基于大数据的强震临震前地震背景噪声异常分析--以2013年芦山7.0级地震为例

Big Data-based Abnormal Analysis of Seismic Background Noise before Strong Earthquake--The Case of the Lushan M_(S)7.0 Earthquake

目前针对强震临震前震动信号的拾取和分析基本都是在有限的频带内开展,且分析的数据量时空范围有限。本文提出一种基于大数据的地震背景噪声计算和分析方法,对海量地震观测数据进行分布式噪声功率谱计算,数据采用2013年3—4月的四川地震台网记录的连续波形数据。通过对2013年四川芦山7.0级地震前四川地震台网记录的50Hz~200s范围内的多个频点时序变化进行分析,发现芦山地震距震中50km范围内的MDS台和BAX台在震前水平方向30~150s周期上噪声出现增强10~20dB且持续3~5天的情况,垂直向未发现明显变化,同时超出50km范围内的台站也未有明显变化。这种长周期异常变化很难通过传统的地震动信号拾取来发现,表明本文提出的强震临震异常分析方法可以用于发现和分析震前的长周期异常信号。

The current research work for picking up and analyzing the pre-shock vibration signals of strong earthquakes is often carried out in a limited frequency band,and the amount of data analyzed has a limited spatial and temporal range. In this paper,we propose a method to calculate and analyze seismic background noise directly based on big data by using clusters for distributed noise power spectrum calculation and storage of calculation results for massive seismic observation data. The continuous waveform data from Sichuan station network from March to April, 2013 was used to analyze the temporal variation of multiple frequency points from 50Hz-200s of recorded data from seismic stations before Lushan earthquake. We found that the MDS and BAX stations within 50km of the epicenter of the Lushan earthquake showed a noise enhancement of about 10~20dB in the horizontal direction for 3~5 days in the 30~150s period in the low frequency band,while no significant changes were found in the vertical direction. This long-period anomaly is difficult to be detected by traditional ground shaking signal pickup,which suggests that the proposed method of strong-motion seismic anomaly analysis is capable of detecting and analyzing long-period anomalous signals.