石油物探2017，Vol.56Issue(5)：658-666,9.DOI:10.3969/j.issn.1000-1441.2017.05.006
基于经验模态分解互信息熵与同步压缩变换的微地震信号去噪方法研究
Microseismic data denoising method based on EMD mutual information entropy and synchrosqueezing transform
摘要
Abstract
On the basis of the characteristics of randomness,non-stationarity,time-frequency coupling of microseismic data,and of the problem of modal aliasing in empirical mode decomposition (EMD),this paper proposes a microseismic data denoising method based on EMD mutual information entropy and synchrosqueezing transform (SST).First,the microseismic signal is decomposed by EMD to acquire the intrinsic mode function (IMF) sequencing from high to low frequency.Next,the mutual information entropy of adjacent IMF components is calculated to identify the boundary between the high-frequency and the low-frequency part.Finally,the effective signal of the high-frequency part is extracted by the SST and reconstructed with the low-frequency part to achieve an ef fective microseismic data denoising.We applied the method to synthetic data sets with different noise intensities and to field data,and the results showed that this method can better remove the aliasing noise,extract the effective signal,and improve the SNR,compared with denoising methods that directly discard the high-frequency components.关键词
微地震信号/经验模态分解/同步压缩变换/互信息熵/重构/噪声压制Key words
microseismic/empirical mode decomposition/synchrosqueezing transform/mutual information entropy/reconstruction/denoising分类
天文与地球科学引用本文复制引用
秦晅,蔡建超,刘少勇,卞爱飞..基于经验模态分解互信息熵与同步压缩变换的微地震信号去噪方法研究[J].石油物探,2017,56(5):658-666,9.基金项目
国家重点研发计划(2016YFC060110304)、国家自然科学基金(41572116)、中央高校基本科研业务费专项资金(CUG160602)联合资助.This research is financially supported by the State Key Program of National Natural Science of China (Grant No.2016YFC060110304),the National Nature Science Foundation of China (Grant No.41572116) and the Fundamental Research Funds for the Central Universities (Grant No.CUG160602). （2016YFC060110304）
