Reconstruction of 1-D conductivity from dual‐loop EM data

Abstract

Inversions of electromagnetic data from different coil configurations provide independent information about geological structures. We develop a 1-D inversion algorithm that can invert data from the horizontal coplanar (HC), vertical coplanar, coaxial (CA), and perpendicular coil configurations separately or jointly. The inverse problem is solved by minimizing a model objective function subject to data constraints. Tests using synthetic data from 1-D models indicate that if data are collected at a sufficient number of frequencies, then the recovered models from individual inversions of different coil systems can be quite similar. However, if only a limited number of frequencies are available, then joint inversion of data from different coils produces a better model than the individual inversions. Tests on 3-D synthetic data sets indicate that 1-D inversions can be used as a fast and approximate tool to locate anomalies in the subsurface. Also for the test example presented here, the joint inversion of HC and CA data over a 3-D conductivity provided a better model than that produced by the individual inversion of the data sets.

Imaging a 3D geological structure from HEM, airborne magnetic and ground ERT data in Kalat-e-Reshm area, Iran

“…We carried out single and joint inversion of HC and CA data. The predicted data are better fitted for the joint inversion and as it is recommended by Zhang et al (2000) a 1D joint inversion of HEM HC and CA data in 3D environments could improve the accuracy and quality of resistivity models as compared to the individual inversion of each dataset. The inversion results confirm the existence of an arc like resistive structure in the area which is wider than what is shown on the geological map which is based on geological observations on the surface of the earth.…”

“…Quadrature (a) and inphase (b) components of CA data, quadrature (c) and inphase (d) components of HC data, and recovered resistivity model (e). observed data than individual inversions and as it is recommended by Zhang et al (2000) a 1D joint inversion of HEM HC and CA data in 3D environments can improve the accuracy and quality of resistivity models as compared to the individual inversion of each dataset.…”

“…Inversion methods (e.g., Fitterman and Deszcz-pan, 1998;Fullagar and Oldenburg, 1984;Holladay et al, 1986;Huang and Palacky, 1991;Paterson and Reford, 1986;Qian et al, 1997;Sengpiel and Siemon, 2000;Zhang et al, 2000) have the advantage of yielding a much better vertical resolution for the given output parameter and the disadvantage that these methods are slower compared to transform methods. Inversion methods for the interpretation of HEM data for a layered earth are being employed more commonly for helicopter-borne surveys as the data quality is improved and as both the number of frequencies and computer speed are increased.…”

Spatial mapping of submerged cave systems by means of airborne electromagnetics: an emerging technology to support protection of endangered karst aquifers

“…To obtain a lateral resistivity distribution, the resistivities of all of these 1D models are stitched together (Sengpiel and Siemon ; Zhang et al . ). In contrast to the recorded AEM components, the calculated resistivities should be independent of the sensor altitude.…”

A quick 2-D geoelectric inversion method using series expansion

“…In solving 2-D or 3-D inversion problems with the FD forward modeling method (Loke and Barker, 1996;Zhang et al, 2000), piecewise constant resistivities defined on a rectangular grid of cells are assumed. This results in a large number of unknowns normally leading to an underdetermined inverse problem.…”