Making Sense of Shale Gas Resource Estimates · 2012 Marcellus Summit () | October 10–12, 2012...
Transcript of Making Sense of Shale Gas Resource Estimates · 2012 Marcellus Summit () | October 10–12, 2012...
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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Presentation at 2012 Marcellus Summit 11 October 2012 — State College, PA
Tom BLASINGAMEPetroleum Engineering — Texas A&M University
College Station, TX 77843-3116 (USA)+1.979.255.8808 — [email protected]
Making Senseof Shale Gas Resource Estimates
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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Tom BLASINGAMEDepartment of Petroleum Engineering
Texas A&M UniversityCollege Station, TX 77843-3116 (USA)
+1.979.845.2292 — [email protected]
Making Senseof Shale Gas Resource Estimates
Brief Biography — Tom Blasingame
Presentation at 2012 Marcellus Summit 11 October 2012 — State College, PA
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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Short Bio: Blasingame●Role:— Professor, Texas A&M U.— Holder of the Robert L. Whiting Professorship — B.S., M.S., and Ph.D. degrees from Texas A&M U. (PETE)
●Counts: (October 2012):— 49 M.S. (thesis) Graduates and 30 M.Eng. (report, non-thesis) Graduates — 10 Ph.D. Graduates— Over 100 Technical Articles
●Honors:— Distinguished Member of the Society of Petroleum Engineers (2000)— SPE Distinguished Service Award (2005)— SPE Distinguished Lecturer (2005-2006)— SPE Uren Award (2006)— SPE Lucas Medal (2012)
●Current Research Activities:— Nano-Scale Flow Phenomena— Reservoir Engineering of Near-Critical, "Liquids-Rich" Shale Systems— Evaluation of Well Performance Data for Shale/Liquids-Rich Systems— Numerical Modeling of Ultra-Low Permeability Reservoir Systems
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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Tom BLASINGAMEDepartment of Petroleum Engineering
Texas A&M UniversityCollege Station, TX 77843-3116 (USA)
+1.979.845.2292 — [email protected]
Making Senseof Shale Gas Resource Estimates
Orientation
Presentation at 2012 Marcellus Summit 11 October 2012 — State College, PA
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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Orientation: Reserves●Facts of life…■ Analogs (... need to understand uncertainty (very high))■ EUR (... minimum of 12-18 months for high confidence)■ IP (... may be uncorrelated with EUR)■ Early Productivity (... poor wells don't get better)■ Time-Rate Analysis (... not representative? (chaotic operations))
●Comments on recovery…■ Early EUR? (... can this be meaningful?)■ EUR = f(t)? (... how do we incorporate this?)■ Well Spacing? (... is this really the holy grail?)
●Mechanisms to estimate recovery…■ Time-Rate Analyses (... may not be sufficient)■ Time-Rate-Pressure Analyses (... requires a reservoir model)
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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●Never-Ending Arguments…■ SRV (... what is it, really?)■ Desorption (... significance? timing? relevance?)■ Stimulation Fluids (... where does it go? does it matter?)■ Microseismic (... crystal ball, roulette wheel, or roadmap?)■ Pressure-Dependent Whatever (... so what?)■ Natural Fractures (... if/when/why/what?)■ Dual Porosity/Dual Permeability (... what about the physics?)■ Well Placement/Effect of Layering (... when does it matter?)
●Things that SHOULD help…■ Production Logs (... but just a snapshot in time)■ Optimal Proppant Design/Placement (... obvious, but)■ Stimulation Stages/Perforation Clusters (... geology + logs)
●Things that DEFINITELY WOULD help…■ Measured pwf (... yes, this is my favorite song)■ Downhole Fluid Sampling (... sooner or later)■ Horizontal Core (... why not?)
Orientation: "Everybody Has An Opinion"
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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Making Senseof Shale Gas Resource Estimates
How Small is Small?(nano-scale pores)
Tom BLASINGAMEDepartment of Petroleum Engineering
Texas A&M UniversityCollege Station, TX 77843-3116 (USA)
+1.979.845.2292 — [email protected]
Presentation at 2012 Marcellus Summit 11 October 2012 — State College, PA
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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Pore-Scale: Nelson Pore/Molecule Size ChartQuestion(s):●How small are pores in shale gas? Note
that the size of the pores is on the order of 5-10 times the size of the fluid molecule.
AAPG Bulletin, v. 93, no. 3 (March 2009)Pore-throat Sizes In Sandstones, Tight Sandstones, and ShalesP.H. Nelson, USGS
Perspective:●The concept of pores and
pore throats begins to break down at these scales.
●The flow path can be as small as 10-20 molecular diameters (or less).
Issues:●How do the fluids move?— Darcy flow?— Dispersion (gases)?— Knudsen flow?
●How are the fluids stored?— In the organic matter?— Adsorbed?— Another mechanism?
← Each green line is x10 SMALLER scale.
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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Pore-Scale: Shale Pore Space (Barnett Example)Question(s):●Where is/are the gas/liquid stored? There
is porosity, often in the organic materials.●Why is the phase behavior of many
shales "near critical"? Nanopores?
J. Sedimentary Research, v. 79/12 (2009)Morphology, Genesis, and Distribution of Nanometer-scale Pores in Siliceous Mudstones of the Mississippian Barnett ShaleLoucks, R.G., R.M. Reed, S.C. Ruppel, and D.M. Jarvie
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
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a. Gas Slippage — Kundt, A. and Warburg, E.: "Über Reibung und Wärmeleitung verdünnter Gase, " Poggendorfs Annalen der Physik und Che-mie (1875), 155, 337.
Pore-Scale: Petrophysics/Permeability
c. Microflow model and correlation, "fully implicit" formulation.b. Knudsen "microflow" model (Modified from Karniadakis and Beskok, 2002).
SPE 107954Improved Permeability-Prediction Relations for in Low Permeability SandsF.A. Florence, Occidental Petroleum Corp., J.A. Rushing, Anadarko Petroleum Corp., K.E. Newsham, Apache Corp., and T.A. Blasingame, Texas A&M U.
vx
vy
Gas Flow
1 /11
41 1 1 4tan151281
21
2121
0
0
4.0
01-
2
aa
m
aa
m
aa
m
a
kp
ak
pak
pa
kk
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
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Tom BLASINGAMEDepartment of Petroleum Engineering
Texas A&M UniversityCollege Station, TX 77843-3116 (USA)
+1.979.845.2292 — [email protected]
Making Senseof Shale Gas Resource Estimates
Schematic Time-Rate Analysis
Presentation at 2012 Marcellus Summit 11 October 2012 — State College, PA
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
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Time-Rate: Schematic Production Performance Plot
●Discussion: Schematic Production Performance Plot■ The schematic represents the most common approach to EUR.■ Used CAREFULLY, this should be valid.
Loga
rithm
of R
ate
Production Time
Hyperbolic Rate
Exponential Rate
"Switch Point"from Hyperbolicto Exponential Economic Limit (in rate — qlimit)
= Estimated Ultimate Recovery (EUR)[The area under the hybrid (hyperbolic-exponential rate curves]
Economic Limit (in time — tlimit)
(tlimit)
(qlimit)
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
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Time-Rate: Schematic — Multi-Fracture Horizontal Well"Plug and Perf" System: Each STAGE has a certain number of perforation "clusters" (typically 4)
Cluster Cluster Cluster Cluster1 2 3 4
Stage 2
Cluster Cluster Cluster Cluster1 2 3 4
Stage n
Cluster Cluster Cluster Cluster1 2 3 4
Stage 1
"FracPoint" (and other such) Systems: Each STAGE is isolated and stimulated
Stage 1 Stage 2 Stage n
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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1:4 Slope (low FcD)
1:2 Slope (high FcD)
1:1 SlopeDepletion
(SRV?)
Compound Linear Flow Regime
Formation Linear Flow Regime
TransitionRegime
Bilinear FlowRegime
EllipticalFlow Regime
Logarithm of Production Time
Loga
rithm
of P
rodu
ctio
n R
ate
])(1[/)( )/1( bii tbDqtq
Early-Time Regimes are HYPERBOLIC?
Discussion:●1:2 Slope → b=2 (HIGH fracture conductivity) .●1:4 Slope → b=4 (LOW fracture conductivity).●This is a schematic, it overly simplifies the system.
][1/ )( tatq LFLF
Time-Rate: Flow Regimes — Multi-Fracture Horizontal Well
][1/ )( 4 tatq BLFBLF
For Shales: | days | weeks | months | years | decades | … |
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
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Tom BLASINGAMEDepartment of Petroleum Engineering
Texas A&M UniversityCollege Station, TX 77843-3116 (USA)
+1.979.845.2292 — [email protected]
Making Senseof Shale Gas Resource Estimates
Conventional Time-Rate Analysis
Presentation at 2012 Marcellus Summit 11 October 2012 — State College, PA
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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Modified Hyperbolic Rate Relation:
Decline Function: D(t)
Hyperbolic Function: b(t)
Function: (t)
Time-Rate: Modified Hyperbolic Rate Relation
)( ]exp[
)( )1()(
limexp,
/1hyp,
t*ttDq
t*ttbD
qtq
i
bi
i
dtdq
qtD 1)(
constant )(
1 )(
tDdtdtb
Discussion:●qDb functions are DIAGNOSTIC.●D(t), b(t), and (t) are evaluated continuously (at all points).●This shale gas case exhibits b=2 behavior → q = a√t (Linear Flow).●Appears to be "hyperbolic," but this is just the Linear Flow portion.
)( 1)( tDtdtdq
qtt
Logarithm of Production Time
Loga
rithm
of P
rodu
ctio
n R
ate,
q(t)
Loga
rithm
ofD
(t)an
d b(
t)
q(t)
D(t)
b(t)
1:2 slope
b(t) ≈ 2
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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)1(ˆ1)( nitDnD
dtdq
qtD
●Observed Behavior of Decline Parameter (D): (from data)
●Flowrate Solution: (derived from D(t) behavior)
●Literature:■Kohlrausch (1854).■Phillips (1996).■Kisslinger (1993)■Decays in random, disordered,
chaotic, heterogeneous systems (e.g., relaxation, aftershock decay rates, etc.).
])/( exp[ˆ)( ni tqtq
Valkó (2009)
Jones (1942) and Arps (1945)
)1( 100
exp )(1
mtD
qtqm
oo
] ˆ exp[ ˆ)( nii tDtDqtq
Time-Rate: Power-law Exponential Relation
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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/28Discussion:
●qDb functions are DIAGNOSTIC.●Power-law exponential relation is derived from:●No direct analog to hyperbolic case.●This is a "tight gas" reservoir case.
PLE Rate Relation:
Decline Function: D(t)
Hyperbolic Function: b(t)
b Function: b(t)
Time-Rate: Power-Law Exponential Rate Relation
]ˆexp[ˆ)( nii tDtDqtq
)1(ˆ
1)(
nitDnD
dtdq
qtD
nn
i
i ttDDn
nDn
tDdtdtb
2)1( ] ˆ[
)1(ˆ
)(1 )(
)1(ˆ nitDnD
)( 1)( tDtdtdq
qtt
Logarithm of Production TimeLo
garit
hm o
fD(t)
and
b(t)
q(t)
D(t)
b(t)
Loga
rithm
of P
rodu
ctio
n R
ate,
q(t)
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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Presentation at Reserves RoundtableThe Woodlands, TX (USA) — 05 September 2012
Considerations for EUR in Unconventional ReservoirsTom Blasingame — Texas A&M University (05 September 2012)
Discussion:●EUR is computed at each "time step" (cumulative or incremental).●EUR estimated for each model.●EUR comparison plots probably min/max trends.
d. CEUR master summary plot (all results).
Time-Rate: Continuous EUR
a. Continuous EUR (CEUR) process plots.
b. CEUR hyperbolic, PLE, and q-Gp summary plots.
c. CEUR governing equations.
])(1[/)( )/1( bigi tbDqtgq
]ˆexp[ˆ)( nigi tDtDqtgq
]/[ )( igi DqGpGiDgiqtgq
[hyperbolic]
[PLE]
[qg(t) vs. Gp(t)]
From: SPE 132352 (2009) Continuous Estimation of Ultimate Recovery, S. Currie, D. Ilk, and T. Blasingame, Texas A&M U.
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
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Tom BLASINGAMEDepartment of Petroleum Engineering
Texas A&M UniversityCollege Station, TX 77843-3116 (USA)
+1.979.845.2292 — [email protected]
Making Senseof Shale Gas Resource Estimates
Emerging Ideas/Tools forTime-Rate Analysis
Presentation at 2012 Marcellus Summit 11 October 2012 — State College, PA
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
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●Time-Rate Analysis: Base Definitions (Arps, 1945)■Loss Ratio:
■Loss Ratio Derivative:
●Approach:■D(t) and b(t) provide diagnostic matching functions (qDb plots).■Diagnostic relations can be used to derive empirical models.
dtdqq
tD /)(1
dtdqq
dtd
tDdtdtb
/)(1)(
Governing Relations: Time-Rate Definitions (slight repeat)
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
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●Rate Relations: (q = Rate; Q = cumulative)■Power-Law Exponential/Stretched Exponential: (2008)
■Duong Relation: (2011)
■Logistic Growth Model (LGM) Relation: (2011)
]ˆexp[ˆ)( nii tDtDqtq
Time-Rate Analysis: Inventory of Relations
)1(1
exp)( 1 mmi t
matqtq
mat
tQtq)()(
2
)1(
][)( n
n
ta
taKntq
n
n
ta
tKtQ )(
]ˆ)([ 1
DtDntD ni
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
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Time-Rate Analysis: PLE, Duong, and LGM Models
●General:■ 50 nd case.■ "qDb" plot■ All models shown.
●PLE Model:■ Very good match.■ Indistinguishable.
●Doung Model:■ Very good match.■ Indistinguishable.
●LGM Model:■ Very good match.■ Indistinguishable.
50 nd Simulation Case
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
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Time-Rate Analysis: PLE, Duong, and LGM Models
●General:■ 800 nd case.■ "qDb" plot■ All models shown.
●PLE Model:■ Very good match.■ Matches BDF regime.
●Doung Model:■ Very good match.■ Does NOT match BDF.
●LGM Model:■ Very good match.■ Fair match of BDF.
800 nd Simulation Case
BDF = Boundary-Dominated Flow(SRV Regime)
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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Tom BLASINGAMEDepartment of Petroleum Engineering
Texas A&M UniversityCollege Station, TX 77843-3116 (USA)
+1.979.845.2292 — [email protected]
Making Senseof Shale Gas Resource Estimates
Summary
Presentation at 2012 Marcellus Summit 11 October 2012 — State College, PA
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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Summary: ●Shale Gas/Shale Liquids Resources■ In-place resources are well understood.■ Flow mechanisms are NOT well understood.■ These systems MUST BE STIMULATED to yield economic rates.
●Practical Issues on Reserves■ Use sufficient data to make appropriate estimates (18-24 months).■ The equation does not really matter — use the DIAGNOSTICS!■ Reserves estimation must become more diagnostic (less analogs).
●Take-Aways■ Reserves are defined by stimulation, geology, and fluid type.■ There are no clear alternatives to the multi-fracture horizontal well.■ You must use diagnostics (not statistics) to define reserves.
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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Tom BLASINGAMEDepartment of Petroleum Engineering
Texas A&M UniversityCollege Station, TX 77843-3116 (USA)
+1.979.845.2292 — [email protected]
Making Senseof Shale Gas Resource Estimates
Practical Aspects
Presentation at 2012 Marcellus Summit 11 October 2012 — State College, PA
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
Making Sense of Shale Gas Resource EstimatesT.A. Blasingame | (11 Oct 2012) Sl
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Practical Aspects: Stimulation
Discussion:●Maximizing SRV (Stimulated Reservoir Volume)
■Build Complexity →Slickwater■Build Conductivity →Hybrid/Gel Systems
● Future Stimulation Challenges:■Can we "rubblize" the reservoir?■Can we "pulverize" the reservoir?■Can we do this with little or no water?
"You only produce from what you frac …"Anonymous
Individual Fractures fromIndividual Perforation Clusters
Complex Fractures fromIndividual Perforation Clusters Project Rulison (1971)
Stimulation using Atomic Weapons
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
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Tom BLASINGAMEDepartment of Petroleum Engineering
Texas A&M UniversityCollege Station, TX 77843-3116 (USA)
+1.979.845.2292 — [email protected]
Making Senseof Shale Gas Resource Estimates
Backup
Presentation at 2012 Marcellus Summit 11 October 2012 — State College, PA
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
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●Modified Duong qg(t ) Relation:
●Modified Duong D(t) Relation:
● Comments:■Model very similar to PLE.■Matches PSS flow data.■Is Duong model "necessary?"■Other improvements?
Time-Rate Analysis: Modified Duong Model 1
tDtm
atqtq DNGmm
g ]1[1
exp)( 11
mDNG at
tmDtD )(
2012 Marcellus Summit (www.MarcellusSummit.com) | October 10–12, 2012The Penn Stater | State College, Pennsylvania
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Time-Rate Analysis: Comparison of Modified Duong Models
Discussion:●Doung (base) Model:■ Transient flow only!■ Liberal EUR possible.
●Modified Doung Model 1:■ Almost same as PLE.■ Conservative EUR.
●Modified Doung Model 2:■ Similar to PLE (ripple).■ Conservative EUR.
Note early-time asymptotic functions.