A Concentrated Time-Frequency Method for Reservoir Detection Using Adaptive Synchrosqueezing Transform

The synchrosqueezing transform (SST) is an effective technique to concentrate the time-frequency (TF) energy and to retrieve the components of a non-stationary multicomponent signal. Therefore, it has been widely used to process and interpret seismic data. However, due to the fixed window width of the short-time Fourier transform (STFT), the STFT-based SST (FSST) is not well suitable for the characterization of the oil and gas reservoirs with varying layer thickness. Here, an adaptive SST is employed to characterize the features of the seismic signals for identifying the oil reservoirs with varying thickness. Overall, the proposed method is based on STFT with time-varying windows. For the local harmonic wave approximation and well-separated condition of a non-stationary multicomponent signal, the adaptive STFT is windowed with the Gaussian function. Compared with the conventional FSST, the adaptive FSST (AFSST) provides the TF concentration with better concentration and separates the components more accurately. In this work, both synthetic model and field seismic data are applied to validate the AFSST method, demonstrating that the AFSST method can precisely distinguish the stratigraphic characteristics.