Reconstruction of electrical resistivity tomography (ERT) data using different base measurements
Che, Haoran LU ; Hedblom, Per LU and Dahlin, Torleif LU
(2026)
In Journal of Applied Geophysics
249.
- Abstract
Electrical resistivity tomography (ERT) is a widely used technique for imaging subsurface resistivity distributions, but conventional data acquisition strategies face trade-offs between resolution, efficiency, and data quality. Comprehensive datasets that maximize subsurface information are impractical to measure directly, motivating the development of ERT data reconstruction approaches that can generate any four-electrode datasets from a limited subset of measurements. In this study, two reconstruction methods: the pseudo–Pole–Pole (pdPP) approach and a modified pseudo–Pole–Dipole (pdPD) method, were systematically evaluated. First, a linear error model is applied to quantify noise propagation in the reconstructed datasets under both... (More)
Electrical resistivity tomography (ERT) is a widely used technique for imaging subsurface resistivity distributions, but conventional data acquisition strategies face trade-offs between resolution, efficiency, and data quality. Comprehensive datasets that maximize subsurface information are impractical to measure directly, motivating the development of ERT data reconstruction approaches that can generate any four-electrode datasets from a limited subset of measurements. In this study, two reconstruction methods: the pseudo–Pole–Pole (pdPP) approach and a modified pseudo–Pole–Dipole (pdPD) method, were systematically evaluated. First, a linear error model is applied to quantify noise propagation in the reconstructed datasets under both absolute and relative noise conditions. We then use synthetic modelling to test the imaging performance of the reconstructed datasets. Finally, field experiments at two test sites in Sweden are analysed to validate the numerical findings and to assess practical performance in real environments. Results show that, under relative errors, large readings of base measurements lead to high errors in reconstructed data, with pdPP generally yielding lower reconstruction errors than pdPD. Under absolute errors, the number of base measurements governs error accumulation, and both methods perform similarly. Imaging results show that plausible inversion results can be achieved using reconstructed datasets with estimated errors as data weighting for inversion. Field experiments validated the numerical findings and further demonstrated that pdPP method is preferred for ERT data reconstruction given that it provides more data with small reconstruction error and is better suited for efficient data acquisition.
(Less)
- author
- Che, Haoran
LU
; Hedblom, Per
LU
and Dahlin, Torleif
LU
- organization
- publishing date
- 2026-03
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- ERT data reconstruction, Pseudo-Pole-Dipole (pdPD), Pseudo-Pole-Pole (pdPP)
- in
- Journal of Applied Geophysics
- volume
- 249
- article number
- 106199
- publisher
- Elsevier
- external identifiers
-
- scopus:105032195711
- ISSN
- 0926-9851
- DOI
- 10.1016/j.jappgeo.2026.106199
- project
- Optimisation of geoelectrical tomography for underground construction applications - Step 2
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2026 The Authors.
- id
- 435082e4-40c3-4212-9eac-2eaa92081355
- date added to LUP
- 2026-03-18 13:56:16
- date last changed
- 2026-03-20 12:25:07
@article{435082e4-40c3-4212-9eac-2eaa92081355,
abstract = {{<p>Electrical resistivity tomography (ERT) is a widely used technique for imaging subsurface resistivity distributions, but conventional data acquisition strategies face trade-offs between resolution, efficiency, and data quality. Comprehensive datasets that maximize subsurface information are impractical to measure directly, motivating the development of ERT data reconstruction approaches that can generate any four-electrode datasets from a limited subset of measurements. In this study, two reconstruction methods: the pseudo–Pole–Pole (pdPP) approach and a modified pseudo–Pole–Dipole (pdPD) method, were systematically evaluated. First, a linear error model is applied to quantify noise propagation in the reconstructed datasets under both absolute and relative noise conditions. We then use synthetic modelling to test the imaging performance of the reconstructed datasets. Finally, field experiments at two test sites in Sweden are analysed to validate the numerical findings and to assess practical performance in real environments. Results show that, under relative errors, large readings of base measurements lead to high errors in reconstructed data, with pdPP generally yielding lower reconstruction errors than pdPD. Under absolute errors, the number of base measurements governs error accumulation, and both methods perform similarly. Imaging results show that plausible inversion results can be achieved using reconstructed datasets with estimated errors as data weighting for inversion. Field experiments validated the numerical findings and further demonstrated that pdPP method is preferred for ERT data reconstruction given that it provides more data with small reconstruction error and is better suited for efficient data acquisition.</p>}},
author = {{Che, Haoran and Hedblom, Per and Dahlin, Torleif}},
issn = {{0926-9851}},
keywords = {{ERT data reconstruction; Pseudo-Pole-Dipole (pdPD); Pseudo-Pole-Pole (pdPP)}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{Journal of Applied Geophysics}},
title = {{Reconstruction of electrical resistivity tomography (ERT) data using different base measurements}},
url = {{http://dx.doi.org/10.1016/j.jappgeo.2026.106199}},
doi = {{10.1016/j.jappgeo.2026.106199}},
volume = {{249}},
year = {{2026}},
}