Multisynchrosqueezing Generalized S-Transform and Its Application in Tight Sandstone Gas Reservoir Identification

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS(2022)

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摘要
Synchrosqueezing transform (SST) is a high-resolution time-frequency (TF) analysis (TFA) approach for seismic spectral anomaly detection. Here, a novel method called multisynchrosqueezing generalized S-transform (GST) is proposed and applied for the identification of tight sandstone gas reservoirs. In this method, a signal model named the Gaussian-Modulated Signal Model (GMSM) is introduced to estimate the instantaneous frequency (IF) of the signal in the GST's spectrum. Then, an iterative algorithm constantly approximating IF is constructed to provide a highly energy-concentrated TF representation while allowing for signal reconstruction. Compared to some advanced TFA methods, the proposed method has better energy-concentrated performance due to an accurate estimate of the IF. A simulated signal and field data are employed to verify the effectiveness of the proposed method. It is concluded that the proposed method has great potential as a TFA technique for identifying tight sandstone gas reservoirs.
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关键词
Reservoirs, Transforms, Estimation, Time-frequency analysis, Noise measurement, Geology, Continuous wavelet transforms, Instantaneous frequency (IF), multisynchrosqueezing generalized S-transform (GST), synchrosqueezing transform (SST), tight sandstone gas reservoirs, time-frequency (TF) analysis (TFA)
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