Eliminating the Fading Noise in Distributed Acoustic Sensing Data
Xiangge He, Zhi Cao, Peng Ji, Lijuan Gu, Shi-peng Wei, Bo Fan, Min Zhang, Hailong Lu
Abstract
Fading noise is a crucial problem in distributed acoustic sensor (DAS) system which can severely degrade the system’s ability on distributed detection. In this paper, we systematically studied the mechanism and characteristics of fading noise in dual-pulse heterodyne demodulated DAS system. Results show that fading noise not only causes big fading errors in signal, but also leads to amplitude distortion of seismic wave. We propose the sort and average over trace (SAOT) algorithm to eliminate the fading noise of DAS data. After implementation of the algorithm on the simulated DAS data, the big fading error can be eliminated 100%, and the residual standard deviation can be reduced by 32 dB. Meanwhile, the correlation between the processed data and the noise-free data is improved by 29 dB. Then the performance of the algorithm is further verified by laboratory experiment, achieving a residual standard deviation reduction of 33 dB. Finally, the algorithm can perfectly eliminate the fading noise in vertical seismic profile (VSP) DAS data and surface seismic DAS data obtained at the oilfield site.