Elastic full-waveform inversion based on the double-cross-shaped discrete flux-corrected transport

Abstract

Multi-parameter elastic full-waveform inversion is a technique that utilizes both P- and S-waves of observed seismic data to produce high-resolution velocity and density models with accurate amplitude information by minimizing the discrepancy between the predicted and observed multi-component data. However, due to the nonlinear nature of the multi-parameter inverse problem, elastic full-waveform inversion is prone to local minima and ‘cycle-skipping’. To overcome these challenges, this paper proposes an elastic full-waveform inversion method that incorporates a double-cross-shaped discrete flux-corrected transport. This method additionally introduces diffusion fluxes in two diagonal directions, which helps to capture low-frequency information in the observed seismic data and maintain forward modelling stability. Multi-scale inversion is achieved by gradually decreasing the diffusion flux correction parameter. Numerical experiments on both two typical models and a field data example demonstrate the effectiveness of the proposed elastic full-waveform inversion method based on the double-cross-shaped discrete flux-corrected transport in generating high-precision velocity and density models.