A high-resolution dispersion imaging method of seismic surface waves based on chirplet transform. (9th December 2021)

• Record Type: Journal Article
• Authors: Su, Qin; Xu, Xingrong; Wang, Zhinong; Sun, Chengyu; Guo, Yaozong; Wu, Dunshi
• Is Part Of: Journal of geophysics and engineering. Volume 18:Number 6(2021)
• Page Start: 908
• Page End: 919
• Publication Date: 2021-12-09
• Subjects: surface waves -- dispersion imaging -- chirplet transform -- time-frequency analysis -- dispersion curve; Geophysics -- Periodicals; Prospecting -- Geophysical methods -- Periodicals; Engineering -- Periodicals; 622.1505
• DOI: 10.1093/jge/gxab061
• Languages: English
• ISSNs: 1742-2132

Abstract

Abstract: The surface-wave analysis method is widely adopted to build a near-surface shear-wave velocity structure. Reliable dispersion imaging results form the basis for subsequent picking and inversion of dispersion curves. In this paper, we present a high-resolution dispersion imaging method (CSFK) of seismic surface waves based on chirplet transform (CT). CT introduces the concept of chirp rate, which could focus surface-wave dispersion energy well in time-frequency domain. First, each seismic trace in time-distance domain is transformed to time-frequency domain by CT. Thus, for each common frequency gather, we obtain a series of 2D complex-valued functions of time and distance, which are called pseudo-seismograms. Then, we scan a series of group velocities to obtain the slanting-phase function and perform a spatial Fourier transform on the slanting-phase function to get its amplitude. In addition, power operation is adopted to increase the amplitude difference between dispersion energy and noise. Finally, we generate the dispersion image by searching for the maximum amplitude of a slanting-phase function. Because the CSFK method considers the position of surface-wave energy in the time-frequency domain, this largely eliminates the noise interference from other time locations and improves the resolution and signal-to-noise ratio of the dispersion image. The results of synthetic test and field dataset processing demonstrate the effectiveness of the proposed method. In addition, we invert all 120 sets of dispersion curves extracted from reflected wave seismic data acquired for petroleum prospecting. The one-dimensional inversion shear-wave velocity models are interpolated into a two-dimensional profile of shear-wave velocity, which is in good agreement with the borehole data.