Machine learning-based aftershock seismicity of the 2015 Gorkha earthquake controlled by flat-ramp geometry and a tear fault  

作　　者：Yeyang Kuang Jiangtao Li 

机构地区：[1]School of Geodesy and Geomatics,Wuhan University,Wuhan 430079,China [2]Hubei Luojia Laboratory,Wuhan 430079,China

出　　处：《Earthquake Science》2025年第1期17-32,共16页地震学报(英文版)

基　　金：funded by the National Key R&D Program of China(2022YFF0800601);National Natural Science Foundation of China(42174069,U1939204).

摘　　要：The Main Himalayan Thrust(MHT),where the 2015 MW7.8 Gorkha earthquake occurred,features the most seismicity of any structure in Nepal.The structural complexity of the MHT makes it difficult to obtain a definitive interpretation of deep seismogenic structures.The application of new methods and data in this region is necessary to enhance local seismic hazard analyses.In this study,we used a well-designed machine learning-based earthquake location workflow(LOC-FLOW),which incorporates machine learning phase picking,phase association,absolute location,and double-difference relative location,to process seismic data collected by the Hi-CLIMB and NAMASTE seismic networks.We built a high-precision earthquake catalog of both the quiet-period and aftershock seismicity in this region.The seismicity distribution suggests that the quietperiod seismicity(388 events)was controlled by a mid-crustal ramp and the aftershock seismicity(12,669 events)was controlled by several geological structures of the MHT.The higher-level detail of the catalogs derived from this machine learning method reveal clearer structural characteristics,showing how the flat-ramp geometry and a possible duplex structure affect the depth distribution of the seismic events,and how a tear fault changes this distribution along strike.

关 键 词：aftershock seismicity 2015 Gorkha earthquake machine learning flat-ramp geometry tear fault 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] P315[自动化与计算机技术—控制科学与工程]