Time-frequency decomposition has been widely used in seismic data analysis. The short-time Fourier transform and wavelet transform are the popular methods to decompose a signal from time domain to time-frequency domain. However, the application of both approaches is restricted due to trade-offs between time and frequency resolution. In this paper, a new time-frequency decomposition approach based on synchrosqueezing transform (SST) is presented, which has a firm mathematical foundation and produces the improved time-frequency resolution. A non-stationary synthetic example shows that the SST can achieve higher resolution both in time and frequency compared with continuous wavelet transform (CWT). Field data examples demonstrate the potential of the SST in detecting low-frequency anomaly caused by hydrocarbon, which is helpful to delineate the location and extent of anomaly more clearly.


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