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See detailA modified DOI-based method to statistically estimate the depth of investigation of dc resistivity surveys
Deceuster, J.; Etienne, A.; Robert, Tanguy et al

in Journal of Applied Geophysics (2014), 103

Several techniques are available to estimate the depth of investigation or to identify possible artifacts in dc resistivity surveys. Commonly, the depth of investigation (DOI) is mainly estimated by using ... [more ▼]

Several techniques are available to estimate the depth of investigation or to identify possible artifacts in dc resistivity surveys. Commonly, the depth of investigation (DOI) is mainly estimated by using an arbitrarily chosen cut-off value on a selected indicator (resolution, sensitivity or DOI index). Ranges of cut-off values are recommended in the literature for the different indicators. However, small changes in threshold values may induce strong variations in the estimated depths of investigation. To overcome this problem, we developed a new statistical method to estimate the DOI of dc resistivity surveys based on a modified DOI index approach. This method is composed of 5 successive steps. First, two inversions are performed by using different resistivity reference models for the inversion (0.1 and 10 times the arithmetic mean of the logarithm of the observed apparent resistivity values). Inversion models are extended to the edges of the survey line and to a depth range of three times the pseudodepth of investigation of the largest array spacing used. In step 2, we compute the histogram of a newly defined scaled DOI index. Step 3 consists of the fitting of the mixture of two Gaussian distributions (G1 and G2) to the cumulative distribution function of the scaled DOI index values. Based on this fitting, step 4 focuses on the computation of an interpretation index (II) defined for every cell j of the model as the relative probability density that the cell j belongs to G1, which describes the Gaussian distribution of the cells with a scaled DOI index close to 0.0. In step 5, a new inversion is performed by using a third resistivity reference model (the arithmetic mean of the logarithm of the observed apparent resistivity values). The final electrical resistivity image is produced by using II as alpha blending values allowing the visual discrimination between well-constrained areas and poorly-constrained cells. The efficiency of the proposed methodology is assessed on synthetic and field data. By using synthetic benchmark analysis, we demonstrate that the selected well-constrained cells are well-reconstructed in size and shape as well as in resistivity contrasts. Compared to the existing image appraisal tools, the proposed statistical method allows the identification of the statistically well-constrained cells of the model without using any arbitrary cut-off value. Using this statistical method in combination with the resolution, when interpreting dc resistivity surveys, provides the geophysicist valuable information to avoid over- or misinterpretation of ERT images. [less ▲]

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See detailReconstruction of sub-wavelength fractures and physical properties of masonry media using full-waveform inversion of proximal penetrating radar
Patriarca, C.; Lambot, S.; Mahmoudzadeh, M. R. et al

in Journal of Applied Geophysics (2011), 74(1)

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See detailSubsurface electrical imaging of anisotropic formations affected by a slow active reverse fault (Trévaresse thrust), Provence, France
Nguyen, Frédéric ULg; Chardon; Garambois, S. et al

in Journal of Applied Geophysics (2007), 62

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See detailImage processing of 2D resistivity data for imaging faults
Nguyen, Frédéric ULg; Garambois, Stephane; Jongmans, Denis et al

in Journal of Applied Geophysics (2005), 57(4), 260-277

A methodology to locate automatically limits or boundaries between different geological bodies in 2D electrical tomography is proposed, using a crest line extraction process in gradient images, This ... [more ▼]

A methodology to locate automatically limits or boundaries between different geological bodies in 2D electrical tomography is proposed, using a crest line extraction process in gradient images, This method is applied on several synthetic models and on field data set acquired on three experimental sites during the European project PALEOSIS where trenches were dug. The results presented in this work are valid for electrical tomographies data collected with a Wenner-alpha array and computed with an 1(1) norm (blocky inversion) as optimization method, For the synthetic cases. three geometric contexts are modelled: a vertical and a dipping fault juxtaposing two different geological formations and a step-like structure. A superficial layer can cover each geological structure. In these three situations, the method locates the synthetic faults and layer boundaries, and determines fault displacement but with several limitations. The estimated fault positions correlate exactly with the synthetic ones if a conductive (or no superficial) layer overlies the studied structure. When a resistive layer with a thickness of 6 in covers the model, faults are positioned with a maximum error of 1 m. Moreover, when a resistive and/or a thick top layer is present, the resolution significantly decreases for the fault displacement estimation (error up to 150%). The tests with the synthetic models for surveys using the Wenner-alpha array indicate that the proposed methodology is best suited to vertical and horizontal contacts. Application of the methodology to real data sets shows that a lateral resistivity contrast of 1:5 1:10 leads to exact faults location. A fault contact with a resistivity contrast of 1:0.75 and overlaid by a resistive layer with a thickness or 1 m gives an error location ranging from 1 to 3 m. Moreover, no result is obtained for a contact with very low contrasts (similar to 1:0.85) overlaid by a resistive soil. The method shows poor results when vertical gradients are greater than horizontal ones. This kind of image processing technique should be systematically used for improving the objectiveness of tomography interpretation when looking for limits between geological objects. (c) 2005 Elsevier B.V. All rights reserved. [less ▲]

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