Fast 1-D Velocity Optimization Inversion to 3D Velocity Imaging: A Case Study of Sichuan Maerkang Earthquake Swarm in 2022

Xinxin Yin, Xiaoyue Zhang, Run Cai, Haibo Wang () and Feng Liu ()
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Xinxin Yin: Gansu Earthquake Agency, Lanzhou 730000, China
Xiaoyue Zhang: Institute of Artificial Intelligence and Change Management, Shanghai University of International Business and Economics, Shanghai 200062, China
Run Cai: Chengdu Surveying Geotechnical Research Institute Co., Ltd. of MCC, Chengdu 610063, China
Haibo Wang: Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Feng Liu: Institute of AI for Education, East China Normal University, Shanghai 200062, China

Sustainability, 2022, vol. 14, issue 23, 1-19

Abstract: To obtain an accurate one-dimensional velocity model, we developed the EA_VELEST method based on the evolutionary algorithm and the VELEST program. This method can quickly generate a suitable 1D velocity model and finally input it into the 3D velocity inversion process using the TomoDD method. We adopt TomoDD methods to inverse the high-resolution three-dimension velocity structure and relative earthquake hypocenters for this sequence. This system processing flow was applied to the Sichuan Maerkang earthquake swarm in 2022. By collecting the seismic phase data of the Maerkang area between 1 January 2009 and 15 June 2022, we relocated the historical earthquakes in the area and obtained accurate 3D velocity imaging results. The relocated hypocenters reveal a SE-trending secondary fault, which is located ~5 km NW of the Songgang fault. In the first ten-hour of the sequence, events clearly down-dip migrated toward the SE direction. The inverted velocity structure indicates that the majority of earthquakes during the sequence occurred along the boundaries of the high and low-velocity zones or high and low- V P / V S anomalies. Especially both the two largest earthquakes, M S 5.8 and M S 6.0, occurred at the discontinuities of high and low-velocity zones. The EA_VELEST method proposed in this paper is a novel method that has played a very good enlightenment role in the optimization of the one-dimensional velocity model in geophysics and has certain reference significance. The 3D velocity results obtained in this paper and the analysis of tectonic significance provide a reference for the seismogenic environment of this Maerkang earthquake and the deep 3D velocity of the Ganzi block.

Keywords: Maerkang earthquake; EA_VELEST; Earthquake relocation; double difference tomography; Songgang fault; three-dimensional velocity structure (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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