Time-synchroextracting of generalized S-transform and its application in fault identification

Abstract

Seismic signals are typical non-stationary signals, and time-frequency analysis method is a powerful tool for processing non-stationary signals, which is also widely used in seismic signal processing. S-transform is a frequently used time-frequency analysis method. However, the time and frequency resolution of S-transform is limited due to Heisenberg uncertainty principle. The post-processing method of time-frequency analysis can solve this problem by further calculation on the basis of the original time-frequency spectrum of the signal. In order to improve the time and frequency resolution, we propose a new time-frequency analysis post-processing method - time synchroextracting of generalized S-transform algorithm. We first deduce the group delay operator expression of the generalized S-transform, and then remove a large amount of fuzzy energy by extracting only the time-frequency coefficients at the group delay operator in the time-frequency spectrum to improve the time-frequency resolution. The comparative analysis of synthetic signals shows that the proposed algorithm has better time-frequency aggregation and can more accurately describe the time-frequency characteristics of seismic signals. We apply the proposed method to the fault identification of the field seismic data, and the results show that the coherent attribute slice extracted by the time-synchroextracting of the generalized S-transform can well describe the fault.