A Hybrid Earthquake Detection Method for Distributed Acoustic Sensing Array Data and Its Application to the 2022 Menyuan Earthquake Sequence

Abstract Rapid response to destructive earthquakes is an important application of the distributed acoustic sensing technology (DAS), which can exploit existing telecom fiber‐optic cables as ultra‐dense DAS arrays. This technique significantly reduces deployment time and records large volume waveforms. However, the large stream of DAS data necessitates efficient earthquake detection methods. We propose a new DAS earthquake detection approach that hybridizes the Array Beam Detection (ABD) and Template Matched Filter (TMF) methods. This approach is applied to detect aftershocks of the 2022 Menyuan Mw6.6 earthquake recorded by a linear DAS array with the dark fiber. The continuous DAS records are scanned by the ABD method first. During this process, if the energy of the ABD‐detected event exceeds a specific threshold, the event is added to the template library, and the TMF is then used to re‐scan the records within a designated time window. The ABD method detects 69.4% of the events in the network catalog. Our new approach detects 89.4% of the catalog events, representing a 20% increase in the overall detection rate. Of the newly detected events, our approach identifies 42.4% more than the ABD method. Notably, the magnitudes of 95.7% of these newly detected events are estimated to be below M2.0, indicating an enhanced monitoring capability. However, precise event locations remain challenging with the linear DAS array.