Abstract: Full-waveform inversion is widely used to reconstruct subsurface properties at different geologic scales. For shallow land applications using surface waves, a lack of information on the source wavelet, dispersion, and presence of higher modes increases the nonlinearity of the inverse problem. The inversion can become more challenging with the presence of near-surface complexities associated with scattering, attenuation, and high-contrast variations in the elastic parameters. Compared with the least-squares formulation, GSOT provides a more convex misfit function and reduces dependence on the accuracy of the initial model. Although a few field-data applications have shown the potential and benefits of using GSOT-based FWI with body waves, there are limited real applications of the inversion with a GSOT misfit function for NS characterization. Despite considerable effort with blind benchmark tests in exploration seismology, typically synthetic FWI examples for NS applications are demonstrated through an “inverse crime” approach. Synthetic FWI examples performed compare the performance of LS- and GSOT-based FWI with more realistic scenarios. We demonstrate the GSOT misfit function improves the initial 1D velocity models and guides the updates toward the actual subsurface properties. This enables the recovery of higher-mode Rayleigh waves and reconstruction of the cavity with better precision.