SKLGP大讲堂第103期 | 宋君豪 — High‐resolution seismicity and ground motion variability across the highly locked southern Anninghe fault with dense seismic arrays and machine learning techniques

报告题目：High‐resolution seismicity and ground motion variability across the highly locked southern Anninghe fault with dense seismic arrays and machine learning techniques

报告人：宋君豪

单位：香港中文大学

时间：2024年11月15日15:00—15:30（周五）

地点：新实验楼211教室（珙桐对面）

报告人简介：

2019年本科毕业于中国科学技术大学，2024年博士毕业于香港中文大学，将于2025年初前往美国加州大学伯克利分校从事博士后研究。主要研究方向为基于密集地震台阵和人工智能方法研究地震活动性以及断裂带结构。博士期间以第一作者在Journal of Geophysical Research: Solid Earth发表文章2篇，2023年获香港中文大学PhD IMPAC奖资助访问美国加州大学伯克利分校半年。

报告简介：

The Anninghe fault in southwestern China has great potential to produce devastating earthquakes. However, its southern segment has experienced seismic quiescence during the past 40 years, resulting in less knowledge about its detailed seismicity and structures which are crucial for seismic hazard assessment. Here, we apply a series of novel machine learning methods to seismic data of multi‐scale temporary dense arrays we deployed near the southern segment of the Anninghe fault. Our event detection and location results show that earthquakes along this segment are very limited, consistent with the wellacknowledged highly locked fault plane status. The detected seismic events are mostly located off the fault and many are closely related to human activities (e.g., mining explosions). The source parameters of one on‐fault earthquake agree with the geologically inferred fault orientation and slip direction. The dense across‐fault recordings from local and regional sources reveal much larger amplitudes around the mapped fault traces, corresponding to two shallower fault damage zones that can trap seismic energies and promote earthquake ruptures. The efficient methods used here can be extended to future longer‐term seismic experiments over the Anninghe fault, or other similar faults.

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