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Calibration, Conversion, and Quantitative Multi-Layer Inversion of Multi-Coil Rigid-Boom Electromagnetic Induction Data

Multi-coil electromagnetic induction (EMI) systems induce magnetic fields below and above the subsurface. The resulting magnetic field is measured at multiple coils increasingly separated from the transmitter in a rigid boom. This field relates to the subsurface apparent electrical conductivity (σ(a...

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Autores principales: von Hebel, Christian, van der Kruk, Jan, Huisman, Johan A., Mester, Achim, Altdorff, Daniel, Endres, Anthony L., Zimmermann, Egon, Garré, Sarah, Vereecken, Harry
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6864633/
https://www.ncbi.nlm.nih.gov/pubmed/31683890
http://dx.doi.org/10.3390/s19214753
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author von Hebel, Christian
van der Kruk, Jan
Huisman, Johan A.
Mester, Achim
Altdorff, Daniel
Endres, Anthony L.
Zimmermann, Egon
Garré, Sarah
Vereecken, Harry
author_facet von Hebel, Christian
van der Kruk, Jan
Huisman, Johan A.
Mester, Achim
Altdorff, Daniel
Endres, Anthony L.
Zimmermann, Egon
Garré, Sarah
Vereecken, Harry
author_sort von Hebel, Christian
collection PubMed
description Multi-coil electromagnetic induction (EMI) systems induce magnetic fields below and above the subsurface. The resulting magnetic field is measured at multiple coils increasingly separated from the transmitter in a rigid boom. This field relates to the subsurface apparent electrical conductivity (σ(a)), and σ(a) represents an average value for the depth range investigated with a specific coil separation and orientation. Multi-coil EMI data can be inverted to obtain layered bulk electrical conductivity models. However, above-ground stationary influences alter the signal and the inversion results can be unreliable. This study proposes an improved data processing chain, including EMI data calibration, conversion, and inversion. For the calibration of σ(a), three direct current resistivity techniques are compared: Electrical resistivity tomography with Dipole-Dipole and Schlumberger electrode arrays and vertical electrical soundings. All three methods obtained robust calibration results. The Dipole-Dipole-based calibration proved stable upon testing on different soil types. To further improve accuracy, we propose a non-linear exact EMI conversion to convert the magnetic field to σ(a). The complete processing workflow provides accurate and quantitative EMI data and the inversions reliable estimates of the intrinsic electrical conductivities. This improves the ability to combine EMI with, e.g., remote sensing, and the use of EMI for monitoring purposes.
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spelling pubmed-68646332019-12-23 Calibration, Conversion, and Quantitative Multi-Layer Inversion of Multi-Coil Rigid-Boom Electromagnetic Induction Data von Hebel, Christian van der Kruk, Jan Huisman, Johan A. Mester, Achim Altdorff, Daniel Endres, Anthony L. Zimmermann, Egon Garré, Sarah Vereecken, Harry Sensors (Basel) Article Multi-coil electromagnetic induction (EMI) systems induce magnetic fields below and above the subsurface. The resulting magnetic field is measured at multiple coils increasingly separated from the transmitter in a rigid boom. This field relates to the subsurface apparent electrical conductivity (σ(a)), and σ(a) represents an average value for the depth range investigated with a specific coil separation and orientation. Multi-coil EMI data can be inverted to obtain layered bulk electrical conductivity models. However, above-ground stationary influences alter the signal and the inversion results can be unreliable. This study proposes an improved data processing chain, including EMI data calibration, conversion, and inversion. For the calibration of σ(a), three direct current resistivity techniques are compared: Electrical resistivity tomography with Dipole-Dipole and Schlumberger electrode arrays and vertical electrical soundings. All three methods obtained robust calibration results. The Dipole-Dipole-based calibration proved stable upon testing on different soil types. To further improve accuracy, we propose a non-linear exact EMI conversion to convert the magnetic field to σ(a). The complete processing workflow provides accurate and quantitative EMI data and the inversions reliable estimates of the intrinsic electrical conductivities. This improves the ability to combine EMI with, e.g., remote sensing, and the use of EMI for monitoring purposes. MDPI 2019-11-01 /pmc/articles/PMC6864633/ /pubmed/31683890 http://dx.doi.org/10.3390/s19214753 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
von Hebel, Christian
van der Kruk, Jan
Huisman, Johan A.
Mester, Achim
Altdorff, Daniel
Endres, Anthony L.
Zimmermann, Egon
Garré, Sarah
Vereecken, Harry
Calibration, Conversion, and Quantitative Multi-Layer Inversion of Multi-Coil Rigid-Boom Electromagnetic Induction Data
title Calibration, Conversion, and Quantitative Multi-Layer Inversion of Multi-Coil Rigid-Boom Electromagnetic Induction Data
title_full Calibration, Conversion, and Quantitative Multi-Layer Inversion of Multi-Coil Rigid-Boom Electromagnetic Induction Data
title_fullStr Calibration, Conversion, and Quantitative Multi-Layer Inversion of Multi-Coil Rigid-Boom Electromagnetic Induction Data
title_full_unstemmed Calibration, Conversion, and Quantitative Multi-Layer Inversion of Multi-Coil Rigid-Boom Electromagnetic Induction Data
title_short Calibration, Conversion, and Quantitative Multi-Layer Inversion of Multi-Coil Rigid-Boom Electromagnetic Induction Data
title_sort calibration, conversion, and quantitative multi-layer inversion of multi-coil rigid-boom electromagnetic induction data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6864633/
https://www.ncbi.nlm.nih.gov/pubmed/31683890
http://dx.doi.org/10.3390/s19214753
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