Application of high-resolution processing in seismic data based on an improved synchrosqueezing transform

Abstract

This study proposes a high-resolution processing technique for seismic data based on the improved synchrosqueezing transform (SST). The SST rearranges the complex spectrum of the wavelet transform along the frequency axis. However, the energy is not concentrated in the position with the faster frequency change rate. To overcome these problems, the proposed method first transformed the seismic signal into an analytical one via Hilbert transformation and then determined the phase correction value (x0(t)) before and after the transformation. This was achieved using the instantaneous frequency attribute (ω(t)) of the analytical signal and a specific frequency (ω0) selected as the dominant frequency of the input data to adjust the change rate of the signal frequency before the SST falls close to zero, which can improve the time–frequency resolution after compression transformation. The essence of this method only adjusts the phase of the signal before and after transformation, without affecting the inverse expression of the SST. The one- and two-dimensional model data results show that the proposed method can better identify the time–frequency distribution characteristics of seismic signals and improve their resolution and the focusing effect in the time–frequency domain. The proposed method shows good prospects for application in gas reservoir detection and identification.