Seismic Anisotropy Estimation Using a Downhole Microseismic Data Set in a Shale Gas Reservoir

Changpeng Yu (), Yaling Zhu and Serge Shapiro
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Changpeng Yu: School of Geophysics and Geomatics, China University of Geosciences (Wuhan), Wuhan 430074, China
Yaling Zhu: School of Geosciences, Yangtze University, Wuhan 430100, China
Serge Shapiro: Institute of Geological Sciences, Free University of Berlin, 12249 Berlin, Germany

Energies, 2023, vol. 16, issue 23, 1-19

Abstract: Shale anisotropy has a significant impact on the data processing and interpretation of microseismic monitoring in shale gas reservoirs. A geology- and rock-physics-constrained approach to estimating shale anisotropy using down-hole microseismic data sets is proposed in this study and is applied to the case of Horn River shale. A priori knowledge of shale anisotropy is obtained by integrating geological analyses and rock physics studies. This knowledge serves as an important constraint when building the initial model, minimizing the uncertainties and evaluating the results. The application to Horn River shale shows that the optimized anisotropic velocity model reduces the time misfit by about 65% compared to the originally provided velocity model. As the relocated perforation shot indicates, the event locations are significantly improved. The results also show that a high fraction of clay mineral results in strong fabric anisotropy in the Fort Simpson formation, whereas the quartz-rich shale gas reservoirs (Muskwa and Otter Park formations) show weaker fabric anisotropy. The percentage of velocity anisotropy in Horn River shale can be up to 40%. The fabric anisotropy of shale derived from the downhole microseismic data set is comparable with that of laboratory experiments. This demonstrates that downhole microseismic monitoring, as a quasi in situ experiment, has the potential to contribute to a better understanding of subsurface anisotropy beyond the laboratory. In addition, microseismic measurements of shale anisotropy are conducted in the seismic frequency band and are thus more applicable for further seismic applications.

Keywords: shale gas; anisotropy; microseismic monitoring; thomsen paramerters (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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