1. National Institute of Defense Technology,Southwest University of Science and Technology,Mianyang 621010,China 2. Fundamental Science on Nuclear Wastes and Environmental Safety Laboratory,Southwest University of Science and Technology,Mianyang 621010,China 3. Sichuan University of Science & Engineering,Zigong 643002,China; 4. State Key Laboratory of Geohazard Prevention and Geoenvironment Protection,Chengdu University of Technology,Chengdu 610059,China
It is inevitable to mix up non-stationary random noise in the process of microseismic signal acquisition.However,the practice shows that the traditional linear filtering and spectrum analysis methods are not idealistic for this mixed signal.In view of such a situation,this paper presents a new method to suppress nonstationary random noise.Firstly,the Ensemble Empirical Mode Decomposition (EEMD) is carried out for noise-containing microseismic signals,and a series of Intrinsic Mode Functions (IMF) with different frequencies components are obtained.In order to accurately identify the signal and noise in these IMF components,the authors calculated the sample entropy of each IMF in this paper.The threshold value of sample entropy was used to extract the IMF components conformable to the characteristics of microseismic signal,and these IMF components are reconstructed in order to suppress random noise.The proposed method has been applied to simulated data and measured microseismic data,and it is indicated that the method has ideal effect for noise reduction.
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