基于概率密度分布的地电场地震前兆异常提取方法  

Extracting Earthquake Precursors from Geoelectrical Data based on Probability Density Distribution

作　　者：于晨 卢军[1] 解滔[1] 岳冲[1] 王淑艳[2] 

机构地区：[1]中国地震台网中心,北京100045 [2]中国地质大学(北京),北京100083

出　　处：《地震》2017年第4期22-36,共15页Earthquake

基　　金：中国地震局监测预报司震情跟踪定向工作任务(2017010218)资助

摘　　要：随着地电场观测技术的不断提高,高采样率的观测资料中蕴含着丰富的与地下构造活动有关的信息,如何从高采样率的观测资料中提取有效的地震前兆异常,是目前地震电磁学科分析人员最为关注的问题之一。本文利用概率密度分布方法,分析了2013年芦山MS7.0地震和岷县漳县MS6.6地震震中周围9个地电场台站的观测数据,分析得到:在芦山地震和岷县漳县地震前,平凉台、古丰台和松山台出现高频异常信息,地电场干扰增强。据此分析,初步研究认为概率密度分布法是一种有效的地电场高频异常信息提取方法。With improvement of geoelectrical field observation technology,there is a great deal of tectonic information in high-frequency sampling observational data.How to extract useful earthquake precursor from these data is a key problem.We introduced the PDF（probability density function）method,analyzed the observational data of 9 geoelectrical stations near the epicenter of the Lushan M_S7.0 earthquake and Minxian and Zhangxian M_S6.6 earthquake.The results show that three geoelectrical data had high-frequency anomalies before the two earthquakes.On the basis of these results,we considered that PDF method has certain reliability and applicability to extract the high-frequency anomaly information from geoelectrical observational data.

关 键 词：地电场 概率密度分布 高频前兆异常 

分 类 号：P315.7[天文地球—地震学]