Physics of Fluid Flow and Transport in Unconventional Reservoir Rocks E-Book
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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Physics of Fluid Flow and Transport in Unconventional Reservoir Rocks Understanding and predicting fluid flow in hydrocarbon shale and other non-conventional reservoir rocks Oil and natural gas reservoirs found in shale and other tight and ultra-tight porous rocks have become increasingly important sources of energy in both North America and East Asia. As a result, extensive research in recent decades has focused on the mechanisms of fluid transfer within these reservoirs, which have complex pore networks at multiple scales. Continued research into these important energy sources requires detailed knowledge of the emerging theoretical and computational developments in this field. Following a multidisciplinary approach that combines engineering, geosciences and rock physics, Physics of Fluid Flow and Transport in Unconventional Reservoir Rocks provides both academic and industrial readers with a thorough grounding in this cutting-edge area of rock geology, combining an explanation of the underlying theories and models with practical applications in the field. Readers will also find: * An introduction to the digital modeling of rocks * Detailed treatment of digital rock physics, including decline curve analysis and non-Darcy flow * Solutions for difficult-to-acquire measurements of key petrophysical characteristics such as shale wettability, effective permeability, stress sensitivity, and sweet spots Physics of Fluid Flow and Transport in Unconventional Reservoir Rocks is a fundamental resource for academic and industrial researchers in hydrocarbon exploration, fluid flow, and rock physics, as well as professionals in related fields.
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Table of Contents
Cover
Title Page
Copyright Page
Dedication Page
List of Contributors
Preface
Introduction
1 Unconventional Reservoirs
1.1 Background
1.2 Advances
1.3 Challenges
1.4 Concluding Remarks
References
Part I: Pore‐Scale Characterizations
2 Pore‐Scale Simulations and Digital Rock Physics
2.1 Introduction
2.2 Physics of Pore‐Scale Fluid Flow in Unconventional Rocks
2.3 Theory of Pore‐Scale Simulation Methods
2.4 Applications
2.5 Conclusion
References
3 Digital Rock Modeling
3.1 Introduction
3.2 Single‐Scale Modeling of Digital Rocks
3.3 Multiscale Modeling of Digital Rocks
3.4 Conclusions and Future Perspectives
Acknowledgments
References
4 Scale Dependence of Permeability and Formation Factor
4.1 Introduction
4.2 Theory
4.3 Pore‐network Simulations
4.4 Results and Discussion
4.5 Limitations
4.6 Conclusion
Acknowledgment
References
Part II: Core‐Scale Heterogeneity
5 Modeling Gas Permeability in Unconventional Reservoir Rocks
5.1 Introduction
5.2 Effective‐Medium Theory
5.3 Single‐Phase Gas Permeability
5.4 Gas Relative Permeability
5.5 Conclusions
Acknowledgment
References
6 NMR and Its Applications in Tight Unconventional Reservoir Rocks
6.1 Introduction
6.2 Basic NMR Physics
6.3 NMR Logging for Unconventional Source Rock Reservoirs
6.4 NMR Measurement of Long Whole Core
6.5 NMR Measurement on Drill Cuttings
6.6 Conclusions
References
7 Tight Rock Permeability Measurement in Laboratory
7.1 Introduction
7.2 Commonly Used Laboratory Methods
7.3 Simultaneous Measurement of Fracture and Matrix Permeabilities from Fractured Core Samples
7.4 Direct Measurement of Permeability‐Pore Pressure Function
7.5 Summary and Conclusions
References
8 Stress‐Dependent Matrix Permeability in Unconventional Reservoir Rocks
8.1 Introduction
8.2 Sample Descriptions
8.3 Permeability Test Program
8.4 Permeability Behavior with Confining Stress Cycling
8.5 Matrix Permeability Behavior
8.6 Concluding Remarks
Acknowledgments
References
9 Assessment of Shale Wettability from Spontaneous Imbibition Experiments
9.1 Introduction
9.2 Spontaneous Imbibition Theory
9.3 Samples and Analytical Methods
9.4 Results and Discussion
9.5 Conclusions
Acknowledgments
References
10 Permeability Enhancement in Shale Induced by Desorption
10.1 Introduction
10.2 Adsorption in Shales
10.3 Permeability Models for Sorptive Media
10.4 Competing Processes during Permeability Evolution
10.5 Desorption Processes Yielding Permeability Enhancement
10.6 Permeability Enhancement Due to Nitrogen Flooding
10.7 Discussion
10.8 Conclusion
References
11 Multiscale Experimental Study on Interactions Between Imbibed Stimulation Fluids and Tight Carbonate Source Rocks
11.1 Introduction
11.2 Fluid Uptake Pathways
11.3 Mechanical Property Change After Fluid Exposure
11.4 Morphology and Minerology Changes After Fluid Exposure
11.5 Flow Property Change After Fluid Exposure
11.6 Conclusions
References
Part III: Large‐Scale Petrophysics
12 Effective Permeability in Fractured Reservoirs
12.1 Introduction
12.2 Objectives
12.3 Percolation‐Based Effective‐Medium Theory
12.4 Comparison with Simulations
12.5 Conclusion
Acknowledgment
References
13 Modeling of Fluid Flow in Complex Fracture Networks for Shale Reservoirs
13.1 Shale Reservoirs with Complex Fracture Networks
13.2 Complex Fracture Reservoir Simulation
13.3 Embedded Discrete Fracture Model
13.4 EDFM Verification
13.5 Well Performance Study – Base Case
13.6 Effect of Natural Fracture Connectivity on Well Performance
13.7 Effect of Natural Fracture Conductivity on Well Performance
13.8 Conclusions
References
14 A Closed‐Form Relationship for Production Rate in Stress‐Sensitive Unconventional Reservoirs
14.1 Introduction
14.2 Production Rate as a Function of Time in the Linear Flow Regime Under the Constant Pressure Drawdown Condition
14.3 An Approximate Relationship Between Parameter
A
and Stress‐Dependent Permeability
14.4 Evaluation of the Relationship Between Parameter
A
and Stress‐Dependent Permeability
14.5 Equivalent State Approximation for the Variable Pressure Drawdown Conditions
14.6 Discussions
14.7 Concluding Remarks
Appendix 14.A Derivation of Eq. (14.22) with Integration by Parts
References
15 Sweet Spot Identification in Unconventional Shale Reservoirs
15.1 Introduction
15.2 Reservoir Characterization
15.3 Sweet Spot Identification
15.4 Discussion
15.5 Conclusion
References
Index
End User License Agreement
List of Tables
Chapter 2
Table 2.1 Parameters of the discrete velocity models are shown in Figure 2....
Chapter 4
Table 4.1 Salient characteristics of the 12 pore networks constructed in th...
Chapter 5
Table 5.1 Various studies as well as mechanisms proposed in the literature ...
Table 5.2 Salient properties of experiments, pore‐network model, and lattic...
Table 5.3 Salient properties of the eight cases used in this study.
Chapter 7
Table 7.1 Comparison of the matrix permeability results for a pyrophyllite ...
Chapter 9
Table 9.1 Physical properties of related fluids.
Table 9.2 Properties and dimensions of Barnett samples used in SI experimen...
Table 9.3 Sample ID and dimension of Longmaxi and Yanchang Formation Shales...
Table 9.4 Sample ID and dimension of Ziliujing Formation Shale used in SI e...
Table 9.5 Mineralogical composition of Barnett samples from XRD analyses.
Table 9.6 Water imbibition slope for Barnett samples.
Table 9.7 TOC and mineralogy of Longmaxi and Yanchang Formation Shale sampl...
Table 9.8 MIP porosity, BET surface area, and average pore diameter, as wel...
Table 9.9 Water imbibition slopes of all transverse (T) samples of Longmaxi...
Table 9.10 SI results of Longmaxi and Yanchang Formation Shale samples.
Table 9.11 TOC and mineralogy (wt.%) of Ziliujing Formation Shale samples u...
Table 9.12 Pore structure information of Ziliujing Formation Shale samples ...
Table 9.13 Spontaneous imbibition results of Ziliujing Formation Shale samp...
Table 9.14 Thermal maturity and wettability inferred from SI experiments fo...
Chapter 11
Table 11.1 Summary of the microindentation test for outcrop eagle ford samp...
Table 11.2 Water analysis of the representative seawater sample from one mi...
Table 11.3 Aperture size change due to 2 wt% KCl fluid treatment in Figure ...
Table 11.4 Aperture size Change due to 0.015 wt% friction reducer (in 2 wt%...
Table 11.5 Quantification of cations dissolution in treatment fluids.
Table 11.6 Absolute permeability measurement under different effect stress ...
Chapter 13
Table 13.1 Key reservoir inputs of all studied models in our work.
Table 13.2 Key fracture parameters of the EDFM verification model.
Table 13.3 The number of grid blocks information and simulation time for ea...
Chapter 14
Table 14.1 The relative error
a
determined for the parameter
A
estimated by ...
Table 14.2 The relative error
a
determined for the parameter
A
estimated by ...
Chapter 15
Table 15.1 Guidelines for sweet spot identification with OQ, RQ, and MQ....
Table 15.2 Parameters comparison of shale gas of different areas in the Sic...
Table 15.3 Identified sweet spots and optimum fracture fluid (modified from...
List of Illustrations
Chapter 1
Figure 1.1 World total energy consumption between 1994 and 2019.
Figure 1.2 Shares of global primary energy between 1994 and 2019 (BP Statist...
Figure 1.3 World shale gas resources (top) and shale gas and oil plays in th...
Figure 1.4 (a) SEM image of contiguous spongy‐textured organic matter pore n...
Figure 1.5 Monthly production for two oil and two gas reservoirs
Chapter 2
Figure 2.1 Schematic of the Knudsen Layer near a solid wall. The Navier–Stok...
Figure 2.2 A gas molecule confined by solid walls in a porous medium. The ga...
Figure 2.3 The Langmuir gas adsorption isotherm curve.
Figure 2.4 Discrete velocity models; (a) D2Q9, (b) D3Q19, (c) D2Q21, and (d)...
Figure 2.5 Schematic of gas–solid interactions considering surface diffusion...
Figure 2.6 Porous structure generated with QSGS. Lattices in black are the s...
Figure 2.7 Simulated apparent permeability and corresponding velocity fields...
Figure 2.8 Methane adsorption isotherms modeled with GCMC and matching resul...
Figure 2.9 Schematic of the porous medium in lattice unit. Black means solid...
Figure 2.10 Gas density distributions at different pressures. (a–d) Gas dens...
Figure 2.11 The densities of different types of gas at different pressures. ...
Figure 2.12 Normalized velocity at different surface coverage and surface di...
Figure 2.13 Schematic of porous structure.
Figure 2.14 Distribution of dimensionless velocity in y direction across sli...
Figure 2.15 Dimensionless normalized velocity distributions in microporous m...
Figure 2.16 (a) Schematic of the nano‐porous medium. Black color represents ...
Figure 2.17 Dynamics of Spontaneous imbibition of water in a straight nano‐c...
Figure 2.18 Spontaneous imbibition of water in a nano‐porous medium. (a) The...
Figure 2.19 Comparison of velocity profiles of gas flow in a periodic microc...
Figure 2.20 The evolution of droplet diameter square against iteration durin...
Figure 2.21 Simulation setup of methane vapor condensation in two adjacent n...
Figure 2.22 The comparison of vapor condensation process in two adjacent nan...
Figure 2.23 The comparison of vapor (a) velocity and (b) density at the
x
‐ax...
Figure 2.24 The comparison of liquid saturation of large (
S
l
) and small (
S
s
)...
Chapter 3
Figure 3.1 The modeling procedure from 2D to 3D image using multiple‐point s...
Figure 3.2 The varied fraction of micropores in the multiscale pore networks...
Figure 3.3 The workflow of fusing the fine‐ and coarse‐scale structures into...
Figure 3.4 Produced two shale models by the quartet structure generation set...
Chapter 4
Figure 4.1 The delta‐based conductance distribution assumed by Machta and Gu...
Figure 4.2 Scaling exponent
α
versus
g
l
/
g
h
for both two and three dimen...
Figure 4.3 The schematic conductance distribution in a porous medium. The co...
Figure 4.4 Pore‐throat radius distributions for 12 pore networks constructed...
Figure 4.5 Simulated permeability,
k
, and formation factor,
F
, against the n...
Figure 4.6 Simulated permeability,
k
, and formation factor,
F
, against the n...
Figure 4.7 Simulated permeability,
k
, and formation factor,
F
, against the n...
Chapter 5
Figure 5.1 The pore throat‐size distribution and the fitted lognormal distri...
Figure 5.2 The pore throat‐size distribution (on the left) and the simulated...
Figure 5.3 (a) The pore throat‐size distribution and (b) the LB simulated pe...
Figure 5.4 The pore throat‐size distribution (on the left) and the LB simula...
Figure 5.5 The pore size distribution, derived from the measured mercury int...
Figure 5.6 The pore size distribution, derived from the air‐brine capillary ...
Figure 5.7 The pore size distribution, derived from the measured mercury int...
Figure 5.8 The pore size distribution, derived from the measured mercury int...
Figure 5.9 The pore size distribution, constructed from two‐dimensional SEM ...
Figure 5.10 The pore size distribution, synthetically generated from a Berea...
Chapter 6
Figure 6.1 (a) The angular momentum vector and the quantized
z
‐components ...
Figure 6.2 Magnetization vector model in one‐pulse experiment in a rotating ...
Figure 6.3 (a) acquired CPMG echoes and (b) inverted spectrum of an unconven...
Figure 6.4 FIB‐SEM of a representative source rock sample, illustrating the ...
Figure 6.5 NMR log of a source rock section in a well. A
T
2
spectrum from a ...
Figure 6.6 GRI total porosity against the NMR log total porosity from the sa...
Figure 6.7 Field NMR organic porosity and FIB‐SEM organic porosity for a sou...
Figure 6.8 The plot of average transverse relaxation
T
2
verse the average po...
Figure 6.9 Schematic illustration of a long rock sample (gray cylinder) in a...
Figure 6.10 Illustration of step‐by‐step moving the sample through the
r.f
. ...
Figure 6.11 Photo of a whole core of diameter 4 in and length 12 in.
Figure 6.12 (a) Acquired NMR echo trains of a whole cores passing through th...
Figure 6.13 Image of the core studied here and the HSR‐NMR detected fluid co...
Figure 6.14 Picture of a sample being weighed in the air on the left and the...
Figure 6.15 Example
T
2
spectra of five drill cutting samples after saturatio...
Figure 6.16 Illustrating measurement method reproducibility: bulk density, m...
Figure 6.17 Cross plots of artificial cuttings measured using GRI and the NM...
Chapter 7
Figure 7.1 The schematic experiment setup for the permeability measurement w...
Figure 7.2 The schematic experiment setup for the permeability measurement w...
Figure 7.3 The schematic experiment setup for the permeability measurement w...
Figure 7.4 A schematic of two flow regimes caused by fractures and the matri...
Figure 7.5 Pressure recordings at upstream and downstream gas reservoirs ver...
Figure 7.6 The coordination system associated with the rock sample for deriv...
Figure 7.7 A linear relationship between of and time for a rock sample fro...
Figure 7.8 Pressure dependence of both fracture and matrix permeabilities (
k
Figure 7.9 Enhancement factor of permeability,
f
c
, for a micro‐tube with a r...
Figure 7.10 The conceptual diagram of the experimental setup to measure the ...
Figure 7.11 The pressure transient curves at inlet, outlet and three pressur...
Figure 7.12 Pressure as a function of the transformation variable λ with res...
Figure 7.13 Permeability versus pore pressure at the constant confining pres...
Figure 7.14 Permeability as a function of pore pressure at the constant conf...
Chapter 8
Figure 8.1 Mineralogy and Leco TOC (vol%) for the four samples studied here....
Figure 8.2 Permeability test program
P
c
is the confining stress (set equa...
Figure 8.3 Effective permeability to dodecane versus effective stress for si...
Figure 8.4 Micro‐computed tomography (μ‐CT) images showing diametrical (left...
Figure 8.5 Micro‐computed tomography (μ‐CT) images showing diametrical (left...
Figure 8.6 Schematic illustration showing how micro‐fractures and matrix por...
Figure 8.7 Matrix permeability versus effective stress for four plugs. The e...
Figure 8.8 Back‐scattered SEM image: (a) Organic‐rich siliceous mudstone Sam...
Figure 8.9 (a) Mercury injection capillary pressure versus mercury saturatio...
Chapter 9
Figure 9.1 Upward imbibition direction at either parallel (P) or transverse ...
Figure 9.2 The locations of the Sichuan Basin, Ordos Basin, and Chongqing ci...
Figure 9.3 Imbibition behavior of Barnett samples. (a) The
n
‐decane imbibiti...
Figure 9.4 Incremental pore volume versus pore‐throat diameter for Barnett s...
Figure 9.5 Relationship between TOC and porosity and pore volume fraction co...
Figure 9.6 Pore size characteristics of Longmaxi and Yanchang samples: (a) P...
Figure 9.7 FE‐SEM photos of Longmaxi and Yanchang Formation Shale samples. (...
Figure 9.8 FIB‐SEM images and pore size distribution information of Samples ...
Figure 9.9 Imbibition behavior of Longmaxi and Yanchang samples and its rela...
Figure 9.10 Pore‐throat diameter distribution of Ziliujing Formation Shale s...
Figure 9.11 FE‐SEM images of Ziliujing Formation Shale samples.
Figure 9.12 1st water imbibition slope of T samples versus MIP porosity (%) ...
Figure 9.13 Simplified pore network models for shale samples with different ...
Figure 9.14 Wettability evolution and pore structure evolution models; for c...
Chapter 10
Figure 10.1 Ternary diagram of shale mineralogy.
Figure 10.2 Macropores aligned parallel to bedding in shale.
Figure 10.3 Three‐dimensional characterization of micro‐fractures in shale....
Figure 10.4 Planes of weakness parallel to laminae in shale. (a) is the opti...
Figure 10.5 Imaging of bedding‐parallel fractures in shale expanding during ...
Figure 10.6 Fluid transport along grain boundaries within shale.
Figure 10.7 Preferential flow network within shale.
Figure 10.8 Multiscale modeling of fluid transport through shale.
Figure 10.9 U‐shaped permeability response with increasing pore pressure for...
Figure 10.10 Behavior of sorptive gases at constant temperature or pressure....
Figure 10.11 (a) Diagram of parallel processes occurring in fissure-like ell...
Figure 10.12 Competitive responses in the deformation of pores due to sorpti...
Figure 10.13 Strain vs. pore pressure for helium (top) and methane (bottom)....
Figure 10.14 Isolating the sorptive strain using Eqs. (10.14) and (10.15). S...
Figure 10.15 Solving for sorptive permeability evolution for processes in pa...
Figure 10.16 Schematic of permeability enhancement expected for a nitrogen f...
Figure 10.17 Normalized permeability evolution
k
/
k
0
. Permeability increased ...
Chapter 11
Figure 11.1 MicroCT image at resolution of (a) 5.48 μm and (b) 2.79 μm for o...
Figure 11.2 Color‐mapped fracture and porosity network. Green: connected fra...
Figure 11.3 Dynamic study of microscale imaging at different imbibition time...
Figure 11.4 Enlarged view of microscale imaging at different imbibition time...
Figure 11.5 Distance of fluid front with time in the matrix of Cal‐Z zone de...
Figure 11.6 Illustration of mapping protocol for microindentation testing.
Figure 11.7 UCS (a), Brazilian tensile strength (b), and Young's modulus (c)...
Figure 11.8 Failure patterns of Brazilian tensile strength test. (a) Treated...
Figure 11.9 Load‐Depth curve of microindentation testing of the outcrop Eagl...
Figure 11.10 SEM images of the thin‐section sample prepared from the tight o...
Figure 11.11 SEM images and elemental mapping from the EDS analysis for the ...
Figure 11.12 SEM image and elemental mapping from the EDS analysis. (a) seco...
Figure 11.13 Two pairs of SEM images from the OMZ of source rock section sam...
Figure 11.14 Three pairs of SEM images from OMZ of source rock section sampl...
Figure 11.15 Three pairs of SEM images from the OMZ of source rock section s...
Figure 11.16 Absolute permeability measurement under different confining pre...
Chapter 12
Figure 12.1 Effective permeability
k
eff
versus fracture density
ρ
deter...
Figure 12.2 Effective permeability simulated by the lattice‐Boltzmann method...
Figure 12.3 Effective permeability simulated by the lattice‐Boltzmann method...
Figure 12.4 Effective permeability simulated by the numerical method (filled...
Chapter 13
Figure 13.1 Shale oil and gas resources in the world.
Figure 13.2 A complex fracture network observed in a fractured shale sample....
Figure 13.3 An example of complex fracture network in multiple wells, which ...
Figure 13.4 Definition and demonstration of EDFM’s special non‐neighboring c...
Figure 13.5 Definition and demonstration of EDFM’s special non‐neighboring c...
Figure 13.6 Two examples of the application of the EDFM method for easy and ...
Figure 13.7 Pressure dependent permeability curve in reservoir simulation.
Figure 13.8 Relative permeability curves used in this verification study.
Figure 13.9 Validation model with a horizontal well and 100 hydraulic fractu...
Figure 13.10 Comparing the well productivity via the EDFM method with those ...
Figure 13.11 Base case model with three horizontal wells and complex hydraul...
Figure 13.12 Base case model with three horizontal wells and complex hydraul...
Figure 13.13 Statistical plots of complex hydraulic fracture geometries. (a)...
Figure 13.14 Wellbore flowing bottom hole pressure.
Figure 13.15 Various types of visualizations with hydraulic fractures after ...
Figure 13.16 Three horizontal wells with two different natural fracture azim...
Figure 13.17 Three horizontal wells with two different natural fracture azim...
Figure 13.18 Comparisons of well productivity between two scenarios of natur...
Figure 13.19 Comparisons of pressure distribution between two different natu...
Figure 13.20 Comparisons of drainage volume between two different natural fr...
Figure 13.21 Three horizontal wells with 5000 natural fractures. (a) 2D view...
Figure 13.22 Comparisons of well productivity between two scenarios of total...
Figure 13.23 Different types of visualizations with 5000 natural fractures a...
Figure 13.24 Three horizontal wells with natural fracture length of 100 m. (...
Figure 13.25 Comparisons of well productivity for two scenarios of natural f...
Figure 13.26 Different types of visualizations with natural fracture lengths...
Figure 13.27 Three horizontal wells with two sets of natural fractures. (a) ...
Figure 13.28 Comparisons of well productivity between two scenarios of natur...
Figure 13.29 Different types of visualizations with two sets of natural frac...
Figure 13.30 Three horizontal wells with two different natural fracture dip ...
Figure 13.31 Three horizontal wells with two different natural fracture dip ...
Figure 13.32 Magnified view of natural fractures with three different kinds ...
Figure 13.33 Comparisons of well productivity with different natural fractur...
Figure 13.34 Pressure distribution with two different natural fracture dip a...
Figure 13.35 Drainage volume with two different natural fracture dip angles ...
Figure 13.36 Comparisons of well productivity among six different conductivi...
Figure 13.37 Comparisons of pressure distribution with two natural fracture ...
Figure 13.38 Comparisons of drainage volume with two natural fracture conduc...
Figure 13.39 Relationship between simulation CPU time and the number of frac...
Chapter 14
Figure 14.1 Schematic one‐dimensional flow from reservoir to hydraulic fract...
Figure 14.2 Comparing the simulated and analytical flux ratio
F
against the ...
Figure 14.3 Comparing the simulated and analytical cumulative production rat...
Figure 14.4 The relative error determined for the parameter
A
estimated by E...
Chapter 15
Figure 15.1 An illustration for identifying the sweet spot based on OQ, RQ, ...
Figure 15.2 Sweet spots prediction workflow using logging and 3D seismic dat...
Figure 15.3 Workflow for the productive sweet spot.
Guide
Cover Page
Title Page
Copyright Page
Dedication Page
List of Contributors
Preface
Table of Contents
Begin Reading
Index
Wiley End User License Agreement
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Physics of Fluid Flow and Transport in Unconventional Reservoir Rocks
Edited by
Behzad Ghanbarian
Feng Liang
Hui‐Hai Liu
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Names: Ghanbarian, Behzad, editor. | Liang, Feng, editor. | Liu, Hui-Hai, editor.Title: Physics of fluid flow and transport in unconventional reservoir rocks / edited by Behzad Ghanbarian, Feng Liang, Hui-Hai Liu.Description: First edition. | Hoboken, NJ, USA : John Wiley & Sons, Inc., 2023. | Includes bibliographical references and index.Identifiers: LCCN 2022052921 (print) | LCCN 2022052922 (ebook) | ISBN 9781119729877 (hardback) | ISBN 9781119727842 (adobe pdf) | ISBN 9781119729907 (epub)Subjects: LCSH: Hydrocarbon reservoirs–Analysis. | Rocks–Permiability. | Petroleum–Migration. | Gas reservoir engineering. | Fluid dynamics. | Transport theory. | Petrology.Classification: LCC TN870.56 .P54 2023 (print) | LCC TN870.56 (ebook) | DDC 622/.338–dc23/eng/20221230LC record available at https://lccn.loc.gov/2022052921LC ebook record available at https://lccn.loc.gov/2022052922
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List of Contributors
Stacey M. AlthausAramco Americas: Aramco ResearchCenter—HoustonHouston, TX, USA
Mustafa BasriSaudi Aramco, DhahranSaudi Arabia
Athma R. BhandariInstitute for Geophysics, JacksonSchool of GeosciencesThe University of Texas at AustinAustin, TX, USA
Mohammed BoudjatitSaudi Aramco, DhahranSaudi Arabia
Huangye ChenAramco Americas: Aramco ResearchCenter—HoustonHouston, TX, USA
Jin‐Hong ChenAramco Americas: Aramco ResearchCenter—HoustonHouston, TX, USA
Li ChenKey Laboratory of Thermo‐Fluid Science and Engineering of MOESchool of Energy and Power EngineeringXi'an Jiaotong UniversityXi'an, Shaanxi, China
Xiaona CuiSimTech LLCKaty, TX, USA
Derek ElsworthDepartment of Energy and Mineral EngineeringEMS Energy Institute and G3 CenterPenn State UniversityUniversity Park, PA USA
Misagh EsmaeilpourPorous Media Research LabDepartment of GeologyKansas State UniversityManhattan, KS, USA
Peter B. FlemingsInstitute for GeophysicsJackson School of GeosciencesThe University of Texas at AustinAustin, TX, USAandDepartment of Geological SciencesJackson School of GeosciencesThe University of Texas at AustinAustin, TX, USA
Zhiye GaoState Key Laboratory of Petroleum Resources and ProspectingChina University of Petroleum, Beijing, ChinaandUnconventional Petroleum Research Institute, China University of Petroleum, Beijing, China
Behzad GhanbarianPorous Media Research LabDepartment of GeologyKansas State UniversityManhattan, KS, USA
Yanhui HanAramco Americas: Aramco ResearchCenter—HoustonHouston, TX, USA
Qinhong HuDepartment of Earth and Environmental SciencesUniversity of Texas at ArlingtonArlington, TX, USA
Nayif JamaSaudi Aramco, Dhahran, Saudi Arabia
Qinjun KangEarth and Environmental Sciences DivisionLos Alamos National LaboratoryLos Alamos, NM, USA
Feng LiangAramco Americas: Aramco ResearchCenter—HoustonHouston, TX, USA
Chuxi LiuThe University of Texas at AustinHildebrand Department of Petroleum and Geosystems EngineeringAustin, TX, USA
Hui‐Hai LiuAramco Americas: Aramco ResearchCenter—HoustonHouston, TX, USA
Rabah MesdourSaudi Aramco, Dhahran, Saudi Arabia
Jijun MiaoSimTech LLCKaty, TX, USA
Feifei QinChair of Building PhysicsDepartment of Mechanical and Process EngineeringETH Zürich, Zurich, Switzerland
Sebastian Ramiro‐RamirezInstitute for Geophysics, Jackson School of GeosciencesThe University of Texas at AustinAustin, TX, USAandDepartment of Geological SciencesJackson School of GeosciencesThe University of Texas at AustinAustin, TX, USA
Brandon SchwartzDepartment of Energy and Mineral Engineering, EMS Energy Institute and G3 CenterPenn State UniversityUniversity Park, PA, USA
Kamy SepehrnooriThe University of Texas at AustinHildebrand Department of Petroleum and Geosystems EngineeringAustin, TX, USA
Pejman TahmasebiColorado School of MinesGolden 80401, USA
Cenk TemizelSaudi AramcoDhahran, Saudi Arabia
Hari ViswanathanEarth and Environmental Sciences DivisionLos Alamos National LaboratoryLos Alamos, NM, USA
Junjian WangKlohn Crippen Berger LtdBrisbane, QueenslandAustralia
Yuqi WuShandong Provincial Key Laboratory of DeepOil and GasChina University of Petroleum (East China)Qingdao, ChinaandSchool of Geosciences, China University of Petroleum (East China), Qingdao, China
Hongbing XieSimTech LLCKaty, TX, USA
Wei YuSimTech LLCKaty, TX, USAandThe University of Texas at AustinHildebrand Department of Petroleum and Geosystems EngineeringAustin, TX, USA
Jilin ZhangAramco Americas: Aramco ResearchCenter—HoustonHouston, TX, USA
Jianlin ZhaoChair of Building PhysicsDepartment of Mechanical and Process EngineeringETH ZürichZurich, Switzerland
Preface
This book provides basic concepts and recent advances of fluid flow and transport in unconventional reservoirs across different scales (from pore to core and to reservoir) for a broad range of audiences from various scientific disciplines, such as geology, geoscience, geochemistry, geophysics, rock mechanics, and petroleum engineering. In the Introduction chapter, we address recent progress and ongoing challenges related to hydrocarbon exploration and production in tight and ultra-tight formations. The first part of the book on pore-scale characterizations consists of three chapters. In the second chapter, Wang and his coworkers present an overview of recent progress on pore-scale simulations and digital rock physics to unconventional reservoir rocks. They emphasize that further small-scale experiments are still required to validate numerical models. In Chapter 3, Wu and Tahmasebi review digital rock models. They discuss that incorporating multiresolution and multiscale structures and generating large-scale digital models are still very challenging. In Chapter 4, Ghanbarian and Esmaeilpour address the effect of scale on permeability and formation factor. They present a simple scaling law and show reasonable agreement between theoretical estimations and pore-network simulations. Part II of the book on core-scale heterogeneity includes seven chapters. In Chapter 5, Ghanbarian et al. study theoretical modeling of single-phase and gas relative permeabilities in shales and tight porous rocks. They apply concepts of the effective-medium approximation and demonstrate that by including the physics of gas flow, one can estimate permeability reasonably well at the core scale. Chapter 6 by Chen and his coworkers addresses applications of nuclear magnetic resonance and its recent advances to determine total porosity and partial porosity in organic matter of unconventional reservoir rocks. In Chapter 7, recent progress on tight rock permeability measurement is addressed by Liu, Zhang, and Boudjatit. They present two newly developed laboratory methods and evaluate them using laboratory measurements. Chapter 8 by Bhandari et al. presents permeability evolution under cycling confining stress conditions. They demonstrate that micro-fractures might be closed due to confining stress leading to permeability reduction under cyclic loading. In Chapter 9, Gao and Hu provide insights into shale wettability using spontaneous imbibition experiments. Their results demonstrate the co-existence of water and oil in the pore network of shales proving their mixed-wet characteristics. In Chapter 10, Schwartz and Elsworth study permeability enhancement in shales induced by desorption. Those authors argue that the magnitude of permeability enhancement depends on the distribution of sorptive mineral components, geometry of flow path, and initial permeability. Chapter 11 by Liang, Liu, and Zhang provides insights that help improve oil and gas production in unconventional reservoirs. More specifically, their experimental evidence shows that aqueous-based fracturing fluid may have positive impacts on gas production from organic-rich carbonate source rocks. The last part of the book focuses on large-scale petrophysics of unconventional reservoirs, which has broad applications to field. In Chapter 12, Ghanbarian proposes percolation-based effective-medium theory to model effective permeability in matrix-fracture systems. By comparing with numerical simulations, he shows that effective permeability can be accurately estimated at different fracture densities. In Chapter 13, Xie et al. apply embedded discrete fracture model to simulate fluid flow in complex fracture networks. They address the effect of natural fracture properties, such as fracture azimuth, length, and dip angle. Chapter 14 by Liu and his coauthors presents a closed-form relationship for production rate. By comparing with numerical simulations, Liu et al. validate their proposed model for different initial reservoir pressures, pressure drawdowns, and pressure sensitivity factors for permeability. In the last chapter, Mesdour et al. discuss sweet spots and their identification in shale reservoirs. They provide a state-of-art review of existing methods developed for sweet spot identification and address relevant challenges and knowledge gaps.
Many colleagues and students contributed to our understanding of fluid flow and transport in unconventional reservoirs. We are grateful to those who helped us with this book. We also acknowledge those who contributed to this book by writing different chapters on several topics. We hope this book helps geologists and petroleum engineers in industry as well as faculty and students in academia.
Behzad Ghanbarian
Feng Liang
Hui-Hai Liu
January 2023
Introduction
1Unconventional Reservoirs: Advances and Challenges
Behzad Ghanbarian1, Feng Liang2, and Hui-Hai Liu2
1 Porous Media Research Lab, Department of Geology, Kansas State University, Manhattan, KS, USA
2 Aramco Americas: Aramco Research Center—Houston, Houston, TX, USA
1.1 Background
Energy is one of the most important components in the world. Primary sources of energy take various forms, such as fossil energy, nuclear energy, and renewable energy sources. Fossil energy resources (e.g. coal, oil, and natural gas) were formed when plants and animals died and were buried underground. The quality of hydrocarbon accordingly depends on organic content as well as temperature and pressure conditions. Although there are limited reserves of fossil energy resources and despite recent advances in renewable energy, global economy still depends on fossil fuels to a great extent (Figure 1.1). Statistics reported by the British Petroleum (BP) company based on data from 1994 to 2019 show that the world primary energy consumption growth in 2019 slowed to 1.3%. This is less than half the growth rate i.e. 2.8% in 2018. Three‐quarters of the energy consumption increase was driven by natural gas and renewable resources in 2019.
Based on analyses reported by the BP company, oil has contributed to the share of global primary energy more than others since 1994 (Figure 1.2) with 33.1% contribution in 2019. After oil, coal and natural gas are the second and third largest contributors. Although coal lost its share to account for nearly 27%, the contribution of natural gas increased to 24% in 2019. The share of renewable resources rose to record highs of 5% in 2019, and they overtook nuclear energy with about 4% contribution. Figure 1.2 shows the share of hydroelectricity has been nearly constant and about 6%.
Unconventional reservoirs, including oil and gas shales and tight sandstones, are distributed around the world (Figure 1.3) with an estimated endowment of several thousand trillion cubic feet (Kim et al. 2000). Since shale reservoirs have been successfully explored and produced in the United States (Figure 1.3), they recently became one of the major contributors to energy supplies.
There exist three general types of unconventional reservoirs, i.e. (i) organic‐rich source rocks, (ii) tight oil reservoirs, and (iii) hybrid plays in which production occurs from source rocks and conventional reservoirs (Zoback and Kohli 2019). These types of unconventional reservoirs are different in geologic formations and, therefore, should be optimally exploited using different and appropriate approaches.
Despite numerous practical applications in oil/gas exploration and production as well as recent progress, we are still far from fully understanding all mechanisms of flow and transport in shales and tight sandstones across scales, particularly from pore to reservoir. In the following, we briefly address recent advances in unconventional reservoirs and discuss current challenges in oil and gas exploration and production.
Figure 1.1 World total energy consumption between 1994 and 2019.
Source: BP Statistical Review of World Energy (2020)/BP International Limited.
1.2 Advances
Since 2005, the beginning of shale gas revolution in the United States, unconventional oil and gas resources as well as their developments and productions have received a remarkable amount of attention around the world (Zoback and Kohli 2019). Despite various challenges that still exist, the petroleum engineering community made tremendous progress, particularly in the past decade. In what follows, we briefly address several notable achievements. For further details and comprehensive recent advances, see e.g. Barati and Alhubail (2020), Rezaee (2021), and Moghanloo (2022).
1.2.1 Wettability
Characterizing the contact angle of fluids (e.g. water, oil, and gas) and its spatial variability within unconventional reservoirs and under in situ conditions are essential not only to understand the trapping phenomenon and enhance oil and gas recovery but also to improve greenhouse gas (e.g. carbon dioxide and hydrogen) sequestration underground. In the literature, various methods, such as contact angle measurements (Iglauer et al. 2015; Roshan et al. 2016), spontaneous imbibition (Liu et al. 2019; Siddiqui et al. 2019), and nuclear magnetic resonance (Odusina et al. 2011; Su et al. 2018) were proposed to determine wettability in unconventional reservoir rocks. Recently, Arif et al. (2021) collected published data on shale contact angle measurements and developed a repository. They concluded that the oil‐brine mixture in shales behaved in terms of wettability over a wide range from water‐wet to strongly oil‐wet. Although the CO2‐brine mixture typically showed weakly water‐wet to CO2‐wet behavior, the CH4‐brine mixture in shales was weakly water‐wet. Arif et al. (2021) also investigated what causes high variabilities in shale wettability and found that the main factors were pressure, temperature, thermal maturity, total organic content, and mineralogy of shales.
Figure 1.2 Shares of global primary energy between 1994 and 2019 (BP Statistical Review of World Energy 2020/BP International Limited).
Although our knowledge of shale wettability has improved, further investigations are still needed to study the solid–fluid and fluid–fluid contact angles under realistic reservoir conditions more comprehensively. This would help enhance oil and gas recovery and exploit unconventional reservoirs even more successfully.
1.2.2 Permeability
Liquid and gas transports in shales and tight porous rocks were widely studied, particularly at the pore and core levels. The literature on gas permeability and its modeling is indeed vast and extensive (Javadpour et al. 2021; Liu 2017; Tahmasebi et al. 2020; Zhang et al. 2019). Numerous models were developed to address gas flow in nanostructures of shales by taking the effect of different transport mechanisms, such as slip flow, Knudsen diffusion, surface diffusion, and sorption into account. For example, Beskok and Karniadakis (1999) incorporated the effect of slip flow and modified the Poiseuille equation to describe gas flow in a cylindrical tube. Civan (2010) later applied the Beskok–Karniadakis model to scale up gas permeability in a network of pores. Using concepts from first‐order slip flow and Knudsen diffusion, Javadpour (2009) developed another model for gas transport in a nano‐scale cylindrical tube.
Figure 1.3 World shale gas resources (top) and shale gas and oil plays in the United States (bottom).
Source: Both maps are from US Energy Information Administration.
Recently, in addition to slip flow and Knudsen diffusion, more complex mechanisms such as sorption and surface diffusion were incorporated to model gas flow in shales. For instance, Wu et al. (2016) proposed a unified theoretical model by coupling various mechanisms including slip flow, Knudsen diffusion, sorption, and surface diffusion. Those authors stated that “… surface diffusion is an important transport mechanism, and its contribution cannot be negligible and even dominates in nanopores with less than 2 nm in diameter.” Jia et al. (2018) found that surface diffusion might increase gas flow significantly at low pore pressures (e.g. < 2000 psi) depending on the value of surface diffusivity.
In the literature, most theoretic models developed to study gas permeability are based on the bundle of tortuous capillary tubes approach. However, it is an oversimplifying idealization in which a porous medium with actual interconnected pores is replaced with non‐interconnected tortuous tubes of equal length (Purcell 1949). An important inconsistency between the bundle of tubes model and real porous media was noted by Fatt (1956). Fatt’s main objection to the parallel‐tubes model was that it has no connections between the individual tubes, in contrast to the network models that he developed. An additional problem is that, in a bundle‐of‐tubes model, individual pores span the entire sample or problem domain, regardless of its size.
Instead of the bundle of tortuous tubes approach, one may theoretically model gas transport in shales using more appropriate upscaling techniques e.g. percolation theory, critical path analysis (CPA), and effective‐medium approximation (EMA) from statistical physics (Ghanbarian et al. 2020; Hunt et al. 2014; Sahimi 2011). Such approaches take into account the effect of pore connectivity. For example, Zhang and Scherer (2012) applied the CPA approach to estimate Klinkenberg‐corrected permeability in shales from mercury intrusion capillary pressure curve and formation factor. They also used the Kozeny–Carman model, compared their estimations with experiments, and found that measured permeability values matched with CPA estimations more accurately. In another study, Ghanbarian and Javadpour (2017) assumed that slip flow and Knudsen diffusion are dominant transport mechanisms and employed the EMA to estimate the pore pressure‐dependent gas permeability in shales. By comparing with experiments, pore‐network models, and lattice‐Boltzmann simulations, they found that their proposed model estimated gas permeability within a factor of 3 of measurements and/or simulations.
1.3 Challenges
Over the past decade, productions from unconventional reservoirs were successful in the United States and Canada. However, there are several outstanding issues that critically impact hydrocarbon recovery in tight and ultra‐tight formations. In the following, we discuss some notable issues briefly.
1.3.1 Multiscale Systems
Unconventional reservoirs are extremely complex multiscale formations composed of nano‐ and micro‐scale pores as well as naturally and hydraulically induced fractures of various sizes. Morphology, pore structure, and spatial/temporal heterogeneities are important, as these factors affect fluid transport in unconventional reservoirs. Figure 1.4a and b show nano‐ and micro‐scale pores within organic and inorganic matrices, respectively, and Figure 1.4c shows microfractures.
Figure 1.4 (a) SEM image of contiguous spongy‐textured organic matter pore network.
Source: Loucks and Reed (2014)/from Gulf Coast Association of Geological Societies.
(b) Intra‐particle pores located along cleavage planes of clay particles.
Source: Loucks et al. (2012)/from American Association of Petroleum Geologists.
(c) Irregular natural microfracture filled with pyrite
Source: Loucks and Reed (2016)/from Gulf Coast Association of Geological Societies.
Maximizing the production of unconventional reservoirs is limited in part by the incomplete understanding of mass transport mechanisms in tight and ultra‐tight reservoir rocks at the pore and even molecular scale. In the literature, various approaches, such as scan electron microscopy (Wu and Aguilera 2012), focused ion beam scanning electron microscopy (Shabro et al. 2014), atomic force microscopy (Javadpour et al. 2012; Wu and Aguilera 2012), and transmission electron microscopy (Chalmers et al. 2012; Froute and Kovscek 2020) were extensively applied to characterize the complexity and heterogeneity of pore space in unconventional reservoir rocks.
Although molecular dynamics simulations (Castez et al. 2017; Fang et al. 2017; He et al. 2020; Huang et al. 2018; Ungerer et al. 2015; Zhang et al. 2020) have been applied to gain molecular insights of transport processes, mass transport dynamics investigations in real shale rocks are still very limited. Characterization of mass transport dynamics in shales is of contemporary interest in the oil and gas industry. Shales may be permeable to some hydrocarbons and impermeable to others. Transport rates are controlled by partitioning between different phases, adsorption, and desorption from pore surfaces, and by diffusion within nano‐scale pores. These molecular‐level processes are dictated by chemical and electrostatic interactions. A better understanding of the molecular mechanisms of mass transport is certain to facilitate oil and gas production.
1.3.2 Hydrocarbon Production
Another issue associated with unconventional reservoirs is that production rates rapidly decrease in the first few years of production (Hakso and Zoback 2019; Sandrea and Sandrea 2014; Speight 2019).
Patzek et al. (2013) developed a simple but robust gas production model using basic concepts and geometry of the extraction process. In their model, the production rate scales with time as t−0.5 at early times, however, declines exponentially at late times. By comparison with gas production from 8294 wells within the Barnett shale, they showed that their model provided accurate scaling of gas production. Patzek et al. (2013) also found reasonable agreement between their theory and experimental data from 2057 horizontal wells. They argued that in young wells, it would be difficult to determine the crossover between the square‐root decay and exponential decay. However, their model was capable of determining lower and upper bounds.
More recently, Hakso and Zoback (2019) analyzed hydrocarbon production data from two oil (Eagle Ford and Bakken) and two gas (Marcellus and Barnett) unconventional reservoirs. The average monthly data are presented in Figure 1.5 (Hakso and Zoback 2019). To eliminate uncertainties, Hakso and Zoback (2019) removed those wells that did not produce hydrocarbon for at least two years. Each curve shown in Figure 1.5 represents the average over more than 7500 wells from each reservoir. As can be seen, monthly production rates decline sharply during the first two to three years of production, consistent with the results of Patzek et al. (2013).
1.3.3 Recovery Factor
Recovery factor is the recoverable amount of hydrocarbon initially in place whose value is relatively low for both shale gas and tight oil wells. Although it is uncertain to accurately determine the amount of total hydrocarbon in place, the recovery factor in tight gas reservoirs is around 25% after a few years of production (Zoback and Kohli 2019). For tight oil, various studies reported recovery factors about 2–10% (Hamdi et al. 2018; Pankaj et al. 2018; Wang et al. 2019). Low and extremely low recovery factors for gas and oil reservoirs indicate that a considerable amount of hydrocarbon is not produced from unconventional resources, particularly compared to conventional reservoirs. One promising enhanced oil recovery approach to improve recovery factor is gas Huff and Puff (Hoffman 2012, 2018). Various types of gas, such as carbon dioxide, methane, air, immiscible hydrocarbon, and miscible hydrocarbon, were used in the gas Huff and Puss process (Firouz and Torabi 2014; Sanchez‐Rivera et al. 2015; Soh and Babadagli 2018). Particularly, the CO2 Huff and Puff process has been applied in the field for several decades. However, there still exist challenges, such as asphaltene precipitation, corrosion, and viscous fingering, associated with field implementations (Zhou et al. 2018). One should note that the price of oil and cost of CO2 capture and storage may also play determinative roles.
1.3.4 Unproductive Wells
Another issue in unconventional reservoirs is that a large number of drilled wells contribute minimally to hydrocarbon production (Zoback and Kohli 2019). It was reported that around 30% of shale wells were not productive (Al‐Nakhli et al. 2020; Miller et al. 2011). Although unproductive wells may be used for CO2 sequestration or enhanced oil recovery purposes, high priorities should be given to produce hydrocarbon more optimally from unconventional reservoirs by drilling more economic wells.
Figure 1.5 Monthly production for two oil and two gas reservoirs
(Source: Hakso and Zoback (2019)/Society of Exploration Geophysicists).
1.4 Concluding Remarks
In this chapter, we briefly reviewed several recent advances in unconventional oil and gas reservoirs. We noted that our knowledge of shale wettability as well as gas and liquid transport at the pore and core levels increased in the past decade. However, there still exist challenges, such as low hydrocarbon production and recovery factors. We also discussed that a considerable number of drilled wells in unconventional formations are unproductive. Although various technologies were developed to improve production, further investigations are still required to substantially increase production rates in tight and ultra‐tight reservoirs.
The major purpose of this book is to, in a systematic way, present the most recent developments in addressing some of these technical challenges in the areas of pore‐scale characterizations, core‐scale heterogeneity, and large‐scale petrophysics.
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