A numerical one-dimensional magnetotelluric inversion technique based on the Nabetian-Rankin algorithm for a layered earth is presented and illustrated with a noise-free theoretical model and two examples with real field data. The inversion of noise-free data is computationally efficient and removes most of the subjective biases of the interpretation of noisy data. A very satisfactory fit of the inverted result to field measurements is achieved using the least-squares criterion applied to the real part of the Nabetani-Rankin function V. The advantages of this function lie in its simplicity, its whiteness, and its relative freedom from noise. The Marquardt algorithm for the estimation of nonlinear parameters used for fitting the V curves overcomes the frequent failure of convergence in the Taylor series method and the slow convergence of the gradient method.--Modified journal abstract.

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