Three‐dimensional gravity inversion based on the Hamiltonian Monte Carlo method

Abstract In geophysics, Bayesian inversion methods are of significant prominence. Here, we present a novel approach utilizing the Hamiltonian Monte Carlo (HMC) method in gravity inversion for elucidating three‐dimensional (3D) density structures. HMC provides a multi‐dimensional sampling method that demonstrates enhanced optimization efficiency, facilitating the attainment of distant proposals with elevated acceptance probabilities. Its applicability also extends to resolving linear inverse problems. Three synthetic models of cubic bodies, dipping dykes and a combined model were designed for tests. The testes underscore the promising potential of HMC in recovering subsurface density source bodies and giving the uncertainty of the inversion model. Furthermore, an inversion test conducted on the Vinton salt dome yields a reasonable 3D distribution of cap rock, consistent with prior studies in this area. The modelling and field experiments showed that the proposed HMC gravity inversion method had higher accuracy and application potential.