A migration-based location method using improved waveform stacking for microseismic events in a borehole system

Acta Geophysica

article

Mao, Qinghui¹  Azeem, Tahir³  Zhang, Xuliang⁴  Zhong, Yu⁵  Fang, Yuan⁶  Zhang, Yunxiao⁷ 

[1] Key Laboratory of Exploration Technologies for Oil and Gas Resources (Yangtze University), Ministry of Education;Hubei Cooperative Innovation Center of Unconventional Oil and Gas, Yangtze University;Department of Earth Sciences, Quaid-I-Azam University;Bureau of Geophysical Prospecting;Institute of Geophysics and Geomatics, China University of Geosciences;Development and Research Center;Oil and Gas Survey, China Geological Survey

关键词: Microseismic event;    Migration-based location;    Improved waveform stacking;    Hydraulic fracturing;    SNR;   

DOI  :  10.1007/s11600-020-00488-z

学科分类：地球科学(综合)

来源: Polska Akademia Nauk * Instytut Geofizyki

【 摘 要 】

The migration-based microseismic event location methods using waveform stacking algorithms are widely used for hydro-fracturing monitoring. These methods have the advantage of not requiring the accurate first arrival time around a detected event, which is more suitable for noisy data than classical travel time-based methods. However, accuracy of these methods can be affected under the condition of relatively low signal-to-noise ratio (SNR). Therefore, in order to enhance the location accuracy of microseismic events in a borehole system, we have proposed a migration-based location method using improved waveform stacking with polarity correction based on a master-event technique, which optimizes the combination way of P- and S-wave waveform stacking. This method can enhance the convergence of the objective function and the location accuracy for microseismic events as compared to the conventional waveform stacking. The proposed method has been successfully tested by using synthetic data example and field data recorded from one downhole monitoring well. Our study clearly indicates that the presented method is more viable and stable under low SNR.

【 授权许可】

Unknown