Theoretical model-based multi-parameter full waveform inversion for elastic media constrained by anisotropic diffusion regularization

Waveform inversion refers to the process of inferring underground medium parameters using seismic wave data. For elastic media, the interdependency between P- and S-wave velocities and density parameters enhances the nonlinearity of multi-parameter waveform inversion, leading to crosstalk in the inversion results. Given this, this study proposed an automatic differentiation-based multi-parameter full waveform inversion method for elastic media constrained by nonlinear anisotropic diffusion regularization (NADR). To address the strong parameter coupling and high nonlinearity in multi-parameter inversion, this study added an anisotropic diffusion regularization term to the objective function. Then, it calculated gradients using automatic differentiation technology, followed by iterative optimization using a mini-batch strategy. Experimental results show that the NADR can effectively mitigate parameter crosstalk and improve the inversion stability.