Microseismic Monitoring of Stimulating Shale Gas Reservoir in SW China: 2. Spatial Clustering Controlled by the Preexisting Faults and Fractures

Abstract

Microseismic monitoring is crucial to improving stimulation efficiency of hydraulic fracturing treatment, as well as to mitigating potential induced seismic hazard. We applied an improved matching and locating technique to the downhole microseismic data set during one treatment stage along a horizontal well within the Weiyuan shale gas play inside Sichuan Basin in SW China, resulting in 3,052 well‐located microseismic events. We employed this expanded catalog to investigate the spatiotemporal evolution of the microseismicity in order to constrain migration of the injected fluids and the associated dynamic processes. The microseismicity is generally characterized by two distinctly different clusters, both of which are highly correlated with the injection activity spatially and temporarily. The distant and well‐confined cluster (cluster A) is featured by relatively large‐magnitude events, with ~40 events of M −1 or greater, whereas the cluster in the immediate vicinity of the wellbore (cluster B) includes two apparent lineations of seismicity with a NE‐SW trending, consistent with the predominant orientation of natural fractures. We calculated the b‐value and D‐value, an index of fracture complexity, and found significant differences between the two seismicity clusters. Particularly, the distant cluster showed an extremely low b‐value (~0.47) and D‐value (~1.35). We speculate that the distant cluster is triggered by reactivation of a preexisting critically stressed fault, whereas the two lineations are induced by shear failures of optimally oriented natural fractures associated with fluid diffusion. In both cases, the spatially clustered microseismicity related to hydraulic stimulation is strongly controlled by the preexisting faults and fractures.

Temporal Variations of Near‐Surface Anisotropy Induced by Hydraulic Fracturing at a Shale Play Site in Southwest China

“…In this study, the fast polarization directions inferred from the vertically propagating S waves are in the range of N40°–70°E, which are generally parallel to the strike directions of the natural fractures observed by microseismic monitoring studies (Chen, Meng et al, ; Meng et al, ). Such an orientation is also confirmed by well log data based on high electric conductivity (Figure b, Chen, Meng et al, ).…”

“…In this study, the fast polarization directions inferred from the vertically propagating S waves are in the range of N40°–70°E, which are generally parallel to the strike directions of the natural fractures observed by microseismic monitoring studies (Chen, Meng et al, ; Meng et al, ). Such an orientation is also confirmed by well log data based on high electric conductivity (Figure b, Chen, Meng et al, ). On the other hand, the local maximum horizontal compressional stress is approximately aligned along the east‐west direction (Figure b, Chen, Meng et al, ), which differs significantly from the observed fast polarization direction.…”

“…Such an orientation is also confirmed by well log data based on high electric conductivity (Figure 1b, Chen, Meng et al, 2018). On the other hand, the local maximum horizontal compressional stress is approximately aligned along the east-west direction (Figure 1b, Chen, Meng et al, 2018), which differs significantly from the observed fast polarization direction. Therefore, we speculate that the physical mechanism responsible for the observed seismic anisotropy is likely the preferential alignment of the natural fractures.…”

“…The white square indicates the shale play site, and the black lines represent faults in the area. (b) The rose diagrams show the distribution of the orientations of the maximum compressional stress (SHmax) and the strikes of natural cracks (Chen, Meng et al, ). The length of the bars is proportional to the numbers of observations that are along the direction of the corresponding bars.…”

Downhole Microseismic Source Location Based on a Multi‐Dimensional DIRECT Algorithm for Unconventional Oil and Gas Reservoir Exploration

“…In other words, to better delineate fracture distribution, reliable locational algorithmic studies are extremely urgent. However, in many cases, we can only estimate the distance to the microseismic source from the difference between the P-and S-wave arrival times, while it is impossible to achieve the geometric shapes and original times of the events induced in a three-dimensional (3D) space (Soledad and Danilo, 2018;Chen et al, 2018) unless the direction where the energy originates from is determined using azimuth from the motion polarization analysis of both the P and S waves recorded by multistage three-component geophones (usually 12 or 16 pieces). As we focus on event location in this study, these preliminary works should already be completed.…”