3D SH-wave Velocity Tomography via Direct Inversion of Multimode Love Wave Dispersion Curves from Seismic Subarrays

With the popularization of dense seismic array observations, tomographic imaging of subsurface velocity structures using surface wave dispersion data extracted via subarray partitioning has emerged as a new trend. The primary advantages of subarray-based dispersion data extraction lie in its reduced susceptibility to the inhomogeneous distribution of noise sources, which yields more stable and reliable dispersion measurements. Additionally, this approach enhances the energy of higher-order modes, thereby providing tighter constraints on subsurface velocity structures. Compared with the higher-order modes of Rayleigh waves, both the fundamental and higher-order modes of Love waves exhibit simpler dispersion characteristics with fewer mode crossings and overlaps, making them more favorable for joint inversion to constrain subsurface SH-wave velocity structures.

Traditional subarray surface wave imaging methods (e.g., SSWI) typically perform 1D velocity structure inversion at individual locations first, followed by stitching all 1D models to generate pseudo-2D or 3D velocity models. Despite its simplicity and computational efficiency, this direct stitching strategy is highly vulnerable to uneven station distributions, and the resultant velocity models may suffer from artificial velocity jumps. To address these limitations, Luo & Yao (2025) proposed a direct subarray surface wave imaging method (SSWDI), which eliminates the stitching step inherent in traditional methods and incorporates spatial smoothness constraints on velocity structures, thus enabling more robust inversion of subarray-derived dispersion data for subsurface imaging. However, the SSWDI method originally focused exclusively on the fundamental mode of Rayleigh waves. In this study, we further extend the SSWDI framework to accommodate both fundamental and higher-order modes of Love waves, and validate the improved method using both numerical synthetic data and field observational data.

Reference

Luo, S., and H. Yao (2025), Direct Tomography of S-wave Structure Using Subarray Surface Wave Dispersion Data: Methodology and Validation, Geophysics, 1–60, doi:10.1190/geo-2024-0515.