Synchrosqueezing-based Transform and its Application in Seismic Data Analysis

Seismic waves are non-stationary due to its propagation through the earth. Time-frequency transforms are suitable tools for analyzing non-stationary seismic signals. Spectral decomposition can reveal the non-stationary characteristics which cannot be easily observed in the time or frequency representation alone. Various types of spectral decomposition methods have been introduced by some researchers. Conventional spectral decompositions have some restrictions such as Heisenberg uncertainty principle and cross-terms which limit their applications in signal analysis. In this paper, synchrosqueezingbased transforms were used to overcome the mentioned restrictions; also, as an application of this new high resolution time-frequency analysis method, it was applied to random noise removal and the detection of low-frequency shadows in seismic data. The efficiency of this method is evaluated by applying it to both synthetic and real seismic data. The results show that the mentioned transform is a proper tool for seismic data processing and interpretation.