Automated seismic waveform location using multichannel coherency migration (MCM)–I: theory

Abstract

This is a repository copy of Automated seismic waveform location using multichannel coherency migration (MCM)-I: theory.

Recent Advances and Challenges of Waveform‐Based Seismic Location Methods at Multiple Scales

“…Though advanced and automated procedures can ensure an efficient picking process (e.g., Akram & Eaton, ; Grigoli et al, ; Ross et al, ; Withers et al, ), robust phase identification and picking are still challenging for low SNR events, and missed arrival times and picking errors may directly cause location errors. Other nonnegligible limitations of most traveltime‐ or ray‐based methods consist of their incapability of utilizing multichannel coherency (Poiata et al, ; Shi, Angus, et al, ), or considering secondary features (like scattering) or finite‐frequency effects (Dahlen et al, ; H. Zhang & Thurber, ).…”

“…Analogous to double difference method (Waldhauser & Ellsworth, ), Zhang et al () proposed the station‐pair double difference method and used it to locate nonvolcanic tremors successfully. Recently, several studies implemented this idea into waveform‐based methods with cross‐correlation techniques from seismic interferometry (e.g., Dales et al, ; Droznin et al, ; Grandi & Oates, ; Poiata et al, ; Ruigrok et al, ; Shi, Angus, et al, ). By including higher‐order cross correlations, K. L. Li, Sadeghisorkhani, et al () and K. L. Li, Sgattoni, et al () extended the previous single cross‐correlation stacking to a double‐correlation method and a more generalized high‐order correlation method, which showed superior performance in lateral imaging resolution for locating tremors with sparse station networks.…”

“…By including higher‐order cross correlations, K. L. Li, Sadeghisorkhani, et al () and K. L. Li, Sgattoni, et al () extended the previous single cross‐correlation stacking to a double‐correlation method and a more generalized high‐order correlation method, which showed superior performance in lateral imaging resolution for locating tremors with sparse station networks. Shi, Angus, et al () proposed a novel multichannel coherency migration method for locating earthquakes using continuous seismic data based on stacking of Pearson correlation coefficients for waveforms from different receiver pairs or groups. Synthetic and field microseismic data sets demonstrated the multichannel coherency could produce improved source energy focusing.…”

“…Besides the imaging operator, the PWS methods also differ in preprocessing of the input waveforms and the event detection and location detection criteria. There are various CFs adopted to improve the SNR and compensate the side effects of source radiation patterns; for example, the input data are converted to envelope (Gharti et al, ; Liao et al, ; Zeng et al, ); semblance (Furumoto et al, ; W. Zhang & Zhang, ; Staněk et al, ; C. Zhang et al, ); short‐term average to long‐term average ratio (STA/LTA; Drew et al, ; Grigoli et al, ; L. Li et al, ); kurtosis (Langet et al, ; Poiata et al, ); multichannel coherency (Shi, Angus, et al, ). …”

“…Cross‐correlation stacking shares the same principle of exploiting differential traveltimes at pair‐wise stations from common events, with master‐station method and station‐pair method mentioned above. This method has been applied to microseismic monitoring in the oil and gas industry (Eisner et al, ; Grandi & Oates, ; L. Li et al, ; Trojanowski & Eisner, ; Shi et al, ), volcanic tremor data (Droznin et al, ; K. L. Li et al, ; K. L. Li et al, ), mining‐induced seismicity (Dales, ; L. Li et al, ), and slow (tectonic tremor and low‐frequency earthquakes) and regular earthquake (Poiata et al, ; Ruigrok et al, ; Shi et al, ). In this study, we will call it interferometric‐type method.…”