Two-dimensional meshless modelling and TE-mode inversion of magnetotelluric data

Abstract

SUMMARY We present a new 2-D forward modelling and inversion scheme to interpret magnetotelluric/radio-magnetotelluric data by utilizing a novel meshless forward operator. We use this discretization technique within an inverse scheme to recover conductivity structures from given magnetotelluric data. To approximate solutions of the partial differential equations that describe the magnetotelluric experiment, we discretize the subsurface only in terms of nodes. These node sets, which are simple to generate, are used to derive the differential operators’ approximations in a generalized meshless framework. First, we study and compare forward modelling calculations to an analytical and known solution from the literature. Several example calculations are given, which validate the proposed meshless forward operator. We then formulate our inverse scheme for TE-mode data, which uses only subsets of the nodal subsurface parametrization to generate conductivity structures from this given data. The inverse scheme consists of a Gauss–Newton algorithm combined with the generalized meshless framework. To validate the algorithm, we present inversion results from synthetic and field data. We compare our results to conductivity models calculated by established, well-known inversion schemes and literature results. We report that our algorithm can accurately model magnetotelluric responses and recover meaningful conductivity models, explaining given magnetotelluric data.