present in native pores• Multiple Salinity (Co vs Cw)
Fl th h f lti l li it b i– Flow-through of multiple salinity brines on core– Preserves distribution of clays and Qv – time – intensive
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Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Multiple-salinity Analysis
*FQ B
*FCC vw
O +=
,1/R
oor
eC
ondu
ctiv
ity(C
O)
Clay-rich sandstone
*FQ B vmax
Slope @ Bmax brines = 1/F*
Excess conductivityC
Clean sandstone
Brine Conductivity (CW), 1/Rw0
BmaxQv
FCC
F1C W
WO =⋅=
Porosity dependence of “m”Empirical: m = 0.234 ln Empirical: m = 0.234 ln φφ + 1.33+ 1.33Dual porosity: m = log[(Dual porosity: m = log[(φφ--φφ22))m1m1 + + φφ22
m2m2]/log ]/log φφφφ22 = 0.35% m= 0.35% m11=2, m=2, m22=1; SE both = 0.11=1; SE both = 0.11rock behaves like a mixture of matrix porosity and rock behaves like a mixture of matrix porosity and p yp ycracks or fracturescracks or fractures
both models fit databoth models fit data
φφ = bulk porosity= bulk porosityφφ22 = fracture porosity= fracture porosity
1 5
1.6
1.7
1.8
1.9
2.0
2.1
2.2
Cem
enta
iton
Expo
nent
rin
e=40
Kpp
mN
aCl)
mm11 = matrix = matrix cementation cementation exponentexponent
mm22 = fracture = fracture cementation cementation exponentexponent
1.0
1.1
1.2
1.3
1.4
1.5
0 2 4 6 8 10 12 14 16 18 20 22
In situ Porosity (%)
In s
itu A
rchi
e C
(m, a
=1, X
br
AAPG ACE Short Course 1: 06.06.2009 146 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Archie Cementation Exponent
2.4)
• Empirical: m = 0.95 - 9.2φ + 6.35φ0.5
• Dual porosity: m = log[(φ-φ2)m1 + φ2m2]/logφ
1 5
1.61.7
1.81.92.0
2.1
2.22.3
ntat
ion
Expo
nent
(m,A
=1
• φ = bulk porosity• φ2 = fracture or
touching vug porosity High: m1 = 2 1 φ2 = 0 0005High: m1 = 2 1 φ2 = 0 0005
1.0
1.11.21.3
1.41.5
0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2 0.22 0.24Porosity (fraction)
Arc
hie
Cem
eporosity• m1 = matrix
cementation exponent
• m2 = fracture or touching vug cementation exponent
High: m1 2.1, φ2 0.0005Int: m1 = 2.0, φ2 = 0.001Low: m1 = 1.8, φ2 = 0.002
m2 = 1
High: m1 2.1, φ2 0.0005Int: m1 = 2.0, φ2 = 0.001Low: m1 = 1.8, φ2 = 0.002
m2 = 1
Archie porosity (cementation) exponentNearly all cores exhibit some salinity dependenceNearly all cores exhibit some salinity dependencetested plugs with 20K, 40K, 80K, and 200K tested plugs with 20K, 40K, 80K, and 200K ppmppm brinesbrines
1.0
0.4
0.5
0.6
0.7
0.8
0.9
Con
duct
ivity
(mho
/m) n=335
0.0
0.1
0.2
0.3
0 2 4 6 8 10 12 14 16 18 20 22
Brine Conductivity (mho/m)
Cor
e C
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Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Archie Cementation Exponent vs. Rw
Nearly all cores Nearly all cores exhibit some salinity exhibit some salinity dependencedependencetested plugs with tested plugs with 2.0
2.1
2.2
2.3xp
onen
t,
p gp g20K, 40K, 80K, and 20K, 40K, 80K, and 200K 200K ppmppm brinesbrines
1.4
1.5
1.6
1.7
1.8
1.9
rchi
e C
emen
tatio
n Ex
(m, A
=1)
1.0
1.1
1.2
1.3
0.01 0.1 1
Brine Resistivity (ohm-m)
In s
itu A
r
Multi-salinity Archie m
2.0
2.2
2.4
onen
t (m
,
1.2
1.4
1.6
1.8
e C
emen
taito
n Ex
poa=
1)
200K
80K
40K
• Archie m decreases with decreasing salinity
0.8
1.0
0 2 4 6 8 10 12 14 16 18 20 22
Arc
hie
In situ Porosity (%)
40K
20K
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Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Slopem-logRwvs Porosity
0.0
0.1
0.2
w S
lope
Each core exhibits a highly linear m vs logRw
Mean value for all cores:
y = 0.0118x - 0.3551R2 = 0.1198
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0 2 4 6 8 10 12 14 16 18 20 22
In s
itu A
rchi
e m
vs
log
Rw Mean value for all cores:
Average Slopem-Rw = -0.27+0.32 (2 standard deviations)
where Slopem-Rw = slope of mRw versus logRw.
Slopes exhibit a weak correlation with porosity . This correlation
0 2 4 6 8 10 12 14 16 18 20 22In situ Porosity (%) can be used to improve the
prediction of m at any salinity:Slopem-Rw = 0.00118 φ – 0.355 (φ - %).
Estimation of Archie m• Each core exhibits a highly linear m vs logRw• Mean value for all cores:
– Average Slopem-Rw = -0.27+0.32 (2 standard deviations)h Sl l f l R– where Slopem-Rw = slope of mRw versus logRw.
• Slopes exhibit a weak correlation with porosity . This correlation can be used to improve the prediction of m at any salinity:– Slopem-Rw = 0.00118 φ – 0.355 (φ - %).
• Combining the above equations the Archie cementation exponent at any given porosity and reservoir brine salinity can be predicted using:using:– mX = m40 + Slopem-Rw (log RwX + logRw40K)– mX = (0.676 logφ + 1.22) + (0.0118 φ-0.355) x (logRwX + 0.758); φ<14%– mX = 1.95 + (0.0118 φ-0.355) x (logRwX + 0.758); φ>14%
• where mx = m at salinity X• m40 = m at 40K ppm NaCl, log RwX = log10 of resistivity of brine at salinity X• logRw40K = log10 of resistivity of 40K ppm NaCl = 0.758
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Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Salinity dependence of “m”•• m = a ln m = a ln φ φ + b+ b•• a, b = a, b = ff (salinity)(salinity)
20K ppm
y = 0.2267Ln(x) + 2.2979
R2 = 0.6619
2 00
2.50
•• low porosity rocks hold low porosity rocks hold more gas than we more gas than we thoughtthought0.00
0.50
1.00
1.50
2.00
0.000 0.050 0.100 0.150 0.200 0.250
insitu porosity (%)
Axis Title
Series1
Log. (Series1)
40K ppm
y = 0.2328Ln(x) + 2.409
R2 = 0.6547
0.50
1.00
1.50
2.00
2.50
3.00
Axis Title
Series1
Log. (Series1) 80K ppm
y = 0.2149Ln(x) + 2.4354
R2 = 0.51322.50
3.00
0.00
0.000 0.050 0.100 0.150 0.200 0.250
insitu porosity (%)
0.00
0.50
1.00
1.50
2.00
0.000 0.050 0.100 0.150 0.200 0.250
insitu porosity (%)
Axis Title
Series1
Log. (Series1)
200K ppm
y = 0.1621Ln(x) + 2.3222
R2 = 0.3633
0.00
0.50
1.00
1.50
2.00
2.50
3.00
0.000 0.050 0.100 0.150 0.200 0.250
insitu porosity (%)
Axis Title
Series1
Log. (Series1)
Critical GasCritical GasCritical Gas Saturation
Critical Gas Saturation
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Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Overview• Previous work indicated
that krg could be modeled using: Corey eqn with p=1.7 & Sgc ~
Western Sandstones
0.1
1
as R
elat
ive
Perm
eabi
lity
q p gc0.15-0.05*log10kik
• Swc ~ Swi600
• Issues– little krg data at Sw >
65% : Does p vary or
0.010 10 20 30 40 50 60 70 80 90 100
Water Saturation
Ga
0.1
1
bilit
y (f
ract
ion)
g-10 mdw -10 mdg-1 mdw -1 mdg-0.1 mdw -0.1 mdg-0.01 mdw -0.01 mdp y
Sgc vary or both?– little Swc data: how is
Swc = f (kik)? Or what is krw exponent ?
SgcSwc>Swi
0.0001
0.001
0.01
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Water Saturation (fraction)
Rel
ativ
e Pe
rmea g-0.001 md
w -0.001 md
Relative Permeability and Capillary Pressure
• Krg - relative permeability to gas• Krw - relative permeability to water• Sgc - critical gas saturation (Sg
f ti th) ativ
e Pe
rmea
bilit
y 1
krg krw
necessary for connective gas path)• Swc - critical water saturation (Sw
below which water relative permeability is zero or less than measurable threshold
• Swi - “irreducible” water saturation (Sw at which further increase in Pc, hydrocarbon column height, results in S d l th it i ry
Pre
ssur
eR
ela
t abo
ve F
ree
ter L
evel
0 10
SgcSwcSwi
Pcdrainage
curve
Transition
gas-
only
prod
uctio
nat
ertio
n
Sw decrease less than some criteria
• At Sg<Sgc no gas flow only water flow• At Swc<Sw<(1-Sgc) transition zone -
both gas & water flow• At Sw<Swc no measurable water flow
only gas flow
Water Saturation
Cap
illar
Hei
ght
Wa
0 10
zone
Free water levelwat
er-o
nly
prod
uctio
nga
s&w
apr
oduc
AAPG ACE Short Course 1: 06.06.2009 151 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Relative Permeability Scaling
0.70.80.91.0
eabi
lity
0.01
0.1
1
mea
bilit
yLogarithmic Linear
A t ti h th iti l t ti f h h th
0.00.10.20.30.40.50.6
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0Water Saturation
Rel
ativ
e Pe
rm
0.000001
0.00001
0.0001
0.001
0 0
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Water Saturation
Rel
ativ
e Pe
rm
• As saturations approach the critical saturation for each phase the relative permeability for that phase changes by orders of magnitude
• At saturations above critical saturations the relative permeability to the remaining flowing phase changes less than an order of magnitude
Relative Permeability Reference Frame• krg = kreg/kr?• Relative permeability is the ratio of the effective
permeability of one phase to a baseline bili di i l fpermeability - traditional references are:
– kr = ke/kabsolute; where kabs may be kair,kwater, koil kklink– kr = ke/kenw,Swc or kr = ke/kenw,Swi
• kabs is the absolute permeability– In high k rocks kwater ~ kklink ~ kabs (~ kair)– In high k rocks ken S c ~ kabs and S c~S iIn high k rocks kenw,Swc kabs and Swc Swi– In low k rocks kwater<kklink– In low k rocks keg,Swi < kklink
• User must choose reference frame - (carefully)
AAPG ACE Short Course 1: 06.06.2009 152 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Relative Permeability Reference Frame• Selection of
– kreference = kwater – kref = keg,Swc – results in krg > 1 at Sw < Swc
• For most reservoir simulation programs 0.001
0.01
0.1
1
10
ve P
erm
eabi
lity
kr cannot exceed 1• In reservoir Swi can be < Swc but it
achieved the low Sw by water flow at krw << krw,Swc
0.01
0.1
1
mea
bilit
y
0.000001
0.00001
0.0001
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Water Saturation
Rel
ativ
0.1
1
10
eabi
lity
kref = kwater
0.000001
0.00001
0.0001
0.001
0 0
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Water Saturation
Rel
ativ
e Pe
rm
0.000001
0.00001
0.0001
0.001
0.01
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Water Saturation
Rel
ativ
e Pe
rme
kref = kklink kref = keg,Swc
Generalized Drainage & Imbibition Relative Permeability Curves
Generalize Drainage Curves Generalized Imbibition CurvesGeneralize Drainage Curves Generalized Imbibition Curves
(after Sahimi, 1994)
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Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Gas Relative Permeability of Low-Permeability Tight Gas Sandstone• Referenced to kklink
• Measurements performed at Sw<Swi by evaporation
• Note shift to lower krg at a given Swwith decreasing ki
(after Thomas & Ward, 1972)
Effect of Confining Pressure on Relative Permeability for Tight Gas Sandstone
• Note data points showing little effect of significant change in g gconfining pressure on krg
• Ward & Morrow (1987) data indicate that krg under pressure may be 10% less than at low pressure
• Referenced to kklink,P• Measurements• Measurements
performed at Sw <Swiby evaporation
• Note shift to lower krgat a given Sw with decreasing ki
(after Thomas & Ward, 1972)
AAPG ACE Short Course 1: 06.06.2009 154 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Gas Relative Permeability is Similar using
different techniques to obtain water
saturation
(after Walls, 1982)
Influence of Confining Pressure on Gas Permeability with Core at Different Water Saturations
(after Walls, 1982)
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Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Effect of Confining Pressure on Relative Permeability for Tight Gas Sandstone
Data of Randolph (1983) show moderate effect of confining stress on kr at low water saturation but increasing effect with increasing Sw
(after Randolph, 1983)
Single-phase Stationary krg Curves
• Relative gas permeability data, representing k values obtained at several saturationskrg values obtained at several saturations, were compiled from published studies (Thomas and Ward, 1972; Byrnes et al , 1979; Sampath and Keighin, 1981; Walls, 1981; Randolph, 1983; Ward and Morrow, 1987)
AAPG ACE Short Course 1: 06.06.2009 156 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Gas Relative PermeabilityWestern Sandstones1
bilit
y Bounding curves consistent with
0.1
Rel
ativ
e Pe
rmea
b single-point data
0.010 10 20 30 40 50 60 70 80 90 100
Water Saturation
Gas
n=43
Single-point krg,Swi Data• Relative gas permeability data representing k• Relative gas permeability data, representing krg
values obtained at a single Sw and krg values obtained for a single sample at several saturations, were compiled from published studies (Thomas and Ward, 1972; Byrnes et al , 1979; Jones and Owens, 1981; Sampath and Keighin, 1981; Walls, p g1981; Randolph, 1983; Ward and Morrow, 1987; Byrnes, 1997; Castle and Byrnes, 1997; Byrnes and Castle, 2001)
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Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Single-Sw Gas Relative PermeabilityAll Tight Gas Sandstones
0 80.91.0
bilit
y 1-10 md0.1-1 md0.05-0.1 md0 01 0 05 d
0.30.40.5
0.60.70.8
Rel
ativ
e Pe
rmea
b 0.01-0.05 md0.005-0.01 md0.001-0.005 md0.0001-0.001 md1 md0.1 md0.01 md0.001 md0.0001 md
0.00.10.2
0 10 20 30 40 50 60 70 80 90 100Water Saturation (%)
Gas
R
Relative Permeability to Gas Relative Permeability to Gas –– at Stressat StressMultiple reservoir intervals Multiple reservoir intervals –– GGRB (n = 583)GGRB (n = 583)
1.01.0
Krg/4000
Byrnesdata
Rel
ativ
e Pe
rmea
bilit
yR
elat
ive
Perm
eabi
lity
0.40.4
0.60.6
0.80.8
Water Saturation (%)Water Saturation (%)00 20201010 3030 4040 5050 6060 7070 8080 9090 100100
00
0.20.2
(Shanley et al, 2003)
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Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Single-Sw Gas Relative PermeabilityAll Tight Gas Sandstones
1bi
lity
0.01
0.1
Rel
ativ
e Pe
rmea
b
1-10 md0.1-1 md0.05-0.1 md0.01-0.05 md0.005-0.01 md0.001-0.005 md0.0001-0.001 md
0.0010 10 20 30 40 50 60 70 80 90 100
Water Saturation (%)
Gas
R 1 md0.1 md0.01 md0.001 md0.0001 md
Relative Permeability Modeling• Early workers (e.g., Burdine, 1953) modeled kr based on Kozeny-
Carmen equation and capillary pressure curves and associated pore size distribution where kr was expressed as a function of the fraction of pore space occupied and the relative size occupiedp p p p
• Example: Wyllie & Spangler (1958)
krw = [(Sw-Swc)/(1-Swc)]2∫∫
0
Sw
1
dSw
Pc2
0dSw
Pc2Tortuosity Term
Gates and Lietz (1950)
Mean HydraulicRadius TermBurdine (1953)
∫
∫Sw
1
1
dSw
Pc2
0dSw
Pc2
krg = [1-(Sw-Swc)/(1-Sgc-Swc)]2
Gates and Lietz (1950)
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Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Corey (1954) Equation• Corey (1954) making the approximation that 1/Pc
2
= C(Sw-Swc)/(1-Swc), i.e., is linear with ΔSw over a range of saturations, simplified the Burdine-P ll d i t ti tPurcell drainage type equations to:
S -S( )4
k
krg = Sw-Swc
1-Sgc-Swc(1- )2 Sw-Swc
1-Swc( )21-( )
Sw Swc
1-Swc( )krw =
•Exponents often modified to adjust for different pore size distribution
Key Features of Krg
Swc decreases with decreasing kiSwc
Sw-Swc,g
1-Sgc-Swc,g
Sw-Swc,gkrg = (1- )1.7
1-Swc,g( )21-( ) Swc,g = 0.16 + 0.053*log10kik
(where<0 then 0)
Scg = 0.15 - 0.05*log10kik
All Tight Gas Sandstones
0.01
0.1
1
Rel
ativ
e Pe
rmea
bilit
y
1-10 md0.1-1 md0.05-0.1 md0.01-0.05 md0.005-0.01 md0.001-0.005 md0.0001-0.001 md1 d
krg, at any given Swincreases with increasing ki
krg,Sw
0.0010 10 20 30 40 50 60 70 80 90 100
Water Saturation (%)
Gas
1 md0.1 md0.01 md0.001 md0.0001 md
Sgc increases with decreasing ki
Sgc
Krg curve shapes are approximately identical for widely different lithofacies
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Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Key Features of Gas Relative Permeability in Low Permeability RocksSwc,g decreases with decreasing ki
Swc,gAll Tight Gas Sandstones
0.01
0.1
1
Rel
ativ
e Pe
rmea
bilit
y
1-10 md0.1-1 md0.05-0.1 md0.01-0.05 md0.005-0.01 md0.001-0.005 md0.0001-0.001 md1 d
krg, at any given Swincreases with increasing ki
krg,Sw
0.0010 10 20 30 40 50 60 70 80 90 100
Water Saturation (%)
Gas
1 md0.1 md0.01 md0.001 md0.0001 md
Sgc increases with decreasing ki
Sgc
Krg curve shapes are approximately identical for widely different lithofacies
Why is Sgc Important?
1
0.001
0.01
0.1
Rel
ativ
e Pe
rmea
bilit
y P = 1.7Sgc = f (kik)
P=f (kik)Sgc = 10%
0.00001
0.0001
0 10 20 30 40 50 60 70 80 90 100Water Saturation
Gas
AAPG ACE Short Course 1: 06.06.2009 161 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Definitions• Critical-gas saturation has been defined variously as
– minimum gas saturation at which the gas phase flows freely (Firoozabadi et al., 1989)
– maximum gas saturation before any gas flow occurs (Moulomaximum gas saturation before any gas flow occurs (Mouloand Longeron, 1989)
– gas saturation at which gas freely flows to the top of a reservoir (Kortekaas and Poelgeest, 1989)
– gas saturation at which gas is produced at the outlet of a core (Li and Yortsos, 1991)Li d Y (1993) i l l ifi d b– Li and Yortsos (1993) appropriately clarified a robust definition as the gas saturation at which the gas forms a system-spanning cluster (and consequently flows freely). This definition is consistent with the critical percolation threshold at which the gas is connected to all parts of the system and not just flowing in a subset of the system.
Measured Sgc• 0.006 < Sgc < 0.38
– Solution-gas laboratory-measured (Hunt and Berry, 1956; Handy, 1958; Moulu and Longeron, 1989; Kortekaas and Poelgeest, 1989; Firoozabadi et al., 1989; and Kamath and Boyer, 1993)
• 0.03 < Sgc < 0.11– 0.0008 mD < kik < 0.031 mD, n =11, Chowdiah (1987)
• Sgc=0.01– k = 0.10 mD, Colton sandstone sample, Kamath and Boyer (1993)
• Sgc = 0.10– solution gas drive, k = 0.10 mD, Colton sandstone sample, Kamath and Boyer
(1993)
• Sgc=0.02– Torpedo sandstone, k = 413 mD, Closmann (1987)
• 0.045 < Sgc < 0.17– Schowalter (1979) , n=10, 0.01 mD < k < 30.09 mD
AAPG ACE Short Course 1: 06.06.2009 162 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Published Single-Saturation Gas Relative Permeablity
0 10000
1.00000y
0.00100
0.01000
0.10000
as R
ealti
ve P
erm
eabi
lity
Thomas & Ward, 1972Byrnes et al, 1979Jones & Owens, 1980Sampath & Keighin, 1981Walls, 1981Chowdiah, 1990
0.00001
0.00010
0 10 20 30 40 50 60 70 80 90 100Water Saturation (%)
G Morrow et al, 1991Byrnes, 1992Byrnes, 1997Byrnes & Castle, 2000
Measurement of Snwc (Sgc)• Confined mercury intrusion
with electrical conductivity• Advantages
Hg in ΔV
– Percolation threshold of Hg detected by resistivity drop of >200x105 to <5 ohm
– Able to determine Pc equilibrium saturation after non-equilibrium breakthrough
Cor
e
q g– Determine pore throat size
difference between entry threshold and percolation threshold
High P Vesseloil
Pnetconfining = 4,000 psi
AAPG ACE Short Course 1: 06.06.2009 163 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Critical Non-wetting Phase Saturation
0.16
0.18
0.20
0.22
g Ph
ase MICP-inflection
Electrical Resistance
0 02
0.04
0.06
0.08
0.10
0.12
0.14
Crit
ical
Non
-wet
ting
Satu
ratio
n
• Electrical conductivity and Pc inflection indicate 0% < Snwc < 22%• Higher Snwc in complex bedding lithofacies
0.00
0.02
0.00001 0.0001 0.001 0.01 0.1 1 10 100 1000
In situ Klinkenberg Permeability (mD)
Measurement of Snwc (Sgc)• Confined gas injection• Advantages
– Sample water wetl i f fi b bbl i
N2 inmicropipette
gas bubble
– Expulsion of first gas bubble is highly sensitive
– Sgc from both Vgas and weight change
• Disadvantages– Potential saturation gradient
Cor
e
g– Solution gas development at
high pressure– Pore volume change with stress
and possible hysteresisHigh P Vesseloil
Pconfining = 4,000 psi
AAPG ACE Short Course 1: 06.06.2009 164 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Critical Gas Saturation
0.70.80.91.0
35404550
Sgc Histogram
0.00.10.20.30.40.50.6
05
1015202530
00 04 08 12 16 20 24 28 32 36 40 44 48
Freq
uenc
y
• Sgcavg = 0.066+0.13 (2 stdev)• Wide variance
0.0
0.0
0.0
0. 0. 0.2
0.2
0.2
0.3
0.3
0.4
0.4
0.4
Critical Gas Saturation
Critical Gas Saturation
0.35
0.40
0.45
0.50
urat
ion
0 00
0.05
0.10
0.15
0.20
0.25
0.30
Crit
ical
Gas
Sat
u
• Sgc is low for high permeability samples and fraction of population shows increasing Sgc with decreasing permeability
0.000.0001 0.001 0.01 0.1 1 10 100
In situ Klinkenberg Permeability (mD)
AAPG ACE Short Course 1: 06.06.2009 165 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
How does Sgc get so high?• In cross-bedded sandstone
series intrusion requires Pc=threshold of lowest k 80
100
120
140
Pres
sure
(psi
)
0.1 md0.01 md0.001 md
1Pc=threshold of lowest k facies
• Sgc = f(Pc1&Pc2, V1/V2, Sgc1&Sgc2, Pc equilibrium, architecture)
0
20
40
60
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Water Saturation (fraction)
Gas
-Wat
er C
apill
ary
P
12
2
12
Sgc=75% Sgc=75%
Sgc=5%
Sgc=5%
1
12
Sgc vs beddingbedding
Corey and Rathjens(1956)
AAPG ACE Short Course 1: 06.06.2009 166 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Sgc and PercolationInvasion direction
3) Series network N ( ) - preferential sample-
• Sgc (L) = A LD−E(Wilkinson and Willemsen, 1983)
– L is network dimension– A is a numerical constant (for
simple cubic network A = 0.65)– D is the mass fractal dimension
1) Percolation Network N ( ) - Macroscopically homogeneous, random distribution of bond sizes, e.g., Simple Cubic Network (z=6)
p
2) Parallel Network N ( ) preferential orientation of pore sizes or beds of different
II
Nspanning orientation of pore sizes or beds of different networks perpendicular to the invasion direction.
p
4) Discontinuous series network N ( ) - preferential non-sample-spanning orientation
d
800
900
1000
re(k
Pa)
0.001 md0.1 md
of the percolation cluster – E is the Euclidean dimension
• As L → ∞ Sgc → 0 – Sgc = 21.5% for L = 10– Sgc = 2.4% for L = 1000– Sgc = 0.8% for L = 10000)
• Experimental results can be explained using four - pore network architecture models
Np
networks parallel to the invasion direction.
p Np
N N
p p p gof pore sizes or beds of different networks perpendicular to the invasion direction. Represents continuum between and p.
0
100
200
300
400
500
600
700
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0Water Saturation
Gas
-Wat
erC
apill
ary
Pres
sur
AB
Sgc andpercolation theory
•• critical gas saturation critical gas saturation strongly controlled by strongly controlled by sedimentary structures/rock sedimentary structures/rock f b if b i
Invasion direction
3) Series network N( ) - preferential sample- fabricfabric•• anyany bedding parallel bedding parallel
laminations result in low laminations result in low SgcSgc
1) Percolation Network N ( ) - Macroscopically homogeneous, random distribution of bond sizes, e.g., Simple Cubic Network (z=6)
p
2) Parallel Network N
N
( ) preferential orientation of pore sizes or beds of different
networks parallel to the invasion
II
3) Series network N
N
( ) - preferential sample-spanning orientation of pore sizes or beds of different networks perpendicular to the invasion direction.
p
4) Discontinuous series network N
Np
( ) - preferential non-sample-spanning orientation of pore sizes or beds of different networks
d
700
800
900
1000
sure
(kPa
)
0.001 md0.1 md
•• experimental results can be experimental results can be explained using four explained using four -- pore pore network architecture modelsnetwork architecture models
N networks parallel to the invasion direction.
p Np
N N
of pore sizes or beds of different networks perpendicular to the invasion direction. Represents continuum between and p.
0
100
200
300
400
500
600
700
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0Water Saturation
Gas
-Wat
erC
apill
ary
Pres
s
AB
AAPG ACE Short Course 1: 06.06.2009 167 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Prediction of Sgc• Four pore network architecture models:
– percolation (Np)– parallel (N//)– series (N⊥)
discontinuous series (N )– discontinuous series (N⊥d)
• Analysis suggests that Sgc is scale- and bedding-architecture dependent in cores and in the field.
• Sgc is likely to be very low in cores with laminae and laminated reservoirs (N//)) and low (e.g., Sgc < 0.03-0.07 at core scale and Sgc < 0.02 at reservoir scale) in massive-bedded sandstones of any permeability (Np)
• In cross-bedded lithologies exhibiting series network properties (N⊥), Sgcapproaches a constant reflecting the capillary pressure property differences and
l ti l th b d i i F th t k Srelative pore volumes among the beds in series. For these networks Sgc can range widely but can reach high values (e.g., Sgc < 0.6)
• Discontinuous series networks, representing lithologies exhibiting series network properties but for which the restrictive beds are not sample-spanning (N⊥d), exhibit Sgc intermediate between Np and N⊥ networks.
CMG IMEXSingle 1-ft thick High-Permeability Layered
Reservoir Simulation Model
• 1ft – 0.01, 0.1, 1, 10, 100 md• keg=0.004,0.04,0.4,4,40 md• Swc= 0.34, krg = 0.38• kbase= 0.004 md, kvert = 0.0004md
AAPG ACE Short Course 1: 06.06.2009 168 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Base Model – keg=0.004 md
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+06
1.E+07
1.E+08
1.E+09
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
khigh = 4 md, kbase = 0.004 md
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
1.E+07
1.E+08
1.E+09
1.E+10
J-01 J-02 J-03 J-04 J-05 J-06Time (m-yr)
Cum
ulat
ive
Gas
(scf
)
AAPG ACE Short Course 1: 06.06.2009 169 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Effect of high-k thin-bed on
recovery
recovery relative to recovery
without bed
Influence of Vertical Permeability
AAPG ACE Short Course 1: 06.06.2009 170 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
BioturbationLenticular bedded
isolated lensesLenticular bedded
thick connected lensesWavy bedded
Shaly Sandstone
• Core through non-bioturbated interval would indicate good k in lenses
core
g g• Series flow indicates long-range permeability would be reduced to
permeability of shale k < 1μd• Bioturbation decreases k of lenses by 5-10X but preserves average k• Beneficial effect of bioturbation decreases with increasing sand:shale
ratio but amount of k decrease also decreases
Permeability ScalesPlug
Wireline- log
DST-Well Test
Lease-Reservoir
Establish role ofHeterogeneities& Fractures
Establish role ofHeterogeneities& F t
Full-DiameterCore
& Fractures
AAPG ACE Short Course 1: 06.06.2009 171 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Conclusions• Drainage capillary pressure (Pc) can be modeled using
equations for threshold entry pressure (Pte) and Brooks-Corey λslopes.
• Capillary pressure (Pc) exhibits a log-log threshold entry (Pt ) k /φ t d d i bl B k Cpressure (Pte) versus kik/φi trend and variable Brooks-Corey
slopes. • Snwr ↑ with Snwi ↑ Land-type relation: 1/Snwr-1/Snwi = 0.55 •• Capillary pressure (Pc) is stress sensitive as expectedCapillary pressure (Pc) is stress sensitive as expected
–– threshold entry pressure is predictable from √K/threshold entry pressure is predictable from √K/ φφ at any at any confining pressureconfining pressure
•• Confining pressure decreases largest pores consistent with Confining pressure decreases largest pores consistent with g p g pg p g ppermeability decrease but has little influence on smaller pores permeability decrease but has little influence on smaller pores (pores largely protected by matrix)(pores largely protected by matrix)
•• Residual gas saturation increases with increasing initial gas Residual gas saturation increases with increasing initial gas saturationsaturation–– LandLand--type relation: (1/type relation: (1/SnwrSnwr))--(1/(1/SnwiSnwi) = 0.55 ) = 0.55
Conclusions• Multi-salinity measurements of Archie cementation exponent, m, have
been completed on 408 samples at various salinities for each sample– 20,000 ppm NaCl, 40,000 ppm, 80,000 ppm, and 200,000 ppm– Three times the number proposed
• Nearly all core exhibit some dependence of conductivity and cementation exponent on salinity
• The salinity dependence of m is weakly negatively correlated with porosity
• Using equations developed the Archie cementation exponent can be predicted for any given porosity and formation brine salinity
• Archie cementation exponent (m) decreases with decreasing porosity below approximately 6%
C b d l d i i l b d l it d l– Can be modeled- empirical or by a dual- porosity model
AAPG ACE Short Course 1: 06.06.2009 172 of 217
Byrnes: Capillary Pressure, Electrical Properties, Relative Permeability
Conclusions• Analysis suggests that Sgc is scale- and bedding-architecture dependent in
cores and in the field. • Sgc is likely to be very low in cores with laminae and laminated reservoirs
( )) d l ( S 0 03 0 0 l d S 0 02 i(N//)) and low (e.g., Sgc < 0.03-0.07 at core scale and Sgc < 0.02 at reservoir scale) in massive-bedded sandstones of any permeability (Np)
• In cross-bedded lithologies exhibiting series network properties (N⊥), Sgcapproaches a constant reflecting the capillary pressure property differences and relative pore volumes among the beds in series. For these networks Sgccan range widely but can reach high values (e.g., Sgc < 0.6)
• Discontinuous series networks, representing lithologies exhibiting series t k ti b t f hi h th t i ti b d t lnetwork properties but for which the restrictive beds are not sample-
spanning (N⊥d), exhibit Sgc intermediate between Np and N⊥ networks.
AAPG ACE Short Course 1: 06.06.2009 173 of 217
Krygowski: Log Responses in Tight Shaly Gas Sands
Lithofacies and Petrophysical Lithofacies and Petrophysical P ti f M d Ti htP ti f M d Ti ht GGProperties of Mesaverde TightProperties of Mesaverde Tight--Gas Gas Sandstones in Western U.S. Basins:Sandstones in Western U.S. Basins:Log Responses in Tight Shaly Gas SandsLog Responses in Tight Shaly Gas Sands
Dan KrygowskiDan Krygowski
Denver, ColoradoAAPG ACE 2009: Denver Colorado 11
The geologic environmentThe geologic environmentComplicated lithology/mineralogyComplicated lithology/mineralogy
QuartzQuartzMixture of clays maybe diagenetic productsMixture of clays maybe diagenetic products
Quantities of interest
Mixture of clays, maybe diagenetic products Mixture of clays, maybe diagenetic products (Vcl/Vsh)
Low porosity, <15%Low porosity, <15% (Phi)FluidsFluids
Gas (water saturation, Sw < 1)Gas (water saturation, Sw < 1) (Sw)Relatively fresh waters Relatively fresh waters (Rw)
AAPG ACE 2009: Denver Colorado 2
yy ( )High irreducible water saturation High irreducible water saturation (Swirr)
Permeability Permeability (k)Low, and of interestLow, and of interest
AAPG ACE Short Course 1: 06.06.2009 174 of 217
Krygowski: Log Responses in Tight Shaly Gas Sands
ExxonMobil Willow Ridge T63X-2G
A Mesaverde A Mesaverde exampleexample
2.65
Rio Blanco county, COPiceance Basin
AAPG ACE 2009: Denver Colorado 3
Environmental effects on the logsEnvironmental effects on the logsComplicated lithology/mineralogyComplicated lithology/mineralogy
Presence of clayPresence of clay•• Gamma ray, SP: decreased response as compared to Gamma ray, SP: decreased response as compared to Ga a ay, S dec eased espo se as co pa ed toGa a ay, S dec eased espo se as co pa ed to
nearby shales.nearby shales.GR may also be affected by radioactive KGR may also be affected by radioactive K--feldspar.feldspar.
•• Porosity measurementsPorosity measurementsDensity porosity: slightly lowerDensity porosity: slightly lowerNeutron porosity: higherNeutron porosity: higherSonic porosity: higherSonic porosity: higher
AAPG ACE 2009: Denver Colorado 4
•• Resistivity: lower, from additional clay conductivity.Resistivity: lower, from additional clay conductivity.May make water saturation calculations higher May make water saturation calculations higher than actual saturations.than actual saturations.
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Krygowski: Log Responses in Tight Shaly Gas Sands
Environmental effects IIEnvironmental effects IIFluidsFluids
GasGas•• Gamma ray: no change. SP: decreased responseGamma ray: no change. SP: decreased response•• Density porosity: slightly higherDensity porosity: slightly higher•• Neutron porosity: lowerNeutron porosity: lower•• Sonic porosity: variableSonic porosity: variable
Relatively fresh waterRelatively fresh water•• Clay conductivity will be a larger percentage of the total Clay conductivity will be a larger percentage of the total
conductivity than in a salt water case.conductivity than in a salt water case.•• Resistivity decreased from equivalent clean case;Resistivity decreased from equivalent clean case;
AAPG ACE 2009: Denver Colorado 5
y qy qShaly sand version of Archie needed?Shaly sand version of Archie needed?
High irreducible waterHigh irreducible water•• WaterWater--free production even with elevated water free production even with elevated water
saturations.saturations.
Environmental effects IIIEnvironmental effects IIIPermeabilityPermeability
Low, but of interestLow, but of interest•• Logs,even NMR logs, don’t measure permeability, but Logs,even NMR logs, don’t measure permeability, but ogs,e e ogs, do t easu e pe eab ty, butogs,e e ogs, do t easu e pe eab ty, but
we can infer permeability from log response. we can infer permeability from log response. •• Many equations; functions of porosity and irreducible Many equations; functions of porosity and irreducible
water saturation.water saturation.An example: Timur:An example: Timur:
•• We can get Swirr from BVWirr, irreducible bulk volume We can get Swirr from BVWirr, irreducible bulk volume water: BVW = Phi*Sw and BVWirr = Phi* Swirrwater: BVW = Phi*Sw and BVWirr = Phi* Swirr
⎟⎟⎠
⎞⎜⎜⎝
⎛∗= 2
662500
irrT
SwPhiK
AAPG ACE 2009: Denver Colorado 6
water: BVW = Phi Sw, and BVWirr = Phi Swirrwater: BVW = Phi Sw, and BVWirr = Phi Swirr
and BVW can give us some indication of fluids and BVW can give us some indication of fluids that will be produced (water vs no water).that will be produced (water vs no water).
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Krygowski: Log Responses in Tight Shaly Gas Sands
Quantities, parameters of interestQuantities, parameters of interestClay/shale volumeClay/shale volume
Density/neutron: problematic because of gas Density/neutron: problematic because of gas effects on the neutron.effects on the neutron.
•• In general, neutron porosity has issues in the Rockies.In general, neutron porosity has issues in the Rockies.
olum
e, V
sh
SP: hydrocarbon SP: hydrocarbon effects will make effects will make Vsh too high.Vsh too high.Gamma ray: Gamma ray: probably the best. probably the best.
AAPG ACE 2009: Denver Colorado 7Radioactivity Index, IRAGamma Ray Index, IGR
Shal
e vp yp y
Use linear unless Use linear unless other data indicates other data indicates otherwise.otherwise.
Vsh may be needed for the following quantities...
BakerAtlas, 1984
More quantities of interestMore quantities of interestPorosity, PhiPorosity, Phi
Need matrix and fluid parametersNeed matrix and fluid parameters•• Variable matrix parameters are not uncommon.Variable matrix parameters are not uncommon.a ab e at pa a ete s a e ot u co oa ab e at pa a ete s a e ot u co o
May need shale/clay parameters: Vsh, shale May need shale/clay parameters: Vsh, shale values for specific measurements: density, values for specific measurements: density,
tt
RHOflRHOmaRHOBRHOmaPHID
−−
=
DTDTmaDT
DTmaDTflDTmaDTPHIS −
=−−
= *32 or
AAPG ACE 2009: Denver Colorado 8
neutron, …neutron, …•• Effective porosity from total porosity, Vsh, and shale Effective porosity from total porosity, Vsh, and shale
response.response.SHeff PHIDVshPHIDPHID ∗−=
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Krygowski: Log Responses in Tight Shaly Gas Sands
Porosity in a gas zonePorosity in a gas zoneSingle porosity measurementSingle porosity measurement
Can the matrix and fluid parameters in the Can the matrix and fluid parameters in the volume of investigation be sufficiently estimated volume of investigation be sufficiently estimated g yg yto produce a reasonable porosity?to produce a reasonable porosity?
•• Most porosity measurements are in the flushed zone.Most porosity measurements are in the flushed zone.
Porosity measurement combinations: Porosity measurement combinations: density and neutrondensity and neutron
If the neutron is good, this is actually a good If the neutron is good, this is actually a good ti t f h d bti t f h d b t d l tt d l t
AAPG ACE 2009: Denver Colorado 9
estimate of hydrocarbonestimate of hydrocarbon--corrected crossplot corrected crossplot porosity.porosity.
21
22
2 ⎟⎟⎠
⎞⎜⎜⎝
⎛ +=
PHINePHIDePHIE
More quantities, for saturationMore quantities, for saturationWater saturation, SwWater saturation, Sw
Water resistivity, RwWater resistivity, Rw•• Produced waters yield Rw values that are much too Produced waters yield Rw values that are much too
fresh (water of condensation in the gas).fresh (water of condensation in the gas).•• NOT SP! NOT SP! Rwa vs GR
75
100
125
150
GR
RwbGRshale•• Pickett plot or Rwa, Pickett plot or Rwa,
apparent water resistivity apparent water resistivity
Archie parameters, a, Archie parameters, a, m (variable), nm (variable), n•• Local knowledge; PickettLocal knowledge; Pickett
AAPG ACE 2009: Denver Colorado 10If Rwf = Rwb, use Archie.
0
25
50
0.1 1 10 100
Rwa
Rw, Rwf
data
GRclean
•• Local knowledge; Pickett Local knowledge; Pickett plotplot
Which form of Archie’s Which form of Archie’s equation?equation?•• Vsh & Rsh; or Rwf & Vsh & Rsh; or Rwf &
RwbRwb
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Krygowski: Log Responses in Tight Shaly Gas Sands
Rwa in the MesaverdeRwa in the MesaverdeRwb
AAPG ACE 2009: Denver Colorado 11
Rw, Rwf
Another saturation parameter methodAnother saturation parameter method
“Super Pickett” plot“Super Pickett” plotGetting a number of parameters.Getting a number of parameters.BVWirr canBVWirr can
Pickett plot
0.1
1
rosi
ty data
reas
ing
Sw
Rw BVWirrincreasing BVW
Slope = f(saturation exponent,n)BVWirr can BVWirr can also be also be estimated estimated from a log from a log plot.plot.
AAPG ACE 2009: Denver Colorado 12
0.011 10 100 1000
Resistivity
Po
Sw = 1
decr
Slope = -1/cementation exponent, m
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Krygowski: Log Responses in Tight Shaly Gas Sands
Pickett with Mesaverde dataPickett with Mesaverde data
Sw = 1 0 6 0 4 0 2
BVW = 0.10.05
0.04BVWirr = 0.026
From slope,saturation exponent, n = 2.0
Rw = 0.064
Sw = 1 0.6 0.4 0.2
From slope,cementation exponent, m = 1.85
AAPG ACE 2009: Denver Colorado 13
Which saturation equation to use?Which saturation equation to use?The most commonly used in the Rockies:The most commonly used in the Rockies:
ArchieArchie21⎞⎛ ∗Rwa
In conductivity spaceIn conductivity space(Ct = 1000/Rt):(Ct = 1000/Rt):
Dual WaterDual Water
2⎟⎠
⎞⎜⎝
⎛∗
∗=
RtPhiRwaSw m CwPhiSwaCt mn ∗∗∗=
⎤⎡ ⎞⎛
SwSw = [a number of versions are published…]= [a number of versions are published…]
AAPG ACE 2009: Denver Colorado 14
⎥⎦
⎤⎢⎣
⎡∗+∗⎟
⎠
⎞⎜⎝
⎛ −∗∗= CwbSwSwbCwf
SwSwbPhiSwCt mn 1
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Krygowski: Log Responses in Tight Shaly Gas Sands
Mesaverde Mesaverde data againdata again
What about permeability?What about permeability?Timur (and other equations) requires Swirr.Timur (and other equations) requires Swirr.
•• Swirr is a proxy for surface area.Swirr is a proxy for surface area.We can get Swirr from BVWirr:We can get Swirr from BVWirr:
But the permeability numbers are suspect (at But the permeability numbers are suspect (at best).best).
•• Core data is needed to calibrate the permeability Core data is needed to calibrate the permeability calculation, calibration being done by modifying the calculation, calibration being done by modifying the porosity and saturation exponents.porosity and saturation exponents.
PHIBVWirrSwirr /=
AAPG ACE 2009: Denver Colorado 16
porosity and saturation exponents.porosity and saturation exponents.NMR logs can provide permeabilityNMR logs can provide permeability
•• They measure both Phi and BVWirr.They measure both Phi and BVWirr.•• But they still need calibration to core for quantitative But they still need calibration to core for quantitative
values.values.
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Krygowski: Log Responses in Tight Shaly Gas Sands
…and bulk volume water, BVW……and bulk volume water, BVW…If Sw < 1, and BVW is a constant, the zone If Sw < 1, and BVW is a constant, the zone has a good chance of producing waterhas a good chance of producing water--free.free.
But we can’t determine the production volumesBut we can’t determine the production volumesBut we can t determine the production volumes.But we can t determine the production volumes.If BVW > 0.05, there’s a good chance that the If BVW > 0.05, there’s a good chance that the well will produce no fluids at all.well will produce no fluids at all.
•• Pore throats are blocked by water.Pore throats are blocked by water.
AAPG ACE 2009: Denver Colorado 17
Mesaverde Mesaverde with with permeability permeability and BVWand BVW
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Krygowski: Log Responses in Tight Shaly Gas Sands
ConclusionsConclusionsThe combination of gas, shaly formations, The combination of gas, shaly formations, and low porosity has adverse affects on all and low porosity has adverse affects on all the logging measurements.the logging measurements.the logging measurements.the logging measurements.
Some of the effects counteract each other; i.e., Some of the effects counteract each other; i.e., gas and clays on neutron porosity.gas and clays on neutron porosity.Generally, the difference between wet zones and Generally, the difference between wet zones and pay is more subtle.pay is more subtle.
AAPG ACE 2009: Denver Colorado 19
So, what specifically have we learned about So, what specifically have we learned about the Mesaverde in the Rockies?the Mesaverde in the Rockies?
The story continues…The story continues…
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Whittaker: Standard Log Analysis
Lithofacies and Petrophysical Lithofacies and Petrophysical Properties of Mesaverde TightProperties of Mesaverde Tight GasGasProperties of Mesaverde TightProperties of Mesaverde Tight--Gas Gas Sandstones in Western U.S. Basins:Sandstones in Western U.S. Basins:Standard AnalysisStandard Analysis
Stefani WhittakerStefani Whittaker
Denver, ColoradoAAPG ACE 2009: Denver Colorado 11
OUTLINEOUTLINE
DATA PREPARATION
Gather Data and Initial Clean up Calc. In situ Core DataImport corrected core data, rock type numbers, and point count numbersShifting: Core data, point count data and rock type data
AAPG ACE 2009: Denver Colorado 2
type data Pick tops and zonesSetting up zone parameters
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Whittaker: Standard Log Analysis
CALCULATION:
Calculate VshCalculate VshTotal and Effective Porosities Calculate SwLook at a Pickett Plot Calculate SWICalculate perm
AAPG ACE 2009: Denver Colorado 3
Calculate perm
Gathering WellGathering Well--Log DataLog Data
Required Curves Required Curves
Depth Matching Depth Matching p gp g
Merging Multiple RunsMerging Multiple Runs
Tool PickTool Pick--up up
Neutron Matrix ConversionNeutron Matrix Conversion
AAPG ACE 2009: Denver Colorado 4
NormalizationNormalization
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Whittaker: Standard Log Analysis
Calculating Calculating InIn--situsitu Core DataCore DataKlinkenbergKlinkenberg CorrectedCorrected
008.0−=CPHICPHIinsitu
Porosity
Permeability
6.0)(log341.1log −= routineinsitu kK
AAPG ACE 2009: Denver Colorado 5
*Note: Alan Byrnes equation from The Mountain Geologist; Volume 34; Number 1; “Reservoir Characteristics of Low-Permeability Sandstones in the Rocky Mountains”; pg. 42. There is a mistype in the publication, the above equation is the CORRECT equation.
Importing DataImporting Data1)1) In Situ Core Data In Situ Core Data
●● Conventional Core DataConventional Core Data●● KGS analyzed Core DataKGS analyzed Core Data (Appended _KGS)(Appended _KGS)
2)2) Rock Type DataRock Type Data•• Core description 5 digit rock type codeCore description 5 digit rock type code•• 5 digit code can be compared to GR5 digit code can be compared to GR
AAPG ACE 2009: Denver Colorado 6
3)3) Point Count DataPoint Count Data•• Thin Section Point Count Data Thin Section Point Count Data •• The total radiation term (VRAD_TS) can The total radiation term (VRAD_TS) can
be compared to the Vsh curve in the logs.be compared to the Vsh curve in the logs.
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Whittaker: Standard Log Analysis
VANHCMT_TSVANHCMT_TS Volume of anhydrite in thin sectionVolume of anhydrite in thin section
VCCMT_TSVCCMT_TS Volume of clay cement in thin sectionVolume of clay cement in thin section
VCO3CMT_TSVCO3CMT_TS Volume of carbonate cement in thin sectionVolume of carbonate cement in thin section
VKSP_TSVKSP_TS Volume of Potassium Feldspar in thin sectionVolume of Potassium Feldspar in thin section
VKVRF_TSVKVRF_TS Volume of Potassium rich volcanic rock fragments in thin sectionVolume of Potassium rich volcanic rock fragments in thin section
VOSRF_TSVOSRF_TS Volume of of other sedimenary rock fragments in thin sectionVolume of of other sedimenary rock fragments in thin section
VOVRF_TSVOVRF_TS Volume of other volcanic rock fragments in thin sectionVolume of other volcanic rock fragments in thin section
VPLAG_TSVPLAG_TS Volume of Plagioclase Feldspars in thin sectionVolume of Plagioclase Feldspars in thin section
VQTZ TSVQTZ TS Volume of quartz in thin sectionVolume of quartz in thin sectionVQTZ_TSVQTZ_TS Volume of quartz in thin sectionVolume of quartz in thin section
VQTZCMT_TSVQTZCMT_TS Volume of quartz cement in thin sectionVolume of quartz cement in thin section
VRAD_TSVRAD_TS Volume of Radioactive Elements in thin section Volume of Radioactive Elements in thin section (VRAD_TS = VKSP_TS + VKVRF_TS + VSSRF_TS + VCCMT_TS + VOVRF_TS)(VRAD_TS = VKSP_TS + VKVRF_TS + VSSRF_TS + VCCMT_TS + VOVRF_TS)
VSSRF_TSVSSRF_TS Volume of Shaley sedimentary rock fragments in thin sectionVolume of Shaley sedimentary rock fragments in thin section
VVISPOR_TSVVISPOR_TS Volume of Visible Porosity in thin sectionVolume of Visible Porosity in thin section
Depth Shifting Core DataDepth Shifting Core Data
Rock Type Number was compared to the GR.Rock Type Number was compared to the GR.
Data Shifted together:Data Shifted together:•• Conventional Core DataConventional Core Data•• KGS analyzed Core DataKGS analyzed Core Data•• Point Count DataPoint Count Data•• Rock Type DataRock Type Data
AAPG ACE 2009: Denver Colorado 8
Rock Type DataRock Type Data
AAPG ACE Short Course 1: 06.06.2009 187 of 217
Whittaker: Standard Log Analysis
Picking Tops and ZonesPicking Tops and Zones
11 PIPI DwightsDwights scout tickets for formation topsscout tickets for formation tops1.1. PI PI DwightsDwights scout tickets for formation tops.scout tickets for formation tops.
2.2. Zones were chosen based on changes in Zones were chosen based on changes in petrophysicalpetrophysical properties to “tighten the properties to “tighten the log/core correlation log/core correlation
•• GRGR
AAPG ACE 2009: Denver Colorado 9
•• GRGR•• PorosityPorosity•• InductionInduction
Standard Discovery Group Standard Discovery Group Shaly Sand ProcessShaly Sand Process
1.1. Set up ParametersSet up Parameters22 Calculate VshaleCalculate Vshale2.2. Calculate VshaleCalculate Vshale3.3. Calculate Porosity Calculate Porosity (Total, Effective, Cross(Total, Effective, Cross--Plot)Plot)
4.4. Calculate Water SaturationCalculate Water Saturation5.5. Calculate Bulk Volume Water andCalculate Bulk Volume Water and
Bulk Volume Water IrreducibleBulk Volume Water Irreducible
AAPG ACE 2009: Denver Colorado 10
and Calculate Irreducible Water Saturationand Calculate Irreducible Water Saturation6.6. Calculate PermeabilityCalculate Permeability
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Whittaker: Standard Log Analysis
Setting up zone ParametersSetting up zone ParametersDeep ResistivityDeep Resistivity Rt = RdeepRt = Rdeep
Rho Matrix Rho Matrix From Header DataFrom Header Data
Neutron MatrixNeutron Matrix From Header DataFrom Header DataNeutron Matrix Neutron Matrix From Header Data From Header Data
Vshale Model Vshale Model Linear using GRLinear using GR
Water Sat. Model Water Sat. Model Archie’s (m=1.85, n=2, a=1)Archie’s (m=1.85, n=2, a=1)
BVW Model BVW Model Effective PorosityEffective Porosity
AAPG ACE 2009: Denver Colorado 11
Permeability ModelPermeability Model Timur ModelTimur Model
Parameters for Permeability were varied by zone:•Permeability Porosity Exponent [KPHIEXP] (Ranged from 5.0 - 9.25)
•Permeability Irreducible Water Saturation Exponent [KSWIEXP] (Ranged from 1.5 - 2.0)
Calculate VshCalculate Vsh
Used the GR with the Linear method to calculate Vsh. Used the GR with the Linear method to calculate Vsh.
Rocky Mountain Region Suggestions:Rocky Mountain Region Suggestions:
cleansh
cleansh GRGR
GRGRV
−
−= log
AAPG ACE 2009: Denver Colorado 12
y g ggy g ggGR_CLEAN = 10GR_CLEAN = 10--15 API15 APIGR_SHALE = 90GR_SHALE = 90--100 API100 API
(Will vary from well to well)(Will vary from well to well)
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Whittaker: Standard Log Analysis
Total PorosityTotal Porosity
Total Porosity Total Porosity PHIN = Converted from LS units toPHIN = Converted from LS units toPHIN = Converted from LS units to PHIN = Converted from LS units to desired output desired output lithologylithology units.units.
PHID = PHID = RHOFLRHOMARHOBRHOMA
−− (Wyllie Time (Wyllie Time
Average Equation)Average Equation)
AAPG ACE 2009: Denver Colorado 13
PHIS = PHIS = DTMADTFDTMAt
−−Δ log
•Take RHOB and Neutron Φ and cross plot them to get a PHIDN
Cross-Plot Porosities
PROS:
-Corrects for grain density
-Eliminates most of the gas effect
CONS:
-Requires a good NPHI log
AAPG ACE Short Course 1: 06.06.2009 190 of 217
Whittaker: Standard Log Analysis
Effective PorosityEffective Porosity
)*( PHINSHVPHINPHINE sh−=
)*( PHIDSHVPHIDPHIDE sh−=
)*( PHISSHVPHISPHISE sh−=
AAPG ACE 2009: Denver Colorado 15
)*( PHIDNSHVPHIDNPHIDNE sh−=
(Diminish the effect of Shale)(Diminish the effect of Shale)
Total Φ Diminishes Shale Volume Diminishes1. Grain Density Differences2. Gas Effect3. Shale Volume
AAPG ACE Short Course 1: 06.06.2009 191 of 217
Whittaker: Standard Log Analysis
Calculate SwCalculate SwArchie’s Water Saturation equationArchie’s Water Saturation equation
a=1; n=2; m=1.85 (Rocky Mountain Suggestion)a=1; n=2; m=1.85 (Rocky Mountain Suggestion)RwRw = Zoned (Pickett Plot or = Zoned (Pickett Plot or RwaRwa plot)plot)Used Neutron/Density Used Neutron/Density crossplotcrossplot Effective PorosityEffective PorosityRtRt = Deep Resistivity= Deep Resistivity
n waRSw =
AAPG ACE 2009: Denver Colorado 17
n
tmR
Swφ
BVW, BVWI and SWIBVW, BVWI and SWITwo ways to find BVW, BVWI, and SWITwo ways to find BVW, BVWI, and SWI
1) Calculate and visual estimation1) Calculate and visual estimation2) Graphically using Pickett Plot2) Graphically using Pickett Plot
Calculate:Calculate:
we SPHIEBVW *=wT SPHIXBVW *=
AAPG ACE 2009: Denver Colorado 18
Then look at a consistently flat part on the BVW and Then look at a consistently flat part on the BVW and visually pick the BVWIvisually pick the BVWI
PHIBVWISWI /=
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Whittaker: Standard Log Analysis
Pickett PlotPickett Plot100% Water Sat. when a=1
Iso BVW lines
BVWI
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Whittaker: Standard Log Analysis
Calculate PermeabilityCalculate Permeability
Used the Timur Model for permeabilityUsed the Timur Model for permeability
62500=coefK
25.90.5~ −KPHIEXPK
0.25.1~ −KSWIEXPK
(Determined by zone)
(Determined by zone)
AAPG ACE 2009: Denver Colorado 21
KSWIEXP
KPHIEXP
coef SWIPHIXKK =log
Piceance BasinPiceance Basin
Vshale Φ, m&nΦ, SWIKexp.
Left to right more error introducedLeft to right more error introducedError introduced =
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Whittaker: Standard Log Analysis
Green River BasinGreen River Basin
Washakie BasinWashakie Basin
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Whittaker: Standard Log Analysis
Uinta BasinUinta Basin
Wind River BasinWind River Basin
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Cluff: Advanced Log Models
Lithofacies and Petrophysical Lithofacies and Petrophysical Properties of Mesaverde TightProperties of Mesaverde Tight GasGasProperties of Mesaverde TightProperties of Mesaverde Tight--Gas Gas Sandstones in Western U.S. Basins:Sandstones in Western U.S. Basins:Advanced Log AnalysisAdvanced Log Analysis
Bob CluffBob CluffThe Discovery Group IncThe Discovery Group Inc
Denver, ColoradoAAPG ACE 2009: Denver Colorado 11
The Discovery Group Inc.The Discovery Group Inc.2009 AAPG Annual Convention Short course #12009 AAPG Annual Convention Short course #1
6 June 2009, Denver, Colorado6 June 2009, Denver, Colorado
OutlineOutlinerock typingrock typingvariable m model for Swvariable m model for Sw
as an alternative to obtuse shaly sand modelsas an alternative to obtuse shaly sand modelsas an alternative to obtuse shaly sand modelsas an alternative to obtuse shaly sand modelspermeability modelingpermeability modeling
AAPG ACE 2009: Denver Colorado 2
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Cluff: Advanced Log Models
Advanced rock typingAdvanced rock typingmost rock typing methods follow some form of most rock typing methods follow some form of φφ--K K separation or BVW separationseparation or BVW separation
Winland R35 isoWinland R35 iso--lineslinesK/K/φφ ratiosratiosBVW classesBVW classes
or, some kind of statistical relationship with logs is or, some kind of statistical relationship with logs is soughtsought
single variate comparsions (e.g. GR vs grain size)single variate comparsions (e.g. GR vs grain size)multivariate comparisons, cluster analysis, etc.multivariate comparisons, cluster analysis, etc.
AAPG ACE 2009: Denver Colorado 3
neural networks (a fancy form of multivariate nonneural networks (a fancy form of multivariate non--linear linear regression)regression)
Winland equationWinland equationDeveloped by Amoco in 1970’sDeveloped by Amoco in 1970’sEmpirically derived eqn from a large Pc dataset, Empirically derived eqn from a large Pc dataset, Weyburn field in CanadaWeyburn field in CanadaEqn published by Kolodzie, 1980 (SPE 9382) Eqn published by Kolodzie, 1980 (SPE 9382) Rock types defined by “equiRock types defined by “equi--pore throat size” pore throat size” classes, or “port” sizes, as determined from Pc at classes, or “port” sizes, as determined from Pc at 35% Snw35% Snw
macroports = 2macroports = 2--10 10 μμmmmesoports = 0.5 mesoports = 0.5 –– 2 2 μμmm
AAPG ACE 2009: Denver Colorado 4
pp μμmicroports = 0.1 microports = 0.1 –– 0.5 0.5 μμmmnanoports < 0.1 nanoports < 0.1 μμmm
implicit is pore throat sizes control hydrocarbon implicit is pore throat sizes control hydrocarbon entry and relate to pay qualityentry and relate to pay quality
AAPG ACE Short Course 1: 06.06.2009 198 of 217
Cluff: Advanced Log Models
100
1000
D)
R35
Winland R35 “port” size classesWinland R35 “port” size classes
“macroports”
log R35 = 0.732 + 0.588 log Kair log R35 = 0.732 + 0.588 log Kair –– 0.864 log 0.864 log φ φ ((%)%)
0.001
0.01
0.1
1
10
nken
berg
gas
per
mea
bilit
y (M
D
2
0.5
0.1
0.02
“microports”
“nanoport”
AAPG ACE 2009: Denver Colorado 5
0.000001
0.00001
0.0001
0.0 5.0 10.0 15.0 20.0 25.0
in-situ porosity (%)
in-s
itu K
lin
Note: essentially all Kmv TGSfall into the nanoport rock type
100
1000
(MD
) K/phi
K/K/φ φ ratio isoratio iso--lineslinesK/phi ratio = Ka (mD) / φ (v/v)
0.001
0.01
0.1
1
10
Klin
kenb
erg
gas
perm
eabi
lity
( 50
5
0.5
0.05
0.005
AAPG ACE 2009: Denver Colorado 6
0.000001
0.00001
0.0001
0.0 5.0 10.0 15.0 20.0 25.0
in-situ porosity (%)
in-s
itu
Note: most smpls are at K/f < 0.5and would fall into 3 or 4 classes,but without natural breaks
AAPG ACE Short Course 1: 06.06.2009 199 of 217
Cluff: Advanced Log Models
K/phi methodsK/phi methodsyou can compute K/phi ratio from ambient or inyou can compute K/phi ratio from ambient or in--situ situ core data, or from log K and phicore data, or from log K and phi
divide it into classes that make sense for your areadivide it into classes that make sense for your areano natural divisions in the overall databaseno natural divisions in the overall database
compute Winland R35 from standard eqn or cook compute Winland R35 from standard eqn or cook your own eqn from our dataset!your own eqn from our dataset!
we have NOT done this for youwe have NOT done this for youLOTS of ways to slice and dice this large a databaseLOTS of ways to slice and dice this large a database
basic Winland classes have limited utility in very basic Winland classes have limited utility in very
AAPG ACE 2009: Denver Colorado 7
tight rocks like these, almost everything falls into tight rocks like these, almost everything falls into the “nanoport” size rangethe “nanoport” size range
Rock types from logsRock types from logswe have digital rock types from core we have digital rock types from core description depth shifted to log datadescription depth shifted to log dataseems like we should be able to pull rockseems like we should be able to pull rockseems like we should be able to pull rock seems like we should be able to pull rock types out of the log data by xtypes out of the log data by x--plots or plots or statistical analysisstatistical analysisWell, maybe its not so easy.........Well, maybe its not so easy.........
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Digital core database @ 0.5 ft resolutionDigital core database @ 0.5 ft resolution
GR log plot vs rock #GR log plot vs rock #
GR to rock # correlation is outstanding!GR to rock # correlation is outstanding!
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GR vs Rock numberGR vs Rock number
but over the entire database, therock type classes broadly overlap
Why is that?Why is that?GR logs are not normalizedGR logs are not normalized
it looks good on a single well basis, but gets it looks good on a single well basis, but gets smeared out over multiple cores/wellssmeared out over multiple cores/wellsppuncorrected environmental effectsuncorrected environmental effectsall vendors GR tools are not alikeall vendors GR tools are not alike
the 13000 rock class will always be a the 13000 rock class will always be a problem, by nature of the definition they problem, by nature of the definition they span a broad range of Vshspan a broad range of Vsh
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p gp gonly the higher rock classes (1only the higher rock classes (1stst 2 or 3 2 or 3 digits) are likely to fall out in the best of digits) are likely to fall out in the best of casescases
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ILD vs. GR xplot colored by major rock #ILD vs. GR xplot colored by major rock #
11000 to 12999’s separate cleanly from 15000’s, butthe 13000’s overlap all
NPHINPHI--RHOB by major rock #RHOB by major rock #
again the 15000’s splitcleanly from 12000’s,while 13000’s overlapthe entire field
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DT DT -- RHOB colored by major rock #RHOB colored by major rock #
nothing separates on this,because DT and RHOBare too similar in their lithology response
Rock typing summaryRock typing summarythere is a lot of data here, we didn’t push the there is a lot of data here, we didn’t push the boundaries of what could be done by any boundaries of what could be done by any meansmeansmeansmeansBUT, from our analysis, the results do not BUT, from our analysis, the results do not look promisinglook promisingvery, very difficult to pull out subtle rock type very, very difficult to pull out subtle rock type signatures from a limited suite of open hole signatures from a limited suite of open hole measurements if the base lithology does notmeasurements if the base lithology does not
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measurements if the base lithology does not measurements if the base lithology does not change muchchange muchonly grain size comes out cleanly, but with a only grain size comes out cleanly, but with a broad overlap between classesbroad overlap between classes
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Saturation modelSaturation modelbasic model assumes Archie with TGS basic model assumes Archie with TGS average m, n valuesaverage m, n valuesShaly sand models (e g Dual Water) allShaly sand models (e g Dual Water) allShaly sand models (e.g. Dual Water) all Shaly sand models (e.g. Dual Water) all yield similar results because fm. waters are yield similar results because fm. waters are saline and shales are not highly conductivesaline and shales are not highly conductivecore data suggests m varies as a function of core data suggests m varies as a function of both porosity and average salinityboth porosity and average salinity
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1000
When F and When F and φφ are plotted logare plotted log--loglog
m= 3m= 2
10
100
Fm= 1
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10.01 0.1 1
φlog F = -m log φ
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Salinity dependence of “m”Salinity dependence of “m”
tested plugs with 20K, 40K, 80K, and 200K ppm brinestested plugs with 20K, 40K, 80K, and 200K ppm brinesNearly all cores exhibit some salinity dependenceNearly all cores exhibit some salinity dependence
1.0
2 2
2.3
,
0.3
0.4
0.5
0.6
0.7
0.8
0.9
e C
ondu
ctiv
ity (m
ho/m
)
1.4
1.5
1.6
1.7
1.8
1.9
2.0
2.1
2.2
chie
Cem
enta
tion
Expo
nent
(m, A
=1)
n=335
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0.0
0.1
0.2
0 2 4 6 8 10 12 14 16 18 20 22
Brine Conductivity (mho/m)
Cor
e
1.0
1.1
1.2
1.3
0.01 0.1 1
Brine Resistivity (ohm-m)In
situ
Arc
All data, all salinities All data, all salinities
2.20
2.40
m, a
=1)
1.20
1.40
1.60
1.80
2.00
Cem
enta
iton
Expo
nent
(m
200K
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0.80
1.00
0 2 4 6 8 10 12 14 16 18 20 22
In situ Porosity (%)
Arc
hie
C
80K
40K
20K
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Salinity dependence of “m”Salinity dependence of “m”
m = a log m = a log φ φ + b+ bintercept b drops with intercept b drops with decreasing salinitydecreasing salinity
20K ppm
y = 0.2267Ln(x) + 2.2979
R2 = 0.6619
1.00
1.50
2.00
2.50
Axis Title
Series1
Log. (Series1) decreasing salinitydecreasing salinityslope is ~ constantslope is ~ constant0.00
0.50
0.000 0.050 0.100 0.150 0.200 0.250
insitu porosity (%)
40K ppm
y = 0.2328Ln(x) + 2.409
R2 = 0.6547
0.00
0.50
1.00
1.50
2.00
2.50
3.00
Axis Title
Series1
Log. (Series1)
80K ppm
y = 0.2149Ln(x) + 2.43542
3.00
200K ppm
y = 0.1621Ln(x) + 2.3222
3.00
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0.000 0.050 0.100 0.150 0.200 0.250
insitu porosity (%)
R2 = 0.5132
0.00
0.50
1.00
1.50
2.00
2.50
0.000 0.050 0.100 0.150 0.200 0.250
insitu porosity (%)
Axis Title
Series1
Log. (Series1)
y 0.1621Ln(x) + 2.3222
R2 = 0.3633
0.00
0.50
1.00
1.50
2.00
2.50
0.000 0.050 0.100 0.150 0.200 0.250
insitu porosity (%)
Axis Title
Series1
Log. (Series1)
Simple procedure to compute SwSimple procedure to compute Sw
determine Rw @ Tf conventionallydetermine Rw @ Tf conventionallyPickett plots Pickett plots –– focus on the lower porosity, wetter focus on the lower porosity, wetter sandstonessandstonesproduced watersproduced watersyour best guess.......your best guess.......
convert Rw to 75convert Rw to 75°°F by chart lookup or Arps F by chart lookup or Arps equationequation
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Pickett Plot examplePickett Plot example
Rw = 0.306
pick m at low porosityend, where BVWirr ~ BVW
Williams PA 424Williams PA 424--3434Piceance basinPiceance basinKmv above “top gas”Kmv above “top gas”
Pickett plot Rw 0.306 ohmm @ 160Pickett plot Rw 0.306 ohmm @ 160°°F = 0.7 @ 75F = 0.7 @ 75°°F (9K ppm) F (9K ppm)
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Our new procedureOur new procedurecompute m at 40K ppm from RMA regression:compute m at 40K ppm from RMA regression:
m40k = 0.676 log m40k = 0.676 log φ φ + 1.22+ 1.22e.g. for 10% e.g. for 10% φ : φ : m = 0.676 + 1.22 = 1.896m = 0.676 + 1.22 = 1.896
correct m for salinit effect bcorrect m for salinit effect bcorrect m for salinity effect bycorrect m for salinity effect bym = m40k + ((0.0118 m = m40k + ((0.0118 φφ –– 0.355) * (log Rw + 0.758))0.355) * (log Rw + 0.758))
e.g. for 10% e.g. for 10% φφ, Rw = 0.7 @ 75, Rw = 0.7 @ 75°°FFm = 1.896 + ((0.0118 * 10 m = 1.896 + ((0.0118 * 10 –– 0.355) * (log 0.7 + 0.758))0.355) * (log 0.7 + 0.758))m = 1.896 + (m = 1.896 + (--0.237 * 0.603) = 1.7530.237 * 0.603) = 1.753
cap m at 1.95 (~12% porosity)cap m at 1.95 (~12% porosity)this corrects for variation in both porosity and fmthis corrects for variation in both porosity and fm
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this corrects for variation in both porosity and fm this corrects for variation in both porosity and fm salinity spacesalinity space
Practical impactPractical impactNominally, most of us use an m close to 2, Nominally, most of us use an m close to 2, but usually slightly less, for tight gas sand but usually slightly less, for tight gas sand evaluations (evaluations (e.g.e.g. 1.85, 1.90)1.85, 1.90)Variable m that DECREASES with Variable m that DECREASES with decreasing porosity leads to lower Sw’sdecreasing porosity leads to lower Sw’sTherefore, there is more gas in the tight Therefore, there is more gas in the tight rocks than we thought.rocks than we thought.Above 10% porosity there is very little Above 10% porosity there is very little differencedifference
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differencedifference
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Example: Low porosity, wet zoneExample: Low porosity, wet zone
Moderate porosity, wetModerate porosity, wet
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“High” porosity gas zone“High” porosity gas zone
m is HIGHER than base case, so Sw is higher!
20Kppm example, Natural Buttes20Kppm example, Natural Buttes
improvement in HCPV in shoulders
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30K ppm example, Wamsutter30K ppm example, Wamsutter
no change
Sw summarySw summary335 Kmv samples run at multiple salinities335 Kmv samples run at multiple salinitiesArchie porosity exponent m varies withArchie porosity exponent m varies with
porosityporosity mm ↓ as porosity ↓↓ as porosity ↓porosity porosity m m ↓ as porosity ↓↓ as porosity ↓salinitysalinity m m ↓ as salinity ↓↓ as salinity ↓
behavior is consistent with increasing behavior is consistent with increasing electrical efficiency with decreasing porosity, electrical efficiency with decreasing porosity, whatever the pore scale architecturewhatever the pore scale architecture
very likely that the surface conductivity is highlyvery likely that the surface conductivity is highly
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very likely that the surface conductivity is highly very likely that the surface conductivity is highly connected with low effective mconnected with low effective mporepore--pore throat conductivity is Archie with m pore throat conductivity is Archie with m close to 2close to 2
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Capillary tube model for mCapillary tube model for m
m 1.0
> 1
~2
> 2m = 1
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Herrick & Kennedy, 1993, SPWLA Paper HH
E0 vs porosity, 40K ppm dataE0 vs porosity, 40K ppm data
TableCurve 2D v5.01
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variable m Archie model can be implemented with a variable m Archie model can be implemented with a simple equation relating m to porosity and formation simple equation relating m to porosity and formation water salinitywater salinitym is constant above 12% porosity at 1 95m is constant above 12% porosity at 1 95m is constant above ~12% porosity at 1.95m is constant above ~12% porosity at 1.95lowering m at 5lowering m at 5--12% 12% φ φ increases GIPincreases GIPsee no impact below ~5% porosity see no impact below ~5% porosity
BVWBVWirrirr is typically 3is typically 3--5%5%no longer calculate Sw’s >> 1no longer calculate Sw’s >> 1Sw = 1 at low Sw = 1 at low φφ validates Rwvalidates Rw
much simpler than Dual Water or Wmuch simpler than Dual Water or W--S formulationsS formulations
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much simpler than Dual Water or Wmuch simpler than Dual Water or W--S formulations S formulations for TGS, easier to implement, and it gets you the for TGS, easier to implement, and it gets you the same answersame answer
PermeabilityPermeabilitypermeability has historically been a problem permeability has historically been a problem to estimate from log datato estimate from log datadynamic property that we are trying todynamic property that we are trying todynamic property that we are trying to dynamic property that we are trying to correlate with static propertiescorrelate with static properties
problem is there are no 1:1 functional problem is there are no 1:1 functional relationships between any of the static relationships between any of the static properties, like porosity, and permeability.properties, like porosity, and permeability.
so, we fudge....so, we fudge....
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gg
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Permeability from logsPermeability from logsPorosityPorosity--permeability crosspermeability cross--plotsplots
regression equations developed for each basin regression equations developed for each basin and presented previouslyand presented previouslyp p yp p ywith an accurate log porosity, you can predict K with an accurate log porosity, you can predict K within a SE of about 4X to 5Xwithin a SE of about 4X to 5Xif you add information such as grain size or rock if you add information such as grain size or rock type, you can do even bettertype, you can do even betteronly a fraction of what is possible to do has been only a fraction of what is possible to do has been done but basic eqn’s by basin are presented indone but basic eqn’s by basin are presented in
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done, but basic eqn s by basin are presented in done, but basic eqn s by basin are presented in the project data storethe project data store
10
100
1000
si, m
D)
0 00001
0.0001
0.001
0.01
0.1
1
10
berg
Per
mea
bilit
y (4
,000
ps
Green RiverPiceancePowder RiverUintahWashakieWind River
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0.0000001
0.000001
0.00001
0 2 4 6 8 10 12 14 16 18 20 22 24In situ calc Porosity (%)
Klin
kenb logK=0.3Phi-3.7
logK=0.3Phi-5.7
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Kozeny & TimurKozeny & Timur--type eqn’stype eqn’sKozeny equationKozeny equation
K = A * K = A * φφ33 / S/ S22, , where S = surface area/bulk volumewhere S = surface area/bulk volume
Timur eqn (and its derivatives) are of this general Timur eqn (and its derivatives) are of this general form, but use Swi as a proxy for the internal surface form, but use Swi as a proxy for the internal surface area termarea term
K = 0.136 * K = 0.136 * φφ4.44.4 / Swi/ Swi22 (original Timur eqn)(original Timur eqn)K = 62,500 * K = 62,500 * φφ66 / Swi/ Swi22 (Schlumberger eqn)(Schlumberger eqn)K = A * K = A * φφBB / Swi/ SwiCC (general form)(general form)
We treat A, B, C as local variables and fit parameters by trial We treat A, B, C as local variables and fit parameters by trial
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p yp yand error or using a multivariate solver (e.g. Excel Solver)and error or using a multivariate solver (e.g. Excel Solver)note:note: NMR eqn’s (e.g. Coates & SDR or T2GM) are basically NMR eqn’s (e.g. Coates & SDR or T2GM) are basically the general Timur eqn, but use Swi and the general Timur eqn, but use Swi and φ φ from NMR instead from NMR instead of indirect estimatesof indirect estimates
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Thank you!Thank you!Q&A period (Q&A period (if time availableif time available))
Visit our project website portalsVisit our project website portals::http://www.kgs.ku.edu/mesaverdehttp://www.kgs.ku.edu/mesaverde
ororhttp://www.discoveryhttp://www.discovery--group.com/projects_doe.htmgroup.com/projects_doe.htm
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