Joint Inversion of Multiphysical Parameters Based on a Combination of Cosine Dot-Gradient and Joint Total Variation Constraints.

The joint inversion of structural constraints is a new and rapidly developing detection technology in comprehensive geophysical interpretation. In this article, a new structural constraint 2-D multiphysical parameter joint inversion algorithm for magnetotelluric (MT), gravity, and magnetic data is developed. The structural constraint term is a combination of cosine dot-gradient (CDG) and joint total variation (JTV) constraints, which not only has characteristics of traditional dot product and cross-gradient structure constraints but also avoids the uncertainty of dot product constraints predicting the gradient direction of the model parameters, overcomes the need for high-order differential approximation of the cross-gradient constraint, ignores the influence of the gradient amplitude of different model parameters on the weight of the structural constraint of different regions, and enhances the reconstruction accuracy of the underground discontinuous interface. To more easily combine multiple optimization algorithms to improve the resolution and computational efficiency of joint inversion, an adaptive inexact structural resemblance (IESR) algorithm is developed to minimize numerical solutions to the objective function. Experimental results have demonstrated that the CDG constraint has a wider use range than the traditional structural constraint, the addition of the JTV constraint can recover the underground discontinuous interface, and an inversion result of higher resolution can be obtained using the adaptive IESR algorithm.