Automated optimization of electrode locations for electrical resistivity tomography

Automated optimization of electrode locations for electrical resistivity tomography This work describes the automated search for optimal electrode locations that will improve reconstructions of a 2D electrical resistivity tomography problem within a meta inverse framework. The meta inverse framework was incorporated into a finite integration forward solver developed for simulating the measurement data, and into an inverse solver developed for reconstructing the resistivity distribution within the subsurface. The meta inverse framework solver then searched to find optimal electrode locations at which best reconstructions of the resistivity distribution within the subsurface could be obtained. The numerical results obtained from applying the forward, inverse and meta inverse solvers to search for resistance anomalies in an electrical resistivity tomography problem are presented. The results show that these solvers are successful for simulations, reconstructions, and for determining the optimal electrode locations at which the best reconstruction of the resistivity distribution can be obtained. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Modeling Earth Systems and Environment Springer Journals

Automated optimization of electrode locations for electrical resistivity tomography

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Publisher
Springer International Publishing
Copyright
Copyright © 2018 by Springer International Publishing AG, part of Springer Nature
Subject
Earth Sciences; Earth System Sciences; Math. Appl. in Environmental Science; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Mathematical Applications in the Physical Sciences; Ecosystems; Environment, general
ISSN
2363-6203
eISSN
2363-6211
D.O.I.
10.1007/s40808-018-0472-7
Publisher site
See Article on Publisher Site

Abstract

This work describes the automated search for optimal electrode locations that will improve reconstructions of a 2D electrical resistivity tomography problem within a meta inverse framework. The meta inverse framework was incorporated into a finite integration forward solver developed for simulating the measurement data, and into an inverse solver developed for reconstructing the resistivity distribution within the subsurface. The meta inverse framework solver then searched to find optimal electrode locations at which best reconstructions of the resistivity distribution within the subsurface could be obtained. The numerical results obtained from applying the forward, inverse and meta inverse solvers to search for resistance anomalies in an electrical resistivity tomography problem are presented. The results show that these solvers are successful for simulations, reconstructions, and for determining the optimal electrode locations at which the best reconstruction of the resistivity distribution can be obtained.

Journal

Modeling Earth Systems and EnvironmentSpringer Journals

Published: May 28, 2018

References

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