| 基于多道信噪能量统计的微地震有效信号识别方法 |
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| 引用本文： | 潘树林,崔庆辉,秦子雨,闫柯.基于多道信噪能量统计的微地震有效信号识别方法[J].物探化探计算技术,2019(4):527-533. |
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| 作者姓名： | 潘树林 崔庆辉 秦子雨 闫柯 |
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| 作者单位： | 西南石油大学地球科学与技术学院;胜利油田分公司物探研究院;中国石油天然气股份有限公司西南油气田分公司 |
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| 基金项目： | 国家自然基金项目(NSFC 41674095);“油气藏地质及开发工程”国家重点实验室开放基金项目(PLN201733);天然气地质四川省重点实验室开放基金项目(2015trqdz03) |
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| 摘 要： | 在微地震监测中有效微地震信号的识别是关键步骤。常规的微地震有效信号识别方法基于单道长短时窗能量比,受噪音影响较大,对于信噪比较低的事件无法准确识别。利用多道记录数据之间的信号相关性好而信号与噪音相关性差的特点,通过记录道自相关求取总能量和相邻记录互相关求取信号能量,以有效信号能量所占比即含信能量比作为门槛值进行有效信号识别,信号识别过程中利用多道互相关对噪音进行了有效压制,提高了微地震信号识别的压噪能力,通过模型数据和实际资料处理验证了方法的有效性。
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| 关 键 词： | 微地震 信号识别 多道相关 含信能量比 |
Microseismic event identification method based on multi-channel |
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| PAN Shulin,CUI Qinghui,QIN Ziyu,YAN Ke.Microseismic event identification method based on multi-channel[J].Computing Techniques For Geophysical and Geochemical Exploration,2019(4):527-533. |
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| Authors: | PAN Shulin CUI Qinghui QIN Ziyu YAN Ke |
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| Institution: | (School of Earth Science and Technology,Southwest Petroleum University,Chengdu 610500,China;Geophysical Research Institute,Shengli Oilfield Company,SINOPEC,Dongying 257022,China;Petro China Southwest Oil & Gasfield Company,Chengdu 610051,China) |
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| Abstract: | The identification of effective microseismic signals in microseismic monitoring is a key step.Conventional microseismic effective signal identification methods are based on the energy ratio of long and short time window in one sensor data,which is greatly affected by noise and cannot accurately identified events with low SNR.This paper uses the characteristics of good correlation of microseismic signal between multiple sensors and poor correlation of noise between multiple sensors.The total energy of record can be obtained through self-correlation of record and the energy of microseismic signal can be obtained through cross-correlation between adjacent records,the microseismic signal can be identified according to energy percent threshold.The noise is suppressed during the signal identification process,so the method proposed in this paper have a good ability to suppressed noise.The effect of the method was verified by model data and real data processing. |
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| Keywords: | microseismic event identification multiple traces cross-correlation signal energy percent |
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