Testing of Dynamic Correction Methods for Magnetotelluric Sounding Curves Using Model Data

The influence of near-surface inhomogeneities is a major challenge in magnetotelluric sounding (MTS), because it hampers retrieval of information on deep structures. Local, thin near-surface inhomogeneities cause static shifts of magnetotelluric (MT) amplitude curves while leaving the phase curves unchanged. A more complicated case arises from significant variations in the total longitudinal conductance S of the upper layer, which lead to changes in the shape of the amplitude curves. Variations in S also affect the phases of the components of the impedance tensor Z and telluric tensor T, as well as the Wiese–Parkinson matrix W and magnetic tensor M. E.B. Fainberg was the first to propose a dynamic correction to MT amplitude curves, which reduces to multiplying them by a frequency-dependent factor. M.N. Berdichevsky generalized this idea to the impedance tensor and the electric distortion matrix. V.A. Kuznetsov proposed an algorithm that also accounts for magnetic distortions. These approaches are based on three-dimensional modeling of the MT field and require specifying the distribution of S in the upper layer and a background 1D layered model. We have implemented dynamic-correction algorithms and assessed their performance using synthetic (model) MTS data. The data were computed for a 3D model of the tectonosphere containing large-scale inhomogeneities at three structural levels: the sedimentary cover, consolidated crust, and upper mantle. Numerical experiments have shown that dynamic correction effectively suppresses the influence of sedimentary cover structures. In the different MTS data components, only the effects of deep crustal and mantle structures remained, enabling their confident localization and potentially simplifying subsequent inversion. Clearly, the success of dynamic correction depends on the accuracy with which the conductance of the upper layer and background 1D model are specified, as well as on observation errors. Future studies will evaluate the effectiveness of dynamic correction under realistic conditions.