3D forward and inverse modeling of self-potential data based on the PARDISO direct solver
In recent years,the self-potential method has played a significant role in the exploration and evaluation of seafloor massive sulfide resources.This study explored the 3D forward and inverse modeling algorithms for self-potential based on the PARDISO direct solver.First,the finite volume method was employed to discretize the self-potential control equation,and the PARDISO direct solver was utilized to improve the forward modeling efficiency.The reliability of the forward modeling algorithm was verified by comparing the numerical solution with the analytical solution.The 3D inverse modeling algorithm considered the topographic factor and incorporated the minimum support constraint and depth weighting into the objective function.The inversion results of theoretical model data effec-tively reconstructed the ore body structure.Finally,the self-potential data obtained from indoor sandbox experiments were inverted u-sing the inverse modeling algorithm,obtaining that the current density anomaly was roughly consistent with the position of the metal bar.Therefore,the inverse modeling algorithm proposed in this study holds critical significance for subsequent inversion of large-scale spontaneous potential data.
self-potential method3D focusing inversionPARDISO direct solver
万方数据
维普
