基于波形聚类分析的微地震监测事件类型判别及应用

以不同类型微地震监测事件在波形相似性上的差异为基础,结合发生位置、走时规律和偏振方向等方面的特征,提出一种基于波形聚类分析的微地震监测事件类型判别方法。首先使用常规的微地震事件识别算法,快速地得到待分类的疑似事件;然后进行波形聚类分析,结合事件的属性特征,实现对不同类型微地震事件及噪声事件的分类和判别。分类结果可用于波形模板匹配,识别同类的低信噪比微地震事件;还可将所有同类事件作为一个整体,采用全局优化手段提高初至拾取的精度。

Microseismic Monitoring Events Classification Based on Waveform Clustering Analysis and Application

Based on the difference of waveform similarity between different types of microseismic monitoring events and combined with their characteristics in occurrence location, traveling time and polarization direction etc., a method for classifying microseismic monitoring events based on waveform clustering analysis is proposed. Firstly unclassified events can be identified rapidly using conventional microseismic event detection methods, then similar events are grouped based on waveform clustering analysis, finally the types of microseismic events or noise events are determined combining the attribute characteristics. Classified microseismic events can be further used for template matching technique to finely detect similar events with low signal-to-noise ratio. Meanwhile the global optimization approach which aims to improve the accuracy of arrival time picking can be also performed by taking similar microseismic events as a whole.