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

Pingping Bing (), Wei Liu, Haoqi Zhang, Li Zhu, Guiping Zhu, Jun Zhou and Binsheng He ()
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Pingping Bing: Hunan Provincial Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, Changsha Medical University, Changsha 410219, China
Wei Liu: College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing 100029, China
Haoqi Zhang: Hunan Provincial Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, Changsha Medical University, Changsha 410219, China
Li Zhu: Hunan Provincial Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, Changsha Medical University, Changsha 410219, China
Guiping Zhu: Hunan Provincial Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, Changsha Medical University, Changsha 410219, China
Jun Zhou: Hunan Provincial Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, Changsha Medical University, Changsha 410219, China
Binsheng He: Hunan Provincial Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, Changsha Medical University, Changsha 410219, China

Mathematics, 2023, vol. 11, issue 13, 1-17

Abstract: The synchrosqueezing transform (SST) has attracted much attention as a post-processing technique since it was proposed. In recent years, improvements to SST have been made. However, the existing methods are mainly based on the time-domain signal model, and the weak frequency modulation assumption for the components composing the signal is always taken into account. Thus, the signals characterized by a rapidly changing instantaneous frequency (IF) may fail to be adequately tackled. To address this problem, the paper presents a novel seismic time–frequency analysis method via synchrosqueezing transform where a frequency-domain Gaussian modulated linear chirp model is utilized to deduce the SST. The group delay (GD) rather than the IF estimator is implemented to compute an estimation of the ridge. Furthermore, a new synchrosqueezing operator is constructed to rearrange the energy around the ridge. A synthetic example verifies the efficiency and robustness of the proposed SST method, which generates better results than some classic time–frequency analysis (TFA) approaches, e.g., short-time Fourier transform (STFT) and STFT-based SST (FSST). A field dataset further demonstrates this method’s potential in the delineation of subsurface geological structures.

Keywords: time–frequency representation; synchrosqueezing transform; chirp model; time localization; geological structures (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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