Deep learning-based earthquake catalog reveals the seismogenic structures of the 2022 MW 6.9 Chihshang earthquake sequence
Journal
Terrestrial, Atmospheric and Oceanic Sciences
Journal Volume
35
Journal Issue
1
Date Issued
2024-12-01
Author(s)
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
Abstract
On 18 September 2022, the MW 6.9 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 MW 6.5 Guanshan foreshock, the MW 6.9 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.
Subjects
2022 M 6.9 Chihshang earthquake sequence W | AI earthquake catalog | Longitudinal Valley | SeisBlue | Seismogenic structure
SDGs
Type
journal article