地震资料智能化处理进展：震源机制、断层首波以及动态触发的识别与分析

朴健; 熊健; 郑定昌; 汪龙潭; 运乃丹; 裴玮来; 周一剑; 周仕勇

doi:10.3799/dqkx.2025.252

Volume 51 Issue 1

Jan. 2026

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Article Navigation > Earth Science > 2026 > 51(1): 56-73

Piao Jian, Xiong Jian, Zheng Dingchang, Wang Longtan, Yun Naidan, Pei Weilai, Zhou Yijian, Zhou Shiyong, 2026. Advances in Intelligent Processing of Seismic Data: Focal Mechanisms, Fault Zone Head Waves and Dynamic Triggering Detection and Analysis. Earth Science, 51(1): 56-73. doi: 10.3799/dqkx.2025.252

Citation:

Piao Jian, Xiong Jian, Zheng Dingchang, Wang Longtan, Yun Naidan, Pei Weilai, Zhou Yijian, Zhou Shiyong, 2026. Advances in Intelligent Processing of Seismic Data: Focal Mechanisms, Fault Zone Head Waves and Dynamic Triggering Detection and Analysis. Earth Science, 51(1): 56-73. doi: 10.3799/dqkx.2025.252

Citation:

Piao Jian, Xiong Jian, Zheng Dingchang, Wang Longtan, Yun Naidan, Pei Weilai, Zhou Yijian, Zhou Shiyong, 2026. Advances in Intelligent Processing of Seismic Data: Focal Mechanisms, Fault Zone Head Waves and Dynamic Triggering Detection and Analysis. Earth Science, 51(1): 56-73. doi: 10.3799/dqkx.2025.252

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Advances in Intelligent Processing of Seismic Data: Focal Mechanisms, Fault Zone Head Waves and Dynamic Triggering Detection and Analysis

doi: 10.3799/dqkx.2025.252

1.
School of Earth and Space Sciences, Peking University, Beijing 100871, China
2.
Department of Artificial Intelligence and Data Science, Guangzhou Xinhua University, Guangzhou 510520, China
3.
Earthquake Administration of Yunnan Province, Kunming 650224, China
4.
Department of Earth and Space Science, Southern University of Science and Technology, Shenzhen 518055, China
5.
Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China
6.
Division of Geological and Planetary Sciences, California Institute of Technology, California 91125, America

Received Date: 2025-08-14
Publish Date: 2026-01-25

Abstract

Abstract

In recent years, the rapid accumulation of massive digital seismic observations has created an urgent demand for efficient and intelligent data-processing methods. This paper presents a suite of new intelligent approaches to seismic data processing developed by our research group, including: POSE, an automatic P-wave first-motion polarity determination method based on Order Statistics and Entropy theory; an automatic detection algorithm for fault zone head waves designed to identify bimaterial interfaces; and HiFi, a method for detecting remote dynamic triggering based on the High-Frequency Power Integral Ratio. These methods not only significantly enhance the resolution of focal mechanism solutions and stress field inversions for small earthquakes, but also provide new tools for characterizing medium contrasts across faults and for investigating how dynamic stress perturbations modulate small earthquake activity. Through application to the 2023 Turkey earthquake doublet and the 2025 M_w 7.7 Mandalay, Myanmar earthquake, we demonstrate the advantages of POSE in focal mechanism determination and regional stress field inversion, the effectiveness of fault zone head-wave detection in revealing velocity contrasts across bimaterial fault interfaces, and the robustness of the HiFi method in identifying long-range dynamic triggering associated with large earthquakes. These new observations offer important support for fault-zone structural imaging, rupture dynamics studies, and seismic hazard assessment, and highlight the broad prospects of intelligent techniques in seismological research.
- intelligent method for seismic data processing,
- dynamic earthquake triggering,
- fault zone head wave P wave first-motion,
- focal mechanism,
- seismology,

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References(74)

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