LAUSR

In the Koyna–Warna region, western India, an enormous number of microearthquakes was detected automatically on borehole records. Most of these events could not be identified on the surface network by a routine approach based on visual inspection primarily due to signal attenuation and the presence of noise. In this work, we implemented an automatic detection workflow to analyze the time series of an earthquake sequence that has clear foreshock and aftershock activity associated with an Mw 4.0 earthquake that occurred on 3 June 2017. Further, we applied a nested grid-search algorithm to constrain the absolute earthquake locations. For about one month of data, a total of ∼1500 earthquakes were detected based on the automatic detection process, out of which ∼1000 earthquakes were locatable. All event detections, P-wave and S-wave phase readings were manually inspected and refined to ensure their quality. Previously, only about 435 events were well located based on the visual inspection approach for the same time period. Also, we analyzed repeated earthquakes based on waveform similarity leading to an improvement in the relocations of earthquakes of the aforementioned earthquake sequence. The relocated seismicity aligns parallel to a deep-reaching lineament derived from recent investigations using airborne light detection and ranging measurements.