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.

Synchrosqueezing Transform Based on Frequency-Domain Gaussian-Modulated Linear Chirp Model for Seismic Time–Frequency Analysis

“…Bing et al [24] presented a seismic time-frequency analysis method based on a time-reassigned synchrosqueezing transform (TSST) to highlight subtle geological structures, where the time-frequency coefficients are reassigned in the time direction rather than in the frequency direction. Yu et al [25] developed a high-resolution processing technique for the detection of seismic activities in gas reservoirs and carried out identification using the improved synchrosqueezing transform, which only adjusts the phase of the signal before and after transformation. Paksima et al [26] analyzed the capabilities of a high-resolution synchrosqueezing S-transform on nonstationary seismic signals and used it to describe the gas accumulation zones and accurately separate two different gas reservoir formations based on enhanced resolution in both time and frequency directions.…”