A high-resolution seismic catalog for the 2021 MS6.4/MW6.1 Yangbi earthquake sequence, Yunnan, China: Application of AI picker and matched filter

Abstract

We present a high-resolution seismic catalog for the 2021 MS6.4/MW6.1 Yangbi sequence. The catalog has a time range of 2021-05-01 to 2021-05-28, and contains ~8,000 well located events. It captures the features of the whole foreshock sequence and the early aftershocks. We designed a detection strategy incorporating both an artificial intelligent (AI) picker and a matched filter algorithm. Here, we adopt a hybrid AI method incorporating convolutional and recurrent neural network (CNN & RNN) for event detection and phase picking respectively (i.e. CERP), a light-weight AI picker that can be trained with small volume of data. CERP is first trained with detections from a STA/LTA and Kurtosis-based method called PAL, and then construct a rather complete template set of ~4,000 events. Finally, the matched filter algorithm MESS augments the initial detections and measures differential travel times with cross-correlation, which finally results in precise relocation. This process gives 9,026 detections, among which 7,943 events can be well relocated. The catalog shows as expected power-law distribution of frequency magnitude and reveals detailed pattern of seismicity evolution. The main features are: (1) the foreshock sequence images simple fault geometry with consistent strike, but also show a variable event depth along strike; (2) the mainshock ruptures the same fault of the foreshock sequence and activate conjugate faults further to the southeast; (3) complex seismicity are developed in the post-seismic period, indicating complex triggering mechanisms. Thus, our catalog provides a reliable basis for further investigations, such as b-value studies, rupture process, and triggering relations.