https://scholars.lib.ntu.edu.tw/handle/123456789/641566
標題: | Deep learning-based earthquake catalog reveals the seismogenic structures of the 2022 M<inf>W</inf> 6.9 Chihshang earthquake sequence | 作者: | 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 HAO KUO-CHEN |
關鍵字: | 2022 M 6.9 Chihshang earthquake sequence W | AI earthquake catalog | Longitudinal Valley | SeisBlue | Seismogenic structure | 公開日期: | 1-十二月-2024 | 卷: | 35 | 期: | 1 | 來源出版物: | Terrestrial, Atmospheric and Oceanic Sciences | 摘要: | 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. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/641566 | ISSN: | 10170839 | DOI: | 10.1007/s44195-024-00063-9 |
顯示於: | 地質科學系 |
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