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Deep learning-based earthquake catalog reveals the seismogenic structures of the 2022 MW6.9 Chihshang earthquake sequence

Authors :
Sun, Wei-Fang
Pan, Sheng-Yan
Huang, Chun-Ming
Guan, Zhuo-Kang
Yen, I-Chin
Ho, Chun-Wei
Chi, Tsung-Chih
Ku, Chin-Shang
Huang, Bor-Shouh
Fu, Ching-Chou
Kuo-Chen, Hao
Source :
Terrestrial, Atmospheric and Oceanic Sciences; December 2024, Vol. 35 Issue: 1
Publication Year :
2024

Abstract

On 18 September 2022, the MW6.9 Chihshang earthquake struck the south half of the Longitudinal Valley, Taiwan, and caused severe damage. A precise and rapid report for the distribution of aftershock sequence after a devastating earthquake provides key information for deciphering the seismogenic structure in the source region. The utilization of deep-learning methodologies for earthquake event detection offers a significant acceleration in data analysis. In this study, we use SeisBlue, a deep-learning platform/package, to extract the whole earthquake sequence from September to October 2022, including the MW6.5 Guanshan foreshock, the MW6.9 mainshock, over 14,000 aftershocks, and 866 foal mechanisms from two sets of broadband networks. After applying hypoDD for earthquakes, the distribution of aftershock sequence clearly depicts not only the Central Range Fault and the Longitudinal Valley Fault but also several local, shallow tectonic structures that have not been observed along the southern Longitudinal Valley.

Details

Language :
English
ISSN :
10170839 and 23117680
Volume :
35
Issue :
1
Database :
Supplemental Index
Journal :
Terrestrial, Atmospheric and Oceanic Sciences
Publication Type :
Periodical
Accession number :
ejs65602327
Full Text :
https://doi.org/10.1007/s44195-024-00063-9