Global nonlinear optimization for the estimation of static shift and interpretation of 1-D magnetotelluric sounding data

Abstract

In the presence of conducting inhomogeneities in near-surface structures, apparent resistivity data in magnetotelluric sounding can be severely distorted. This is due to electric fields generated from boundary charges on surficial inhomogeneities. Such distortion persists throughout the entire recording range and is known as static shift in magnetotellurics. Frequency-independent static shifts manifest as vertical, parallel shifts that occur in plots of the dual logarithmic scale of apparent resistivity versus time period. The phase of magnetotelluric sounding data remains unaffected by the static shift and can be used to remove the static shift to some extent. However, individual inversion of phase data yields highly nonunique results, and alone it will not work to correctly remove the static shift. Inversions of uncorrected magnetotelluric data yield erroneous and unreliable estimations, while static-shift-corrected magnetotelluric data provide better and reliable estimations of the resistivities and thicknesses of subsurface structures. In the present study, static shift (a frequency-independent real constant) is also considered as one of the model parameters and is optimized together with other model parameters (resistivity and thickness) using the very fast simulated annealing global inversion technique. This implies that model parameters are determined simultaneously with the estimate of the static shift in the data. Synthetic and noisy data generated for a number of models are interpreted, to demonstrate the efficacy of the approach to yield reliable estimates of subsurface structures when the apparent resistivity data are affected by static shift. Individual inversions of static-shift-affected apparent resistivity data and phase data yield unreliable estimations of the model parameters. Furthermore, the estimated model parameters after individual data inversions do not show any systematic correlations with the amount of static shift in the data. The present study shows that only joint inversion of the apparent resistivity and phase data, without or with optimizing of the static shift, yields models that show good fits between the observed and the model data. Joint inversion results also reveal a systematic relationship between the estimated model parameters and the static shift in the data. The proposed approach also shows that estimated resistivities are ‘S’ (the static shift parameter) times the actual resistivities, and that estimated thicknesses are √S times the actual thicknesses without optimization of the static shift. This result is in good agreement with the existing relationship in the literature. Therefore, the global optimization procedure developed can be effectively used to optimize the static shifts in data, to obtain reliable estimations of model parameters. Subsequently, joint inversion of the apparent resistivity and phase data, with optimization of the static shift, is performed, which yields accurate estimates of subsurface structures. It is demonstrated that this approach can also be used when the data is not affected by the static shift. In such cases, the estimated static shift parameter ‘S’ will be close to unity. The efficacy of the approach is demonstrated with a field example from Singhbhum craton, eastern India, by providing an accurate estimation of the craton thickness and the conducting structure that lies below the craton. Normal 0 false false false EN-US X-NONE X-NONE