利用区域台网快速自动反演中等强度地震矩张量

地震 ›› 2014, Vol. 34 ›› Issue (2): 65-73.

利用区域台网快速自动反演中等强度地震矩张量

邱毅, 金星, 李军, 朱耿青, 邵平荣, 徐嘉隽

福建省地震局, 福建福州 350003

发布日期:2020-07-14
作者简介:邱毅(1984-), 男, 福建武夷山人, 工程师, 主要从事地震学和地震工程等研究。
基金资助:
国家科技支撑计划(2009BAK55B00)和中国地震局地震科技星火计划(XH12026Y)联合资助

Automated and Rapid Moment Tensor Inversion for Moderate Earthquakes using Regional Seismic Network

QIU Yi, JIN Xing, LI Jun, ZHU Geng-qing, SHAO Ping-rong, XU Jia-jun

Earthquake Administration of Fujian Province, Fuzhou 350003, China

Published:2020-07-14

摘要/Abstract

摘要： 震后快速得到地震矩张量, 可以更好地为烈度速报、应急救援和震后趋势判定等服务。本文基于中国区域地震台网现状, 对Dreger的矩张量反演方法进行改进。结合区域地震速报系统, 将系统触发、地震相关信息与地震波形记录获取、矩张量反演计算和最佳解挑选等过程实现自动化, 建立了地震矩张量快速自动反演系统。将该系统在线运行于福建地震台网, 实现了对闽台地区中等强度地震的矩张量在线快速自动反演。将反演结果与其他研究机构的结果对比, 验证了本文方法的可靠性。

关键词: 区域地震台网, 地震矩张量, 自动快速, 中等强度地震, 闽台地区

Abstract: Obtaining quickly the moment tensor solution could offer help for rapid intensityreporting,seismic emergency and succor, post-seismic tendency determination, and so on. In this paper, an automated and rapid moment tensor inversion system had been constructed using the regional broadband stations.Based on regional seismic network in China, we improved the seismic moment tensor inverse software developed by Dreger. The systemwas triggered by the rapid earthquake determination systemused in seismic network. The system obtained the earthquake information and seismic waveform data automatically.Itwas realized that the automation of the moment tensor inversion and selecting the best solution of seismic moment tensorprocess. The system had been applied to Fujian seismic network, and compared the results with other research institutions to verify the reliability of the system.

Key words: Regional seismic network, Seismic moment tensor inversion, Moderate earthquake, Fujian-Taiwan region

中图分类号:

P315.7

邱毅, 金星, 李军, 朱耿青, 邵平荣, 徐嘉隽. 利用区域台网快速自动反演中等强度地震矩张量[J]. 地震, 2014, 34(2): 65-73.

QIU Yi, JIN Xing, LI Jun, ZHU Geng-qing, SHAO Ping-rong, XU Jia-jun. Automated and Rapid Moment Tensor Inversion for Moderate Earthquakes using Regional Seismic Network[J]. EARTHQUAKE, 2014, 34(2): 65-73.

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