Method and system for determining magnetotelluric time domain impedance

Abstract

The invention relates to a method and a system for determining magnetotelluric time domain impedance. By equivalently solving the optimization problem, the operation of matrix inversion is avoided, and meanwhile, the noise type and distribution in the signal are not assumed, so that the influence of peak impulse noise is suppressed without Bayesian estimation, the impedance estimation process is simplified, and the calculated amount is reduced; moreover, by using an interleaved multiplier iteration method, the updating of iteration parameters can be accelerated, the number of variables of eachiteration can be reduced, and the convergence speed is faster than the steepest descent iteration used by the traditional method; and besides, time domain impedance estimation is converted into an unconstrained convex optimization problem by adopting an improved algorithm, and the convex optimization problem is solved to obtain a global optimal value, so that the problem that the steepest descentiteration of local optimization is caught in a local minimum value in a traditional method is avoided, fitting errors are reduced, and a convergence result is more reliable.

Description

technical field [0001] The invention relates to the technical field of magnetotelluric detection, in particular to a method and system for determining the impedance of the magnetotelluric time domain. Background technique [0002] Magnetotelluric sounding is an important geophysical exploration method. This method uses natural electromagnetic field signals measured on the surface to estimate impedance, and can invert to obtain underground electrical structure information. According to different processing objects, impedance estimation is divided into time domain and frequency domain impedance estimation. Among them, the time-domain impedance estimation is less sensitive to some noise and has lower requirements on the stability of the electromagnetic field. Therefore, this method can achieve better results than the frequency-domain impedance estimation in the case of strong electromagnetic interference in the survey area. However, in practical applications, due to the large ...

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Problems solved by technology

However, when the time series to be processed is long, Bayesian estimation of noise, noise suppression using Bayesian estimation results, and the calculation of adaptive step size require a large amount of calculation

At the same time, the objective function of the measured data is often complex and cannot satisfy the assumption of the negative gradient direction (ideal direction of descent) everywhere. The convergence speed of the steepest descent method will t

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