In the southern Sichuan Basin, China, the recent increase in the seismic activity has been suspected to be related to hydraulic fracturing stimulation for producing the shale gas. In this study, we used the monitoring data from a local seismic network within the shale gas blocks to study the earthquakes near the shale gas production wells that have detailed injection data. Comparison of the timing of earthquakes and stimulation schedule of the studied well pads indicates an apparent correlation between the seismic activity and hydraulic fracturing. The results of seismic velocity tomography reveal that the reactivation of preexisting faults due to fluid diffusion is the primary cause of the observed earthquakes. Focal mechanism analysis combined with geomechanical modeling indicates that the increased pore pressures resulted from hydraulic fracturing are sufficient to trigger seismic slip on the faults.

The accuracy of the velocity model strongly affects the accuracy of microseismic source location and hence the reliability of fracture imaging. We have developed a systematic methodology for microseismic velocity model inversion and source location. A new misfit function is used for both problems, which yields more reliable result than the conventional ones. Using the same measure of misfit, the location errors resulting from the use of different misfit functions are eliminated. The neighborhood algorithm and master station method (MSM) are adopted for calculating the velocity model and source location, respectively. The reason for using the neighborhood algorithm is that it has fewer tuning parameters and is easy to be tuned, whereas the advantage of the MSM is that it can automatically remove the mispicks. The performance of the proposed methods is illustrated using the ball-hit events with known locations, and the validity of the inversion results is verified by the relocations of these events. We also used the inverted velocity models to locate the microseismic events detected from the monitoring data. The location result indicates that the fractures have an average half-length of 280 m and height of 55 m and the fracture azimuth is approximately N77°W.

No abstract

Detection and arrival picking of microseismic events with low signal-to-noise ratios (S/N) are problematic because these events are usually obscured by ambient noise. We have developed an intraevent coherence-based event detection method to address this problem. The innovations of this method include the adaptation of a crosscorrelation, least-squares-based algorithm to achieve better moveout correction for successive record segments and the use of a multichannel semblance coefficient to identify the microseismic events. After finding the events, we adopted a new picker to determine their P- and S-wave arrival times. This picker was developed by combining three aspects of the distinction between seismic signal and ambient noise, namely, the (1) amplitude, (2) polarization, and (3) statistic property differences. We evaluated the performance of the proposed methods using a real data set recorded during an 11-stage hydraulic fracture stimulation. We have determined that, for microseismic event detection, the proposed method has an overall false trigger rate of 12%. As for arrival picking, the average picking error of the new picker is [Formula: see text] and its standard deviation is [Formula: see text]. Comparison of the results of different event detection and arrival picking methods versus the S/N of the data demonstrates that the proposed methods are more applicable for detection and arrival picking of low S/N microseismic events.