Signal-to-noise ratio enhancement for downhole microseismic data based on 3D shearlet transform

Abstract

Downhole microseismic data are characterized for their high frequency and small amplitude, which bring great difficulty for noise suppression. We present a random noise attenuation method for downhole microseismic data based on the 3D shearlet transform (3DST). In contrast to the 2D shearlet, 3DST takes into account the correlation among three components of downhole microseismic. With the help of correlation among the data, downhole microseismic data are reassembled into a new 3D matrix and then transformed to the shearlet domain. After the analysis of the coefficients’ energy and the high-order cumulant on each scale, an efficient threshold function is proposed. We apply a small threshold to the coefficients associated with the signal’s scales, and a large threshold is chosen for the scales of the noise. Experimental results indicate that the algorithm significantly improves the signal-to-noise ratio of the microseismic data and effectively preserves a valid signal.