Coupled Fluid Flow and Geomechanical Modeling of Seismicity in the Azle Area (North Texas)
- Rongqiang Chen (Texas A&M University) | Xu Xue (Texas A&M University) | Jaeyoung Park (Texas A&M University) | Changqing Yao (Texas A&M University) | Hongquan Chen (Texas A&M University) | Akhil Datta-Gupta (Texas A&M University) | Michael J. King (Texas A&M University) | Peter Hennings (University of Texas Bureau of Economic Geology) | Robin Dommisse (University of Texas Bureau of Economic Geology)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- August 2020
- Document Type
- Journal Paper
- 1,006 - 1,018
- 2020.Society of Petroleum Engineers
- azle area seismicity, coupled flow and geomechanical simulation, strain accumulation, unbalanced fluid loading
- 7 in the last 30 days
- 94 since 2007
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A series of earthquakes was recorded along a mapped fault system near Azle, Texas, in 2013. To identify the mechanism of seismicity, geologic, production/injection, and seismicity data are gathered to build a detailed simulation model with coupled fluid flow and geomechanics to model fluid injection/production and the potential onset of seismicity. Sensitivity studies for a broad range of reservoir and geomechanical parameters are performed to identify the influential parameters for injection wellhead pressure and earthquake data. A Pareto-based multiobjective history matching is performed using these influential parameters. The calibrated results are used to identify the controlling mechanisms for seismicity in the Azle area, North Texas, and their relationship to hydrocarbon production and fluid injection in the vicinity.
Geomechanical interaction has a significant impact on seismicity in the Azle area. Unbalanced loading created by the difference in the net fluid injection and production on different sides of the fault seems to generate accumulation of plastic strain change, likely resulting in the onset of seismicity. Previous studies ignore fluid withdrawal from gas production. Thus, they seem to have significantly underestimated the fluid withdrawal rates, almost by an order of magnitude. The equivalent bottomhole-voidage fluid rate used in this study suggests a drop in history-matched reservoir pore pressure that is consistent with the observed tubinghead pressure trends. Pore pressure increases may not fully explain the seismicity near the Azle area. Instead, geomechanical effects and strain propagation to the basement appear to be the dominant mechanisms. The low fault cohesion and minimum effective horizontal stress obtained from history matching confirm that the faults must be near or at the critically stressed state before the initiation of fluid production/injection. A sensitivity analysis indicates that the minimum effective horizontal stress and fracture gradient play a critical role in the potential risk for seismicity related to fluid injection/production. A streamline flow pattern further shows that there is no fluid movement in the basement formation and the unbalanced loading from different sides of the fault is more likely the controlling mechanism for seismicity.
|File Size||8 MB||Number of Pages||13|
Aki, K. and Richards, P. G. 2002. Quantitative Seismology, second edition. Sausalito, California, USA: University Science Books.
Bittencourt, A. C. and Horne, R. N. 1997. Reservoir Development and Design Optimization. Paper presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, 5–8 October. SPE-38895-MS. https://doi.org/10.2118/38895-MS.
Bonnlander, B. V. and Weigend, A. S. 1994. Selecting Input Variables Using Mutual Information and Nonparametric Density Estimation. Proc., International Symposium on Artificial Neural Networks, Tainan, Taiwan, 42–50.
Bradley, H. B. 1987. Petroleum Engineering Handbook. Richardson, Texas, USA: Society of Petroleum Engineers.
Cappa, F. and Rutqvist, J. 2011. Modeling of Coupled Deformation and Permeability Evolution during Fault Reactivation Induced by Deep Underground Injection of CO2. Int J Greenhouse Gas Control 5 (2): 336–346. https://doi.org/10.1016/j.ijggc.2010.08.005.
Chang, K. W. and Yoon, H. 2018. 3-D Modeling of Induced Seismicity Along Multiple Faults: Magnitude, Rate, and Location in a Poroelasticity System. J Geophys Res Solid Earth 123 (11): 9866–9883. https://doi.org/10.1029/2018JB016446.
Chen, R., Xue, X., Park, J. et al. 2020. New Insights into the Mechanisms of Seismicity in the Azle Area, North Texas. Geophysics 85 (1): EN1–EN15. https://doi.org/10.1190/geo2018-0357.1.
Computer Modelling Group. 2016. STARS User Guide (Version 2016.10). Calgary, Alberta, Canada: Computer Modelling Group Ltd.
Dahm, T. and Krüger, F. 2014. Moment Tensor Inversion and Moment Tensor Interpretation. In New Manual of Seismological Observatory Practice 2 (NMSOP-2), ed. P. Bormann, 1–37. Potsdam, Germany: Deutsches GeoForschungsZentrum GFZ. https://doi.org/10.2312/GFZ.NMSOP-2_IS_3.9.
Datta-Gupta, A. and King, M. J. 2007. Streamline Simulation: Theory and Practice, Vol. 11. Richardson, Texas, USA: SPE Textbook Series, Society of Petroleum Engineers.
Drillinginfo. 2017. Online Research Queries, https://info.drillinginfo.com/ (accessed 1 May 2017).
Economides, M. J., Hill, A. D., Ehlig-Economides, C. et al. 2013. Petroleum Production Systems, second edition. London, England, UK: Pearson Education.
Ellsworth, W. L. 2013. Injection-Induced Earthquakes. Science 341 (6142): 1225942. https://doi.org/10.1126/science.1225942.
Ewing, T. E. 1991. The Tectonic Framework of Texas. Austin, Texas, USA: Bureau of Economic Geology, University of Texas at Austin.
Fan, Z., Eichhubl, P., and Gale, J. F. W. 2016. Geomechanical Analysis of Fluid Injection and Seismic Fault Slip for the Mw4.8 Timpson, Texas, Earthquake Sequence. J Geophys Res Solid Earth 121 (4): 2798-2812. https://doi.org/10.1002/2016JB012821.
Frohlich, C., DeShon, H., Stump, B. et al. 2016. A Historical Review of Induced Earthquakes in Texas. Seismol Res Lett 87 (4): 1022–1038. https://doi.org/10.1785/0220160016.
Frohlich, C., Hayward, C., Stump, B. et al. 2011. The Dallas–Fort Worth Earthquake Sequence: October 2008 through May 2009. Bull Seismol Soc Am 101 (1): 327–340. https://doi.org/10.1785/0120100131.
Gono, V., Olson, J. E., and Gale, J. F. 2015. Understanding the Correlation between Induced Seismicity and Waste Water Injection in the Fort Worth Basin. Paper presented at the 49th U.S. Rock Mechanics/Geomechanics Symposium, San Francisco, California, USA, 28 June–1 July. ARMA 2015-419.
Granger, C. and Lin, J. 1994. Using the Mutual Information Coefficient To Identify Lags in Nonlinear Models. J Time Ser Anal 15 (4): 371–384. https://doi.org/10.1111/j.1467-9892.1994.tb00200.x.
Hornbach, M. J., DeShon, H. R., Ellsworth, W. L. et al. 2015. Causal Factors for Seismicity Near Azle, Texas. Nat Commun 6: 6728. https://doi.org/10.1038/ncomms7728.
Hornbach, M. J., Jones, M., Scales, M. et al. 2016. Ellenburger Wastewater Injection and Seismicity in North Texas. Phys Earth Planet Inter 261 (Part A): 54–68. https://doi.org/10.1016/j.pepi.2016.06.012.
Jha, B. and Juanes, R. 2014. Coupled Multiphase Flow and Poromechanics: A Computational Model of Pore Pressure Effects on Fault Slip and Earthquake Triggering. Water Resour Res 50 (5): 3776–3808. https://doi.org/10.1002/2013WR015175.
Jimenez, E., Sabir, K., Datta-Gupta, A. et al. 2007. Spatial Error and Convergence in Streamline Simulation. SPE Res Eval & Eng 10 (3): 221–232. SPE-92873-PA. https://doi.org/10.2118/92873-PA.
Kanamori, H. 1977. The Energy Release in Great Earthquakes. J Geophys Res 82 (20): 2981–2987. https://doi.org/10.1029/JB082i020p02981.
Krantz, B. and Neely, T. 2016. Subsurface Structural Interpretation: The Significance of 3-D Structural Frameworks. In 3-D Structural Interpretation: Earth, Mind, and Machine, 91–109. Tulsa, Oklahoma, USA: AAPG.
Lele, S. P., Hsu, S. Y., Garzon, J. L. et al. 2016. Geomechanical Modeling To Evaluate Production-Induced Seismicity at Groningen Field. Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, Abu Dhabi, UAE, 7–10 November. SPE-183554-MS. https://doi.org/10.2118/183554-MS.
Lucia, F. J. 2007. Carbonate Reservoir Characterization: An Integrated Approach, second edition. Berlin, Germany: Springer Science & Business Media.
Mishra, S. 2009. Uncertainty and Sensitivity Analysis Techniques for Hydrologic Modeling. J Hydroinform 11 (3–4): 282–296. https://doi.org/10.2166/hydro.2009.048.
Park, H. Y., Datta-Gupta, A., and King, M. J. 2015. Handling Conflicting Multiple Objectives Using Pareto-Based Evolutionary Algorithm during History Matching of Reservoir Performance. J Pet Sci Eng 125: 48–66. https://doi.org/10.1016/j.petrol.2014.11.006.
Park, J., Kim, J., and Zhu, D. 2016. Assessment of Potential Fault Activation in Tarim Basin during Hydraulic Fracturing Operations by Using Rigorous Simulation of Coupled Flow and Geomechanics. Paper presented at the SPE Asia Pacific Hydraulic Fracturing Conference, Beijing, China, 24–26 August. SPE-181811-MS. https://doi.org/10.2118/181811-MS.
Railroad Commission of Texas. 2015a. Proposal for Decision, Oil and Gas Docket No. 09-0296410, https://www.rrc.state.tx.us/media/31022/09-96410-sho-pfd.pdf (accessed 2 September 2019).
Railroad Commission of Texas. 2015b. Proposal for Decision, Oil and Gas Docket No. 09-0296411, https://www.rrc.state.tx.us/media/31023/09-96411-sho-pfd.pdf (accessed 2 September 2019).
Railroad Commission of Texas. 2019. H10 Filing System, http://webapps.rrc.state.tx.us/H10/h10PublicMain.do (accessed 28 August 2019).
Romero, C. E. and Carter, J. N. 2001. Using Genetic Algorithms for Reservoir Characterization. J Pet Sci Eng 31 (2): 113–123. https://doi.org/10.1007/s12040-019-1144-3.
Rutqvist, J., Rinaldi, A. P., Cappa, F. et al. 2013. Modeling of Fault Reactivation and Induced Seismicity during Hydraulic Fracturing of Shale-Gas Reservoirs. J Pet Sci Eng 107: 31–44. https://doi.org/10.1016/j.petrol.2013.04.023.
Schlumberger. 2018. Petrel E&P Software Platform, https://www.Software.Slb.Com/Products/Petrel.
Segall, P. 1989. Earthquakes Triggered by Fluid Extraction. Geology 17 (10): 942–946. https://doi.org/10.1130/0091-7613(1989)017<0942:ETBFE>2.3.CO;2.
Segall, P., Grasso, J. R., Mossop, A. 1994. Poroelastic Stressing and Induced Seismicity Near the Lacq Gas Field, Southwestern France. J Geophys Res Solid Earth 99 (B8): 15423–15438. https://doi.org/10.1029/94JB00989.
Segall, P. and Lu, S. 2015. Injection-Induced Seismicity: Poroelastic and Earthquake Nucleation Effects. J Geophys Res Solid Earth 120 (7): 5082–5103. https://doi.org/10.1002/2015JB012060.
Simpson, R. W. 1997. Quantifying Anderson’s Fault Types. J Geophys Res Solid Earth 102 (B8): 17909–17919.
Snee, J. E. L. and Zoback, M. D. 2016. State of Stress in Texas: Implications for Induced Seismicity. Geophys Res Lett 43 (19): 208–214. https://doi.org/10.1002/2016GL070974.
Stein, R. S. 1999. The Role of Stress Transfer in Earthquake Occurrence. Nature 402 (6762): 605–609. https://doi.org/10.1038/45144.
USGS. 2018. Search Earthquake Catalog, https://earthquake.usgs.gov/earthquakes/search/ (accessed 1 May 2018).
Wang, H. 2000. Theory of Linear Poroelasticity with Applications to Geomechanics and Hydrogeology. Princeton, New Jersey, USA: Princeton University Press.
Yin, J., Park, H. Y., Datta-Gupta, A. et al. 2011. A Hierarchical Streamline-Assisted History Matching Approach with Global and Local Parameter Updates. J Pet Sci Eng 80 (1): 116–130. https://doi.org/10.1016/j.petrol.2011.10.014.