High-resolution time–frequency analysis based on a synchroextracting adaptive S-transform and its application. (17th October 2022)

• Record Type: Journal Article
• Authors: Lin, Ying; Chen, Siyuan; Zhang, Guangzhi; Huang, Minmin; Wang, Baoli
• Is Part Of: Journal of geophysics and engineering. Volume 19:Number 5(2022)
• Page Start: 1124
• Page End: 1133
• Publication Date: 2022-10-17
• Subjects: synchroextracting transform (SET) -- synchroextracting adaptive S-transform (SEAST) -- sparse adaptive S-transform (SAST) -- dispersion attribute; Geophysics -- Periodicals; Prospecting -- Geophysical methods -- Periodicals; Engineering -- Periodicals; 622.1505
• DOI: 10.1093/jge/gxac068
• Languages: English
• ISSNs: 1742-2132

Abstract

Abstract: We propose synchroextracting adaptive S-transform (SEAST) by combining the adaptivity provided by the recently introduced 'Sparse Adaptive S-transform' (SAST) with the high resolution of synchroextracting spectral decomposition method. Traditional synchroextracting transforms are based on short-time Fourier transforms (STFTs) and their application is limited by having a fixed analysis window size for high and low frequencies and no multi-resolution features. The arbitrary window functions used in the SAST vary with frequency and amplitude, making it more suitable for non-stationary seismic signal analysis. The SEAST retains the multi-resolution advantages of adaptive S-transforms, while providing the strong time–frequency focus associated with synchroextracting transforms. The method was used to calculate seismic dispersion attributes and the resulting field data indicates that its time–frequency resolution and joint P-wave dispersion attributes can help to fine-tune identification of the location of oil and gas reservoirs.