岩土力学 ›› 2019, Vol. 40 ›› Issue (2): 767-776.doi: 10.16285/j.rsm.2017.1647

• 岩土工程研究 • 上一篇    下一篇

基于波形参数的微震P波到时拾取值质量控制方法

朱梦博,王李管,刘晓明,彭平安,赵嘉轩   

  1. 1. 中南大学 资源与安全工程学院,湖南 长沙 410083;2. 中南大学 数字矿山研究中心,湖南 长沙 410083
  • 收稿日期:2017-08-07 出版日期:2019-02-11 发布日期:2019-02-19
  • 通讯作者: 王李管,男,1964年生,博士,教授,博士生导师,主要从事数字矿山方面的研究工作。E-mail: liguan_wang@163.com E-mail:mengbo_zhu@163.com
  • 作者简介:朱梦博,男,1992年生,博士研究生,主要从事数字矿山、微震监测系统开发方面的研究工作。
  • 基金资助:
    国家重点研发计划项目(No. 2017YFC0602905);中南大学中央高校基本科研业务费专项资金项目(No. 2017zzts568)。

A quality control method for microseismic P-wave phase pickup value based on waveform parameters

ZHU Meng-bo, WANG Li-guan, LIU Xiao-ming, PENG Ping-an, ZHAO Jia-xuan   

  1. 1. School of Resources and Safety Engineering, Central South University, Changsha, Hunan 410083, China; 2. Digital Mine Research Center, Central South University, Changsha, Hunan 410083, China
  • Received:2017-08-07 Online:2019-02-11 Published:2019-02-19
  • Supported by:
    This work was supported by the National Key Research and Development Program of China (2017YFC0602905) and the Fundamental Research Funds for the Central Universities of Central South University (2017zzts568).

摘要: 微震事件中常常包含一些异常信号、强噪声干扰信号和弱信号,这些通道信号的P波到时自动拾取精度往往很低,甚至拾取错误。目前国内外微震监测系统进行自动定位时,并不对各个P波到时拾取值预先筛选,而需要技术人员手动剔除或修正部分无效P波到时,然后才能进行正确定位。为此,首先引入了一种Akaike信息准则(AIC)两步骤拾取算法,并基于某深埋隧道微震监测案例定量分析了P波到时拾取误差与震源定位精度之间的关系,从而引入了P波到时拾取值容许误差的概念。然后,利用AIC两步骤拾取算法拾取微震波形的P波到时,并计算各项波形参数,进行大量统计,深入研究了影响P波到时拾取精度的波形参数。以容许误差为基准,将P波到时拾取值分为有效(标签为1)和无效(标签为?1)两类,并以相应的波形参数为数据输入,采用支持向量机方法(SVM)训练数据,最终建立了P波到时拾取值质量控制模型。实际应用表明:P波到时拾取值质量控制方法能有效剔除错误拾取值,从而大幅度提高数据自动处理效率和震源定位精度。

关键词: P波到时拾取, AIC算法, 波形参数, 质量控制, 震源定位

Abstract: A microseismic event often contains some abnormal channel signals, strong noise interference signals and weak signals. The picking accuracy of these channel signals’ P-wave phase arrivals is often low, and even those P-picks are false. Currently, the invalid P-picks are not screened out before automatic source location in microseismic monitoring system, and the manual intervention need to be carried out. To solve this difficult problem, a modified Akaike information criterion (AIC) picker was proposed firstly. Secondly, the quantitative relationship between the P-picks accuracy and the source location accuracy was analyzed based on a microseismic monitoring case of a deeply buried tunnel, and then a new concept of P-pick admissible error was introduced. Furthermore, all kinds of microseismic signals’ P-wave phases were picked up by the modified AIC picker, and the corresponding waveform parameters were calculated. A great amount of statistic work has revealed the relationship between P-pick accuracy and waveform parameters. Finally, the P-picks were classified into valid group (tagged 1) and invalid group (tagged -1) based on the admissible error. And support vector machine (SVM) classifier was applied to build a forecasting model for identifying valid and invalid P-picks. Practical application shows that the invalid P-picks are identified correctly and effectively by this quality control method. The accuracy of microseismic source location is improved greatly after eliminating the invalid pickups.

Key words: P-wave phase identification, AIC picker, waveform parameters, quality control, source location

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[3] 张继红. 伞式自扩锚应用效果研究[J]. , 2006, 27(5): 842-845.
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