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Simultaneous enhancement and detection of microseismic events based on autocorrelation

LEI FENG,  ZHIXIAN GUI* ,  ZHI LI CHEN,  YIZHUO LIU,  QIANG WEI
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Key Laboratory of Exploration Technologies for Oil and Gas Resources (Yangtze University), Ministry of Education, Wuhan 430100, P.R. China.,
Cooperative Innovation Center of Unconventional Oil and Gas (Yangtze University), Wuhan 430100, P.R. China.,
College of Geophysics and Petroleum Resources, Yangtze University, Wuhan 430100, P.R. China.,
JSE 2023, 32(4), 337–356;
Submitted: 20 March 2023 | Accepted: 5 July 2023 | Published: 1 August 2023
© 2023 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

Feng, L., Gui, Z.X., Chen, Z., Liu, Y.H. and Wei, Q., 2023. Simultaneous enhancement and detection of microseismic events based on autocorrelation. Journal of Seismic Exploration, 32: 337-356. Microseismic monitoring is the main method of hydraulic fracturing evaluation, which is realized by locating the source. Before locating the source, it is necessary to determine the position of the valid signal in the receiving channel. But the data received is very complicated, including the dead trace, strong noise, invalid data, etc. In order to solve some cases, Methods of data enhancement and data detection are mentioned. However, there are some problems in the application of the enhancement method and detection method in microseismic monitoring. Therefore, This research improves the enhancement method to reduce the suppression of the P-wave by the original method and proposes a more efficient detection method based on autocorrelation. The test of synthetic data and filed microseismic data shows that the enhancement method improved and the detection method is effective.

Keywords
microseismic monitoring
denoising
detection
autocorrelation
sensor array
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Journal of Seismic Exploration, Print ISSN: 0963-0651, Published by AccScience Publishing
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