According to the surface microseismic effective signal characteristics and data acquisition methods,combined with
microseismic signal higher-order cumulant statistical characteristic analysis,considering the different distribution
characteristics of effective signal and noise in the time and space direction,we discuss the fourth-order cumulants
estimation method of surface microseismic signal in time and space domain.Considering the advantages of Bayesian
estimation method for week signal estimation,we study self-adaptive algorithm of fourth-order cumulant based on
Bayes framework,take the joint probability density function of signal fourth-order cumulant as that of original signal
to carry out maximum posterior estimation,to establish fourth-order cumulant Bayesian estimiation method for
surface microseismic data.While extracting weak signals,useless relevant signals would be extracted,so the weak
effective signals are difficult to recognize.As we all know,regional relevant noise is evenly distributed in time
direction and effective signal is locally distributed,in terms of the characteristic,we propose adopting self-adaptive
subtraction to remove the regional relevant noise in Bayesian estimation results.By analyzing the method
series,effective extraction method for surface microseismic effective signals is formed.The method has obtained
good result in the actual data application.
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