Dynamic Characterization of Unconventional Gas Reservoirs: Field Cases
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Transcript of Dynamic Characterization of Unconventional Gas Reservoirs: Field Cases
Neuquén, Argentina
10-12 June 2014
Dynamic Characterization of
Unconventional Gas Reservoirs: Field Cases
SPE Exploration and Development of Unconventional
Reservoirs Conference
Jorge Arévalo, Francisco Castellanos, Jose Pacheco, PEMEX E&P,
Nestor Martínez, CNH, and Francisco Pumar, CBM
Contents
• Introduction and background
• Conceptual model for unconventional gas
reservoirs
• Model modification to consider desorbed gas
• Analyses of field cases
• Final remarks
Shale Total Recoverable Resources (TRR)
In June 2013 the U.S EIA estimated TRR of shale gas at 6,634 tcf across 137
formations in 41 countries.
TRR of shale gas is nearly ten times the 665 tcf estimated for the U.S.
The international some countries in the Middle East, which still have significant
conventional natural gas reserves still in place.
Shale test wells have already been fracture-stimulated in Argentina, Australia,
the United Kingdom, Poland, China, and Mexico.
Some plays like Eagle Ford and Woodford have
transborder continuity
Other plays like Bakken and
Haynesville in the U.S. are
analogous to some Mexican
plays.
NiobraraMarcellus
HeneysvilleBarnet
Antrim
Monterey
Woodford
Bakken
Contents
• Introduction and background
• Conceptual model for unconventional gas
reservoirs
• Model modification to consider desorbed gas
• Analyses of field cases
• Final remarks
The Mexican shale basins are conterminous with
those in the U.S.
In Mexico, five oil provinces with
potential shale oil/gas plays have
been identified: Chihuahua,
Sabinas-Burro Picachos, Burgos,
Tampico-Misantla, and Veracruz.
Haynesville
EUA
Golfo de Mexico
Océano
Pacífico
Sierra Marathon
Ouachita
México
Eagle Ford
Área de Lutitas del Cretácico Superior
Área de Lutitas del Jurásico Superior0 200 400100
KmsEsc.: 1:9,000,000
Chihuahua
Sabinas
Tampico -
Misantla
Burgos
Mz
Veracruz
Burro-
Picachos
Mexico began exploring its shale basins in 2011
0 400 800 Kilómetros200
Chihuahua
Sabinas
Burro-Picachos
Burgos MZ
Tampico-
Misantla
Veracruz
Gas seco
Gas y condensado
Aceite
República Mexicana
Gas y aceite en
estudioIn study
0 400 800 Kilómetros200
Chihuahua
Sabinas
Burro-Picachos
Burgos MZ
Tampico-
Misantla
Veracruz
Gas seco
Gas y condensado
Aceite
República Mexicana
Gas y aceite en
estudio
In study
Some important shale
hydrocarbon basins have
been identified such as La
Pimienta-La Casita and
Eagle Ford formations in
which 545 tcf of TRR were
estimated.
This represents 27% of
North American shale gas
reserves and 7.5% of shale
gas reserves worldwide.
The geological formations of these basins range from low k (< less than 0.1
md) to extremely low k (nano-darcies).
It is necessary to drill horizontal wells with multiple fracking stages to improve
the fluid transmissibility in the formations.
Contents
• Introduction and background
• Conceptual model for unconventional gas
reservoirs
• Model modification to consider desorbed gas
• Analyses of field cases
• Final remarks
Geomechanic
properties
Micro- y nanoporosity
Thermal maturity
Adsorbed gas
adsorbido
COT > 2
9
Conceptual model for unconventional gas reservoirs
Organic material content (OMC) and
adsorbed gas are the governing factors that
have a major influence on the behavior of
unconventional gas reservoirs with low
permeability.
This behavior can be represented through
conceptual models taking the following
concepts into consideration:
1) storage mechanisms
2) transport
3) physical gas adsorption and desorption
effects
Triple porosity storage model for UGRs
Main types of gas storage in UGRs:
a) free gas in the matrix pores
b) adsorbed gas in the matrix surface
A triple-porosity model includes:
free gas and adsorbed gas (it
considers all of the gas that is stored
in formations that contain organic
material)
a combination of double-porosity,
matrix fractures and adsorbed gas in
which free gas is stored in the double-
porosity
Porosity 1 = matrix micro-pores
Porosity 2 = natural fractures
Porosity 3 = gas adsorbed (a “virtual
porosity” in the surface of the formation
particles in the matrix)
Transport mechanism with adsorption process
A diffusion process is present in the primary porosity that can be categorized into three
different mechanisms:
Rock matrix diffusion (molecule-molecule interactions dominate)
Knudsen diffusion (molecule-surface interactions dominate)
Surface diffusion from the adsorbed gas layer
In the primary porosity (rich in
OMC) there are large surface
areas for gas adsorption that
allow for the storage of large
amounts of gas.
The rock pores are extremely
small, which causes the
system permeability of this
primary porosity to be
substantially small, resulting
in no gas or water flow.
𝑞𝑔 =−𝐷𝐴 𝑧𝑠𝑐𝑅𝑇𝑠𝑐𝑝𝑠𝑐
𝑑𝐶
𝑑𝑥
Physical gas adsorption and desorption in UGRs
In UGRs that present OMC, a storage mechanism that is different from conventional gas
reservoirs is the additional phenomenon of adsorption of the gas molecules
to the organic rock walls (adsorption or physisorption, a process in which the adsorbed
molecules conserve their chemical nature)
The Langmuir model
describes the gas
adsorption phenomenon in
solids, which considers that
a gas molecule is adsorbed
in a single place and
doesn’t affect neighboring
molecules.
𝑉𝑎 =𝑉𝐿𝑝
𝑝𝐿 + 𝑝
Langmuir isotherm of a saturated gas reservoir with
adsorbed gas
Desorption or saturation pressure is equal to the undersaturated initial reservoir pressure,
which can be graphically represented by an initial gas content that is on the isotherm curve.
Langmuir isotherms describe the
maximum gas amount in UGRs that
can be stored under certain
conditions with OMC, p and T.
There are different factors that can
decrease the maximum adsorption
capacity of reservoir gas such as
OMC, p, and T.
Langmuir isotherm of an unsaturated gas reservoir
with adsorbed gas
In this case, the desorption or saturation pressure is less than the undersaturated initial
reservoir pressure, represented by an initial gas content that is below the isotherm.
Behavior of the adsorption isotherm upon changing
the Langmuir pressure
Other main parameters to consider during the exploitation of unconventional gas reservoirs
include the Langmuir parameter values since they determine the type of isotherm and in
consequence the desorption pressure, the gas storage volume, and the desorbed gas that
can be produced during exploitation.
Contents
• Introduction and background
• Conceptual model for unconventional gas
reservoirs
• Model modification to consider desorbed gas
• Analyses of field cases
• Final remarks
Model modification to consider desorbed gas
The model for conventional and unconventional reservoirs takes the desorption process
into account as a modified function of pseudotime.
The desorption phenomenon can be taken into consideration in the solutions for the
dry gas diffusion equation, using gas m(p) and modified total system compressibility
(ct*)
𝑚 𝑝 = 2 𝑝
𝜇𝑧𝑑𝑝
𝑝
𝑝0
𝑐𝑡∗ = 𝑐𝑔 1 − 𝑆𝑤 + 𝑐𝑤𝑆𝑤 + 𝑐𝑓 + 𝑐𝑑
𝑐𝑑 =𝑝𝑠𝑐𝑇𝑉𝐿𝑝𝐿𝑧
𝑇𝑠𝑐𝜙𝑝 𝑝 + 𝑝𝐿2=𝜌𝑔𝑠𝑐𝑉𝐿𝑝𝐿
𝜙𝜌 𝑔 𝑝 + 𝑝𝐿2
where
Model modification to consider desorbed gas
To eliminate the nonlinearity of the diffusion equation, the Fraim and Wattenbarger
pseudotime function is used.
Fraim and Wattenbarger studied flow regimes from a production data analysis through
the derivative function for normalized rate.
They defined the term “time match function” to take into account the definition of
modified apparent pseudotime that considers gas desorption effects using (𝑐𝑡∗).
𝑡𝑎∗ 𝑝 = 𝜇𝑖𝑐𝑡
∗𝑖
𝑑𝑡
𝜇𝑐𝑡∗𝑝
𝑡
0
These variables consider instantaneous desorption (assumption for long-term gas
production in some low-permeability, shale, and coalbed methane reservoirs).
Flow regime identification using the derivative
function for normalized gas rate and pseudotime
The modified pseudotime function can be included in the multi-fractured horizontal
well models.
The desorbed gas effect can be considered in the pseudotime function to resolve the
modified diffusion equation for adsorbed gas.
Flow regime Log-Log diagnostic Derivative function slope Type of plot
Bilinear flow
Radial derivative m = 1/4 𝑚 𝑝𝑖 −𝑚 𝑝𝑤𝑓
𝑞𝑔 𝑣𝑠. 𝑙𝑜𝑔 𝑡∗
(1.1)
Bilinear derivative m = 0 𝑚 𝑝𝑖 −𝑚 𝑝𝑤𝑓
𝑞𝑔 𝑣𝑠. 𝑡∗
4
(1.2)
Linear flow
Radial derivative m = 1/2 𝑚 𝑝𝑖 −𝑚 𝑝𝑤𝑓
𝑞𝑔 𝑣𝑠. 𝑙𝑜𝑔 𝑡∗
(1.3)
Linear derivative m = 0 𝑚 𝑝𝑖 −𝑚 𝑝𝑤𝑓
𝑞𝑔 𝑣𝑠. 𝑡∗
(1.4)
Radial flow Radial derivative m = 0 𝑚 𝑝𝑖 −𝑚 𝑝𝑤𝑓
𝑞𝑔 𝑣𝑠. 𝑙𝑜𝑔 𝑡∗
(1.5)
PSS flow.
Radial derivative m = 1 𝑚 𝑝𝑖 −𝑚 𝑝𝑤𝑓
𝑞𝑔 𝑣𝑠. 𝑙𝑜𝑔 𝑡∗
(1.6)
Derivative functions for normalized gas rate for
vertical wells (gas adsorption using pseudotime)
Flow
regime Specialized plot Interpretation equation
Lineara 𝑞𝑔𝑗 − 𝑞𝑞𝑗−1
𝑞𝑔𝑛𝑡𝑎𝑛∗ − 𝑡𝑎(𝑛−1)
∗
𝑛
𝑗=𝑖
𝑣𝑠.𝑚 𝑝𝑖 −𝑚 𝑝𝑤𝑓
𝑞𝑔 𝑘𝑚𝑓𝐴𝑐 =
𝛼 𝑇
𝜇𝑔𝑖 𝜙𝑉𝑐𝑡 𝑓𝑖 + 𝜙𝑉𝑐𝑡 𝑚𝑖
1
𝑚𝐿𝑃𝐶
(2.1)
Bilinearb 𝑞𝑔𝑗 − 𝑞𝑞(𝑗−1)
𝑞𝑔𝑛𝑡𝑛∗ − 𝑡𝑛−1
∗4
𝑛
𝑗=𝑖
𝑣𝑠.𝑚 𝑝𝑖 −𝑚 𝑝𝑤𝑓
𝑞𝑔
𝑘𝑚𝑓
34 𝑤
=984 𝐴𝑐
4 𝑇
𝜇𝑔𝑖 𝜙𝑉𝑐𝑡 𝑓𝑖 + 𝜙𝑉𝑐𝑡 𝑚𝑖4
1
𝑚𝐿𝑃𝐶
(2.2)
Radialc 𝑞𝑔𝑗 − 𝑞𝑞(𝑗−1)
𝑞𝑔𝑛𝑙𝑜𝑔 𝑡𝑎𝑛
∗ − 𝑡𝑎(𝑛−1)∗
𝑛
𝑗=𝑖
𝑣𝑠.𝑚 𝑝𝑖 −𝑚 𝑝𝑤𝑓
𝑞𝑔 𝑘ℎ 𝑚𝑓 =
1640𝑇
𝑚𝐶𝑃𝑅𝑃𝐶
(2.3)
Sphericalb 𝑞𝑔𝑗 − 𝑞𝑞(𝑗−1)
𝑞𝑔𝑛
1
𝑡𝑎𝑛∗ − 𝑡𝑎(𝑛−1)
∗
𝑛
𝑗=𝑖
𝑣𝑠.𝑚 𝑝𝑖 −𝑚 𝑝𝑤𝑓
𝑞𝑔
𝑘𝑓
= 𝜇𝑔𝑖 𝜙𝑉𝑐𝑡 𝑓𝑖 + 𝜙𝑉𝑐𝑡 𝑚𝑖10098
𝑚𝐶𝑅𝑆𝐷𝑃
23
(2.4)
Boundary
dominated
effectsb
𝑞𝑔𝑗 − 𝑞𝑞(𝑗−1)
𝑞𝑔𝑛𝑡𝑎𝑛∗ − 𝑡𝑎(𝑛−1)
∗
𝑛
𝑗=𝑖
𝑣𝑠.𝑚 𝑝𝑖 −𝑚 𝑝𝑤𝑓
𝑞𝑔 𝑘ℎ 𝑓 =
712𝑇
𝑏𝑆𝑆𝑃𝐷𝑃𝑙𝑛2.2458 𝐴
𝐶𝐴𝑟𝑤2+ 2𝑆
(2.5)
Solution:
a. 𝐶𝑜𝑛𝑠𝑡𝑎𝑛𝑡 𝑝𝑤𝑓 , 𝛼 = 201 and constant 𝑞𝑔 , 𝛼 = 128
a. For constant 𝑞𝑔
a. For 𝑝𝑤𝑓 and constant 𝑞𝑔
Derivative functions for normalized gas rate for
horizontal wells (gas adsorption using pseudotime)
Flow regime Derivative
function plot Type of plot Interpretation equation
Early linear flow m = 1/2 𝑚 𝑝𝑖 −𝑚 𝑝𝑤𝑓
𝑞𝑔 𝑣𝑠. 𝑡𝑎
∗ 𝑘𝑓𝐴𝑐𝑤 =1262𝑇
𝜔 𝜙𝜇𝑐𝑡 𝑓+𝑚
1
𝑚1 (3.1)
Bilinear flow m = 1/4 𝑚 𝑝𝑖 −𝑚 𝑝𝑤𝑓
𝑞𝑔 𝑣𝑠. 𝑡𝑎
∗4 𝑘𝑓𝐴𝑐𝑤 =4064𝑇
𝜎𝑘𝑚 𝜙𝜇𝑐𝑡 𝑓+𝑚0.25
1
𝑚2 (3.2)
Linear flow
m = 1/2 𝑚 𝑝𝑖 −𝑚 𝑝𝑤𝑓
𝑞𝑔 𝑣𝑠. 𝑡𝑎
∗ 𝑘𝐴𝑐𝑤 =1262𝑇
𝜙𝜇𝑐𝑡 𝑓+𝑚
1
𝑚3 (3.3)
Transitory linear
flow in the matrix m = 1/2 𝑚 𝑝𝑖 −𝑚 𝑝𝑤𝑓
𝑞𝑔 𝑣𝑠. 𝑡𝑎
∗ 𝑘𝑚𝐴𝑐𝑤 =1262𝑇
𝜙𝜇𝑐𝑡 𝑚
1
𝑚4 (3.4)
Contents
• Introduction and background
• Conceptual model for unconventional gas
reservoirs
• Model modification to consider desorbed gas
• Analyses of field cases
• Final remarks
Extension of the Eagle Ford formation in southern
Texas
Data from a well located in the Eagle Ford shale
formation in southern Texas
Depth, ft. 2,500 - 14,000
Net thickness, ft. 50 - 300
Pressure gradient, psia/ft. 0.4 - 0.8
TOC, % 2 - 9
Gas saturation, %: 83 – 85
Permeability, nd 1 - 800
Data from well A in the Eagle Ford formation in
southern Texas
Well radius, ft. 0.33
Lateral length, ft. 4,000
Thickness, ft. 283
Depth, TVD, ft. 10875
Hydrocarbon porosity (%) (φhc = φef (1-Sw)) 5.76
Reservoir pressure, psia 8,350
Temperature, °R 745
Gas compressibility, 10-5 psia-1 6
Gas viscosity, cp 0.03334
Number of effective fractures 20
Stimulated Reservoir Volume (SRV), MMft3 169
Gas rate, cumulative production and pwf history for
well A
Diagnostic plots of normalized Δm(p)/qg vs. t and
Δm(p)/qg vs. ta for well A
Specialized plots to characterize bilinear flow:
Δm(p)/qg vs. t1/4 and Δm(p)/qg vs. ta1/4
Specialized plots to characterize linear flow of
Δm(p)/qg vs. t1/2 and Δm(p)/qg vs. ta1/2
Adsorbed gas values of shale formations in the
U.S. (Andrews, 2013)
Rock parameters to estimate gas desorption in
well A (Xu, 2012)
VL = 720 scf/ton ρr = 2.5 gr/cm3
PL = 550 SRV = 17 MM ft.
T = 285 °F mr = 12 MM tons
φ = 0.0576
Matrix and fracture permeabilities for well A both
without and with gas desorption
Permeability Without gas
desorption
With gas
desorption
matrix (𝑘𝑚): 2.15 × 10−4 𝑚𝑑 1.28 × 10−5 𝑚𝑑
fracture (𝑘𝑓): 1.61 × 10−2 𝑚𝑑 2.62 × 10−2 𝑚𝑑
𝑶𝑮𝑰𝑷 =𝟐𝟎𝟎. 𝟔 𝑻 𝑺𝒈𝒊
𝝁𝒄𝒕𝑩𝒈 𝒊
∙𝒕𝒍𝒓𝒎𝟑+𝒑𝒊𝑽𝑳𝒑𝒊 + 𝒑𝑳
𝒎𝒓
OGIP = 3.15 Bscf (without gas adsorption) OGIP = 4.06 Bscf (with gas adsorption)
Mechanical state of well B
Data from well B in the Eagle Ford formation in
northern Mexico
Well radius, ft. 0.375
Lateral length, ft. 1837
Thickness, ft. 492
Depth, TVD, ft. 2530
Hydrocarbon porosity (%) (φhc = φef (1-Sw)) 6.0
Reservoir pressure, psia 5,100
Temperature, °R 667
Gas compressibility, 10-4 psia-1 1.3
Gas viscosity, cp 0.0239
Number of effective fractures 8
Stimulated Reservoir Volume (SRV) (MMft3) 445
3936 ft
646 ft
Drainage volume of well B
𝑳 =𝑯𝒐𝒓𝒊𝒛𝒐𝒏𝒕𝒂𝒍 𝒘𝒆𝒍𝒍 𝒍𝒆𝒏𝒈𝒕𝒉
𝑬𝒇𝒇𝒆𝒄𝒕𝒊𝒗𝒆 𝒇𝒓𝒂𝒄𝒕𝒖𝒓𝒆𝒔=𝟏𝟖𝟑𝟕
𝟖= 𝟐𝟑𝟎 𝒇𝒕
Cross-sectional area to flow is:
Acw = 2xeh = 2 x 1837 x 492 = 1,807,411 ft2
The matrix–natural fracture area between the blocks formed by the hydraulic fractures is
Acm = 2 x 2yehL = 2 x 2 x 246 x 1837 x 492 x 8 = 3,873,024 ft2
t (days)
Pressure and gas rate history of well B
Diagnostic plots of Δm(p)/qg vs. ta for well B
Specialized plots to characterize linear flow of
Δm(p)/qg vs. ta1/2
Parameters calculation for well B
𝒄𝒕∗ = 𝒄𝒈 𝟏 − 𝑺𝒘 + 𝒄𝒘𝑺𝒘 + 𝒄𝒇 + 𝒄𝒅
𝒄𝒅 =𝒑𝒔𝒄𝑻𝑽𝑳𝒑𝑳𝒛
𝑻𝒔𝒄𝝓𝒑 𝒑 + 𝒑𝑳𝟐 =
𝝆𝒈𝒔𝒄𝑽𝑳𝒑𝑳
𝝓𝝆 𝒈 𝒑 + 𝒑𝑳𝟐
where
Using the m3 slope equation, matrix permeability (km) was estimated,
assuming that the fracture porosity is negligible compared with matrix
porosity,
𝝓𝝁𝒄𝒕 𝒇+𝒎 = 𝝓𝝁𝒄𝒕 𝒎
The reservoir is saturated in its desorption pressure (the desorption began
with reservoir pressure)
and Rock compressibility (cf) is negligible in comparison with gas
compressibility
𝒄𝒕∗ = cg + cd
History matches of qg vs. ta1/2 and Δm(p)/qg vs. ta
1/2
for linear flow
Rock parameters to estimate gas desorption in
well B (Xu, 2012)
VL = 60 scf/ton ρr = 2.8 gr/cm3
PL = 250 SRV = 446 MM ft.3
T = 207 °F mr = 35 MM tons
φ = 0.06
km = 3.85x10-6 md
OGIP = 1.7 Bscf (without gas adsorption)
Final remarks
In UGRs with high OMC, it is important to consider the gas that is
adsorbed in the formation since this can significantly alter the OGIP and
the estimated parameters such as primary and secondary
permeabilities.
Applying Langmuir’s isotherm model, it is possible to take into
consideration and predict the behavior of adsorbed and desorbed gas in
UGRs that contain organic material. This is significant since, once gas
desorption pressure is reached, there is an additional production
mechanism in the reservoir.
Pseudotime developed for the characterization of conventional gas
reservoirs can be effectively applied to UGRs, taking into account
instantaneous gas desorption in the total compressibility of the system
and depending on the average reservoir pressure.
Final remarks
Through the well data analysis, it was possible to confirm the
applicability of the modified models to analyze production and
characterization data from UGRs, taking into consideration the
phenomenon of adsorption using Langmuir’s isotherm and modified
pseudotime at any moment during well production.
For the characterization models used in this work, the assumption was
made that the desorbed gas is instantaneous, obtaining good results.
However, it is important to bear in mind that desorption is not
instantaneous in all reservoirs. As such, it is recommended to adjust the
models taking into account real gas desorption time.
Langmuir isotherms only consider the monocomponent fluid, methane
gas. For multicomponent blends, it is recommendable to utilize the
multicomponent Langmuir isotherm or to study how to adjust a cubic
state equation, allowing us to better characterize the desorption
phenomenon.
THANKS
QUESTIONS?