Terrestrial, Atmospheric and Oceanic Sciences (Feb 2024)

Deep learning-based earthquake catalog reveals the seismogenic structures of the 2022 MW 6.9 Chihshang earthquake sequence

  • Wei-Fang Sun,
  • Sheng-Yan Pan,
  • Chun-Ming Huang,
  • Zhuo-Kang Guan,
  • I-Chin Yen,
  • Chun-Wei Ho,
  • Tsung-Chih Chi,
  • Chin-Shang Ku,
  • Bor-Shouh Huang,
  • Ching-Chou Fu,
  • Hao Kuo-Chen

DOI
https://doi.org/10.1007/s44195-024-00063-9
Journal volume & issue
Vol. 35, no. 1
pp. 1 – 16

Abstract

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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.

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