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2-D joint structural inversion of cross-hole electrical resistance and ground penetrating radar data

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2-D joint structural inversion of cross-hole electrical resistance and ground penetrating radar data. / Bouchedda, Abderrezak; Chouteau, Michel; Binley, Andrew et al.
In: Journal of Applied Geophysics, Vol. 78, 03.2012, p. 52-67.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Bouchedda A, Chouteau M, Binley A, Giroux B. 2-D joint structural inversion of cross-hole electrical resistance and ground penetrating radar data. Journal of Applied Geophysics. 2012 Mar;78:52-67. doi: 10.1016/j.jappgeo.2011.10.009

Author

Bouchedda, Abderrezak ; Chouteau, Michel ; Binley, Andrew et al. / 2-D joint structural inversion of cross-hole electrical resistance and ground penetrating radar data. In: Journal of Applied Geophysics. 2012 ; Vol. 78. pp. 52-67.

Bibtex

@article{02a3eecb90b1470199ccfa5913af2823,
title = "2-D joint structural inversion of cross-hole electrical resistance and ground penetrating radar data",
abstract = "We present a joint structural inversion algorithm for cross-hole electrical resistance tomography (ERT) and cross-hole radar travel time tomography (RTT) that encourages coincident sharp changes on a smoothly varying background in the two models. The proposed approach is based on the combination of two iterative soft-thresholding inversion algorithms in parallel manner where the structural information is exchanged at each iteration. Iterative thresholding algorithm allows to obtain a sparse wavelet representation of the model (blocky model) by applying a thresholding operator to the wavelet coefficients of model obtained through a Gauss-Newton iteration. The structural information is introduced in the inversion system using the smoothness weighting matrices that control boundary cells and the thresholds that are estimated by maximizing a structural similarity criterion, which is a function of the two (ERT and RTT) models. A Canny edge detector is implemented to extract the structural information. The detected edges serve to build a weighting matrix that is used to alter the smoothness matrix constraint. To validate our methodology and its implementation, tests were performed on three synthetic models. The results show that the parameters estimated by our joint inversion approach are more consistent than those from individual inversions and another joint inversion algorithm. In addition, our approach appears to be robust in high noise level conditions. Finally, the proposed algorithm was applied for vadose zone characterisation in a sandstone aquifer. It achieves results that are consistent with hydrogeological information and geophysical logs available at the site. The results were also compared in terms of structural similarities to models obtained by a joint structural inversion algorithm with a cross-gradient constraint. Based on this comparison and hydrogeologic information, we conclude that the proposed algorithm allows to the RTT and ERT models to be dissimilar in the areas where the data are incompatible. (C) 2011 Elsevier B.V. All rights reserved.",
keywords = "Wavelet thresholding, CONSTRAINTS, FLOW, GEOPHYSICAL-DATA, COOPERATIVE INVERSION, ALGORITHM, MOISTURE, SANDSTONE, BOREHOLE RADAR, ERT, Joint structural inversion, RTT, RESISTIVITY, TOMOGRAPHY",
author = "Abderrezak Bouchedda and Michel Chouteau and Andrew Binley and Bernard Giroux",
year = "2012",
month = mar,
doi = "10.1016/j.jappgeo.2011.10.009",
language = "English",
volume = "78",
pages = "52--67",
journal = "Journal of Applied Geophysics",
issn = "0926-9851",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - 2-D joint structural inversion of cross-hole electrical resistance and ground penetrating radar data

AU - Bouchedda, Abderrezak

AU - Chouteau, Michel

AU - Binley, Andrew

AU - Giroux, Bernard

PY - 2012/3

Y1 - 2012/3

N2 - We present a joint structural inversion algorithm for cross-hole electrical resistance tomography (ERT) and cross-hole radar travel time tomography (RTT) that encourages coincident sharp changes on a smoothly varying background in the two models. The proposed approach is based on the combination of two iterative soft-thresholding inversion algorithms in parallel manner where the structural information is exchanged at each iteration. Iterative thresholding algorithm allows to obtain a sparse wavelet representation of the model (blocky model) by applying a thresholding operator to the wavelet coefficients of model obtained through a Gauss-Newton iteration. The structural information is introduced in the inversion system using the smoothness weighting matrices that control boundary cells and the thresholds that are estimated by maximizing a structural similarity criterion, which is a function of the two (ERT and RTT) models. A Canny edge detector is implemented to extract the structural information. The detected edges serve to build a weighting matrix that is used to alter the smoothness matrix constraint. To validate our methodology and its implementation, tests were performed on three synthetic models. The results show that the parameters estimated by our joint inversion approach are more consistent than those from individual inversions and another joint inversion algorithm. In addition, our approach appears to be robust in high noise level conditions. Finally, the proposed algorithm was applied for vadose zone characterisation in a sandstone aquifer. It achieves results that are consistent with hydrogeological information and geophysical logs available at the site. The results were also compared in terms of structural similarities to models obtained by a joint structural inversion algorithm with a cross-gradient constraint. Based on this comparison and hydrogeologic information, we conclude that the proposed algorithm allows to the RTT and ERT models to be dissimilar in the areas where the data are incompatible. (C) 2011 Elsevier B.V. All rights reserved.

AB - We present a joint structural inversion algorithm for cross-hole electrical resistance tomography (ERT) and cross-hole radar travel time tomography (RTT) that encourages coincident sharp changes on a smoothly varying background in the two models. The proposed approach is based on the combination of two iterative soft-thresholding inversion algorithms in parallel manner where the structural information is exchanged at each iteration. Iterative thresholding algorithm allows to obtain a sparse wavelet representation of the model (blocky model) by applying a thresholding operator to the wavelet coefficients of model obtained through a Gauss-Newton iteration. The structural information is introduced in the inversion system using the smoothness weighting matrices that control boundary cells and the thresholds that are estimated by maximizing a structural similarity criterion, which is a function of the two (ERT and RTT) models. A Canny edge detector is implemented to extract the structural information. The detected edges serve to build a weighting matrix that is used to alter the smoothness matrix constraint. To validate our methodology and its implementation, tests were performed on three synthetic models. The results show that the parameters estimated by our joint inversion approach are more consistent than those from individual inversions and another joint inversion algorithm. In addition, our approach appears to be robust in high noise level conditions. Finally, the proposed algorithm was applied for vadose zone characterisation in a sandstone aquifer. It achieves results that are consistent with hydrogeological information and geophysical logs available at the site. The results were also compared in terms of structural similarities to models obtained by a joint structural inversion algorithm with a cross-gradient constraint. Based on this comparison and hydrogeologic information, we conclude that the proposed algorithm allows to the RTT and ERT models to be dissimilar in the areas where the data are incompatible. (C) 2011 Elsevier B.V. All rights reserved.

KW - Wavelet thresholding

KW - CONSTRAINTS

KW - FLOW

KW - GEOPHYSICAL-DATA

KW - COOPERATIVE INVERSION

KW - ALGORITHM

KW - MOISTURE

KW - SANDSTONE

KW - BOREHOLE RADAR

KW - ERT

KW - Joint structural inversion

KW - RTT

KW - RESISTIVITY

KW - TOMOGRAPHY

U2 - 10.1016/j.jappgeo.2011.10.009

DO - 10.1016/j.jappgeo.2011.10.009

M3 - Journal article

VL - 78

SP - 52

EP - 67

JO - Journal of Applied Geophysics

JF - Journal of Applied Geophysics

SN - 0926-9851

ER -