Multichannel coherence migration grid search (MCMgs) in locating microseismic events recorded by a surface array

Abstract

SUMMARY Microseismic monitoring has been used in geo-energy related activities, such as shale-gas exploitation, mining, deep geothermal exploitation, geotechnical and structural engineering, for detecting and locating fractures, rock failures and micro-earthquakes. The success of microseismic monitoring depends on reliable detection and location of the recorded microseismicity. Multichannel coherence migration (MCM) is a detection and location waveform migration-based approach which does not require phase picking, identification and association and performs well on noisy data. Its caveat is a high computational cost, which impedes its application of MCM on large data sets or for real-time monitoring. To address this issue, we propose an improved approach, the multichannel coherence migration grid search (MCMgs), by introducing an adaptive grid optimization technique. Based on results from synthetic and real data, we show that MCMgs reduces the computation time up to 64 times. In addition, MCMgs generates multiple maximum coherence values with various grid sizes instead of a single (maximum) coherence value that links to a single gridpoint and size, thus resulting in more accurate locations. Our simulation results on different deployment geometries demonstrate that MCMgs is effective even with a small number of recordings available—a minimum of seven. We conduct a sensitivity analysis to assess how the detectability of events is affected by the spatial arrangement of the deployed monitoring array. If a limited number of seismometers are available for deployment, our analysis favours a patch array deployment geometry. We show that 12 seismometers deployed at a patch array geometry can have similar detection and localization capability as a large rectangular array of more than 100 seismometers but at a much lower computational and deployment cost.