An application of regression M-estimation with the Hilbert transform to magnetotelluric data processing

Abstract

An accurate estimate of impedance functions is essential for the correct interpretation of a magnetotelluric (MT) sounding. Unfortunately, noise is inevitably encountered when the MT observation is conducted. In effect this can strongly influence the results given by the MT process and results in a distortion of the estimate. This paper proposes an alternative method for making unbiased robust estimates of MT impedance functions. The means for accomplishing this is based on the regression M-estimation and the Hilbert Transform operating on minimum phase MT impedance functions. Using MT data from the Columbia River Plateau and the EMSLAB Lincoln line, it is shown that the method can produce usable MT impedance functions even under conditions of severe noise contamination and in the absence of remote reference data.