Modified S-transform based high-resolution dispersion imaging method for multi-channel surface wave data

High-resolution dispersive energy imaging is crucial in the multi-channel analysis of surface waves (MASW) for accurately predicting the near-surface shear wave velocity profile. Existing wavefield transformation methods such as time intercept-phase slowness (τ-p) transform, frequency-wavenumber (f-k) transform, phase-shift method, and the high-resolution linear Radon transform (HRLRT) often face challenges in low signal-to-noise-ratio (SNR) environments. This study proposes a modified S-transform-based high-resolution wavefield transformation method to unambiguously image the surface wave's dispersion spectrum, even for low SNR. Following the time-frequency analysis of the raw shot-gather, the method splits the pseudo-seismogram for individual frequency. After that, slant slices along different surface wave group velocities are obtained and processed using the HRLRT. Finally, the transformed spectrum for all available group velocities is converted to the dispersion spectrum in the frequency-phase velocity $(f$-$c)$ domain. The effectiveness of the proposed technique is demonstrated using two synthetic datasets and three field records. Dispersion spectra produced by the proposed method are compared with those obtained with the Slant $f$-$k$ (SFK) transform and HRLRT. The results demonstrate that the proposed method performs better than the existing high-resolution dispersion imaging methods, especially in low SNR scenarios. It effectively processes noiseless and noisy records, producing accurate, high-resolution, mode-separated dispersion spectra even under challenging conditions.