ACTA Scientiarum Naturalium Universitatis Pekinensis
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. 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; † Corresponding authors, E-mail: tianyue@pku.edu.cn (HU Tianyue), chuanhe_pku@163.com (HE Chuan)
Abstract 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
近年来, 随着非常规油气资源勘探开发技术逐渐成熟, 水力压裂微地震监测技术得到快速发展。微地震监测是通过观测分析由岩石破裂或错断导致的微小地震事件来监测地下人工裂缝发育过程与发育状态的地球物理技术, 主要用于在水力压裂作业
过程中解释裂缝的走向、方位和几何形态以及评价压裂效果。目前, 微地震监测技术已成功地应用于油气田开发、矿山开采以及地质灾害监测等多个领域, 其有效性和可靠性得到广泛认可[16]。微地震事件的识别及初至拾取是微地震数据处