3-D Joint Inversion of MT and CSEM Data Based on Adaptive Finite-Element Forward Modeling

Electromagnetic (EM) methods are widely used in geophysical exploration. Different EM methods offer varying detection depths and resolutions. Magnetotelluric (MT) typically provides information about deep structures, whereas controlled-source EM (CSEM) is more effective in imaging shallow targets. To enhance the resolution of subsurface structures, a joint inversion of MT and CSEM data is proposed. In this article, we combine MT and CSEM data and perform joint inversion using the limited-memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) algorithm. To balance the two data types, we propose a data weighting scheme based on the square root of the ratio of the number of data points. To improve the accuracy of forward responses and the reliability of the inversion, we use a high-order adaptive finite-element forward modeling method. The forward modeling mesh and inversion mesh are decoupled to prevent the over-parameterization of the inversion mesh. In addition, this approach uses an algorithm based on posteriori error estimators to guide the adaptive refinement process of the forward modeling mesh. The accuracy and efficiency of the forward modeling method are verified using a layered model. The inversion results of two complex models demonstrate that the joint inversion method offers superior resolution compared to standalone inversions.