Acta Scientiarum Naturalium Universitatis Pekinensis ›› 2018, Vol. 54 ›› Issue (2): 361-372.DOI: 10.13209/j.0479-8023.2017.079

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Automatic Microseismic Event Detection and Arrival Picking Based on Waveform Cross-Correlation

WEI Mengyi1, TAN Yuyang1,2, MAO Zhonghua3, FENG Gang3, HU Tianyue1,†, HE Chuan1,†   

  1. 1. Institute of Oil & Gas, School of Earth and Space Sciences, Peking University, Beijing 100871
    2. School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026
    3. Shengli Branch, Sinopec Geophysical Company, Dongying 257086
  • Received:2016-12-20 Revised:2017-01-10 Online:2018-03-20 Published:2018-03-20
  • Contact: HU Tianyue, E-mail: tianyue(at); HE Chuan, E-mail: chuanhe_pku(at)


魏梦祎1, 谭玉阳1,2, 毛中华3, 冯刚3, 胡天跃1,†, 何川1,†   

  1. 1. 北京大学地球与空间科学学院石油与天然气研究中心, 北京 100871
    2. 中国科学技术大学地球和空间科学学院, 合肥 230026
    3. 中国石油化工集团公司石油工程地球物理有限公司胜利分公司, 东营 257086
  • 通讯作者: 胡天跃, E-mail: tianyue(at); 何川, E-mail: chuanhe_pku(at)
  • 基金资助:


Generally, a cluster of seismic events which share similar source locations and focal mechanisms will show similar waveforms on the record. Based on this assumption, a method have been developed for microseismic event detection and arrival picking based on waveform cross-correlation. This method achieves moveout correction for the seismic records based on cross-correlation functions, then calculates a multi-channel semblance coefficient to identify the microseismic events. Meanwhile, the seismic records after moveout correction are superposed. The STA/LTA method is adopt to pick the arrivals for the stacked traces, the arrival times of the microseismic events are then automatically obtained. The performance of the method is evaluated using both synthetic and real datasets. Analysis of the results demonstrates that the proposed method can not only detect the microseismic events, but also obtain relatively accurate arrival picks at the same time.

Key words: microseismic, event detection, arrival picking, cross-correlation function, moveout correction


根据具有相似震源位置及破裂机理的微地震事件通常在地震记录上表现出相似波形特征的原理, 提出一种基于波形互相关的微地震事件自动识别及初至拾取方法。首先, 通过计算道间互相关函数, 对微地震记录进行时差校正; 然后, 通过计算道间相似系数的方法识别连续地震记录中的微地震事件。在完成事件识别的同时, 对时差校正后的多道记录进行叠加, 并采用STA/LTA方法对叠加道进行初至拾取, 结合各道间的时差信息即可获得各道微地震事件的初至到时。为了检验所提方法的可行性和有效性, 分别对模型数据和实际资料进行处理,结果表明利用所提方法可以在有效地识别微地震事件的同时, 得到较为准确的初至拾取结果。

关键词: 微地震, 事件识别, 初至拾取, 互相关函数, 时差校正

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