Volume 47, pp. 1-17, 2017.

Identifying the magnetic permeability in multi-frequency EM data inversion

Gian Piero Deidda, Patricia Díaz de Alba, and Giuseppe Rodriguez

Abstract

Electromagnetic induction surveys are among the most popular techniques for non-destructive investigation of soil properties in order to detect the presence of either ground inhomogeneities or of particular substances. In this paper we develop a regularized algorithm for the inversion of a nonlinear mathematical model well established in applied geophysics, starting from noisy electromagnetic data collected by varying both the height of the measuring device with respect to the ground level and its operating frequency. Assuming the conductivity to be known in advance, we focus on the determination of the magnetic permeability of the soil with respect to depth, and give the analytical expression of the Jacobian matrix of the forward model, which is indispensable for the application of the inversion algorithm. Finally, numerical experiments on synthetic data sets illustrate the effectiveness of the method.

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Key words

Regularization, nonlinear inverse problems, electromagnetic induction

AMS subject classifications

65F22, 65H10, 65R32, 86A22

ETNA articles which cite this article

Vol. 53 (2020), pp. 459-480 Federica Pes and Giuseppe Rodriguez: The minimal-norm Gauss-Newton method and some of its regularized variants

Vol. 61 (2024), pp. 105-120 Patricia Díaz de Alba and Federica Pes: A two-dimensional integral model of the first-kind for LIN electromagnetic data inversion

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