Suppression of random microseismic noise based on complete ensemble empirical mode decomposition with adaptive noise of TFPF

被引：0

作者：

Chen Y. ^{[1
]}

Cheng H. ^{[1
]}

Gong E. ^{[1
]}

Xue L. ^{[1
]}

机构：

[1] Key Laboratory of Ministry of Education on Safe Mining of Deep Metal Mines, Northeastern University, Shenyang

来源：

Shiyou Diqiu Wuli Kantan/Oil Geophysical Prospecting | 2021年 / 56卷 / 02期

关键词：

Denoising; Empirical mode decomposition (EMD); Microseism; Sample entropy (SE); Time-frequency peak filtering (TFPF);

D O I：

10.13810/j.cnki.issn.1000-7210.2021.02.003

中图分类号：

学科分类号：

摘要：

Microseismic monitoring is widely applied in unconventional oil and gas fields, and supports the production and reserve increase of oil and gas fields. Because microseismic data are non-stationary, conventional denoising methods are not effective. This paper proposes a time-frequency peak filtering (TFPF) method of adaptive white noise based on the sample entropy (SE) complete set of empirical mode decomposition (CEEMDAN) to suppress noises while preserving effective signals. First raw microseismic data are decomposed into several IMFs of intrinsic modal components by CEEMDAN. Then after calculating the sample entropy, the IMFs are divided into two groups - one group will be filtered and the other will be left alone. The former group is TFPF filtered after selecting filter windows, and reconstructed with the latter to get final filtered signals. Application to theoretical model and field data has shown that the noise suppression method proposed in the paper is more effective than traditional EMD and constant-window TFPF denoising methods. © 2021, Editorial Department OIL GEOPHYSICAL PROSPECTING. All right reserved.

引用

页码：234 / 241

页数：7

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