Imaging Microseismic Events and Seismic Anisotropy from Shear-Wave Splitting Analysis
Yuan, Duo 1988-
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Microseismic imaging has become a useful tool in monitoring and analyzing fractures generated by hydraulic-fracturing stimulation in unconventional reservoirs. Although this technology has become more mature, there are still challenges in the processing of downhole microseismic data. First, intrinsic anisotropic reservoir rock-like-shale stacked with man-made fractures resulted in more complicated anisotropy than seen in more commonly used vertical transverse isotropy (VTI). However, a more accurate low-symmetry anisotropic model cannot be constrained from conventional P and fast S-wave travel times alone due to relatively sparse ray coverage. Second, for single monitoring well, event azimuths, which are obtained by a P-wave hodogram, must be added to data to determine event locations. However, typical weak P-wave arrivals usually cause heavy azimuth measurement uncertainties. To address these issues, we introduced new data, full S-wave-splitting parameters (delay time of the slow S-wave and fast S-wave polarization direction), to improve velocity models and microseismic locations. To solve the first problem, instead of assuming a higher-symmetry anisotropic model, we attempted to add S-wave splitting data, which is very helpful to constrain anisotropy. A Genetic Algorithm (GA) inversion was adopted to simultaneously determine event locations and stiffness coefficients of anisotropic media. We applied this approach to synthetic waveforms and successfully recovered the input event locations and velocity model. The effectiveness of this method is further demonstrated from real microseismic data acquired in the Bakken shale reservoir. The determined microseismic events are aligned in E15N direction, which agrees with the azimuth of the fast symmetric axis in the resulting anisotropic model in the area. Another study in this dissertation is the development of a new method of determining microseismic event azimuths using S-wave splitting analysis. This approach is based the positive correlation between the effectiveness of S-wave splitting measurements and the accuracy of the event azimuth. We applied a grid search to find the optimal azimuth. The obtained event azimuths agree well with the input ones in the synthetic experiments and with those determined from clear P wave particle motions in the field data tests. In summary, S-wave splitting data contain valuable information about seismic anisotropy and were significantly useful in resolving the velocity model and locating microseismic events. To the best of our knowledge, this dissertation is the first study using full S-wave splitting parameters in microseismic imaging. We have demonstrated the success of our new methods using synthetic and field data and envision their broad application in the future.