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A New Inversion Method Based on Distorted Born Iterative Method for Grounded Electrical Source Airborne Transient Electromagnetics | IEEE Journals & Magazine | IEEE Xplore

A New Inversion Method Based on Distorted Born Iterative Method for Grounded Electrical Source Airborne Transient Electromagnetics


Abstract:

A new iterative inversion algorithm is proposed to reconstruct the electrical conductivity profile in a stratified underground medium for the grounded electrical source a...Show More

Abstract:

A new iterative inversion algorithm is proposed to reconstruct the electrical conductivity profile in a stratified underground medium for the grounded electrical source airborne transient electromagnetic (GREATEM) system. In forward modeling, we simplify the mathematical expressions of the magnetic fields generated by a finite line source in the layered ground to semianalytical forms in order to save the computation time. The Fréchet derivative is derived for the electromagnetic response at the receivers due to a small perturbation of the conductivity in a certain layer underground. The initial expression of the Fréchet derivative has an expensive triple integral and contains the Bessel function in the integrand. It is simplified by partially eliminating the integration along the source line and deriving the analytical expression for the integration in the vertical direction inside the perturbed layer. In the inverse solution, we use the distorted Born iterative method (DBIM). This is the first time that the DBIM is applied to data measured by the GREATEM system. Besides, the forward and inverse procedures are carried out in the frequency domain and based on the Fréchet derivative of a line source. We demonstrate the validity of our forward model, Fréchet derivative, inverse model, and the precision as well as robustness of the inversion algorithm through numerical computation and comparisons. Finally, we apply the inversion algorithm to the measured data and compare the retrieved conductivity to the actual drilling data.
Published in: IEEE Transactions on Geoscience and Remote Sensing ( Volume: 56, Issue: 2, February 2018)
Page(s): 877 - 887
Date of Publication: 09 October 2017

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