王亮^1,2,,
梁春涛^1,2,,
1. 地球勘探与信息技术教育部重点实验室(成都理工大学), 成都 610059
2. 地质灾害防治与地质环境保护国家重点实验室(成都理工大学), 成都 610059

基金项目: 国家自然科学基金（41674059，41340009）资助


详细信息

作者简介: 王亮, 男, 1989年生, 成都理工大学博士候选人, 主要从事震源观测方面的研究.E-mail: wangliang.seis@gmail.com

通讯作者: 梁春涛.E-mail: liangct@cdut.edu.cn

中图分类号: P315

收稿日期:2021-01-02
修回日期:2021-02-18
上线日期:2021-07-10

Detecting small earthquakes using the theoretical Green's function of virtual earthquakes as templates

WANG Liang^1,2,,
LIANG ChunTao^1,2,,
1. Key Laboratory of Earth Exploration and Information Techniques of Ministry of Education(Chengdu University of Technology), Chengdu 610059, China
2. State Key Laboratory of Geohazard Prevention and Geoenviroment Protection, (Chengdu University of Technology), Chengdu 610059, China


More Information

Corresponding author: LIANG ChunTao,E-mail:liangct@cdut.edu.cn

MSC: P315

--> Received Date: 02 January 2021
Revised Date: 18 February 2021
Available Online: 10 July 2021


摘要
摘要:搜寻小地震而得到更加完备的地震目录是地震学的基本课题.传统的匹配滤波方法用已知地震的波形与连续观测做互相关，可有效识别小地震.然而，一些地区缺乏早期观测或地震活动性低而无真实地震可做模板，造成传统匹配滤波法难以施展.使用虚拟地震的理论波形做模板可解决该问题.若使用的虚拟地震包含所有可能的震源机制，即离散地覆盖整个震源机制解空间，虚拟地震的数量将大量增加，导致计算量剧增.本研究借鉴裁剪-粘贴法（CAP）中对滑动互相关的处理方式，发展了以虚拟地震的理论格林函数为模板的匹配滤波方法（Green's function-based matched filter，简称为GFMF），在不改变计算结果的前提下通过减少滑动互相关的次数，节省计算时间.本文将该方法应用到加州一地震序列，凭借对震源位置和震源机制的网格搜索，得到了该序列的时空分布变化特征和该区域全部中等地震的震源机制.研究结果显示，虚拟地震可以用作模板来检测小地震以解决真实模板地震不足的问题.若不对虚拟地震的震源机制进行遍历，得到的地震数量将减少70%以上.这表明本研究对震源机制遍历的相关优化是重要的.
关键词: 地震检测/
匹配滤波/
模板匹配/
格林函数

Abstract:Detecting small earthquakes to get completer seismic catalogs is one primary topic of seismology. The traditional matched-filter method cross-correlates known earthquakes' waveforms with continuous waveforms, effectively detecting small earthquakes. However, some areas may lack early observations or have low seismic activity. Such areas cannot provide enough real earthquakes as templates, making it is challenging to implement the traditional matched-filter method. The theoretical waveform of the virtual earthquake as templates can solve the above problems. If the virtual earthquakes have varying focal mechanisms, the amount of calculation will increase significantly. We learn from the processing method of sliding cross-correlation in the CAP method and develop a Green's function-based matched filter (GFMF) method. GFMF can obtain the same results but need less computational time by optimizing the number of cross-correlation. We apply this method to a region in California and obtain the temporal evolution and spatial distribution characteristics of an earthquake sequence and all moderate earthquakes' focal mechanism in the region with grid searches of the source locations and focal mechanisms.The research results show that virtual earthquakes can be used as templates to detect small earthquakes to solve insufficient template earthquakes. The study results show the detection number will be reduced by more than 70% without the grid search of focal mechanisms, which shows that the optimization of the focal mechanism searching in this study is important.
Key words:Seismic events detecting/
Matched filter/
Template matching/
Green's function



PDF全文下载地址:

http://www.geophy.cn/data/article/export-pdf?id=3846e97d-7b0c-4730-a6e5-c853c032055d