The joint inversion of electrical resistivity tomography (ERT) and seismic refraction tomography (SRT) is a common practice to achieve a more accurate characterization of subsurface features, since these methods are sensitive to different properties of the subsurface. We propose an approach for integrating ERT and SRT, which involves a cross-gradient joint inversion on structured meshes even in cases with complex topography and a post-inversion procedure where a new cross-gradient index and fuzzy c-means analysis are used to assess the reliability of the joint procedure and facilitate the interpretation of the results. Our strategy does not introduce non-strictly necessary elements within the joint inversion procedure for dealing with a non-flat tomography, which can accentuate the illposedness of the inverse problem. The proposed method was applied to both synthetic and a field cases located in Central Italy, where an accurate geophysical reconstruction is needed for rehabilitation of an existing dam and boreholes are available to validate the geophysical survey. For all cases, joint inversion consistently yielded superior results compared to individual inversion, and the post-inversion tools facilitated the assessment of the impact of the joint scheme and allowed for a quantitative reconstruction (position and shape) of the main units at the site.

Coupling ERT and SRT data through cross-gradient joint inversion and clustering on structured meshes incorporating topography / Penta de Peppo, G.; Cercato, M.; De Donno, G.. - (2024), pp. 1-5. (Intervento presentato al convegno 30th European Meeting of Environmental and Engineering Geophysics, Held at the Near Surface Geoscience Conference and Exhibition 2024, NSG 2024 tenutosi a Helsinki, Finlandia) [10.3997/2214-4609.202420062].

Coupling ERT and SRT data through cross-gradient joint inversion and clustering on structured meshes incorporating topography

Penta de Peppo G.
;
Cercato M.;De Donno G.
2024

Abstract

The joint inversion of electrical resistivity tomography (ERT) and seismic refraction tomography (SRT) is a common practice to achieve a more accurate characterization of subsurface features, since these methods are sensitive to different properties of the subsurface. We propose an approach for integrating ERT and SRT, which involves a cross-gradient joint inversion on structured meshes even in cases with complex topography and a post-inversion procedure where a new cross-gradient index and fuzzy c-means analysis are used to assess the reliability of the joint procedure and facilitate the interpretation of the results. Our strategy does not introduce non-strictly necessary elements within the joint inversion procedure for dealing with a non-flat tomography, which can accentuate the illposedness of the inverse problem. The proposed method was applied to both synthetic and a field cases located in Central Italy, where an accurate geophysical reconstruction is needed for rehabilitation of an existing dam and boreholes are available to validate the geophysical survey. For all cases, joint inversion consistently yielded superior results compared to individual inversion, and the post-inversion tools facilitated the assessment of the impact of the joint scheme and allowed for a quantitative reconstruction (position and shape) of the main units at the site.
2024
30th European Meeting of Environmental and Engineering Geophysics, Held at the Near Surface Geoscience Conference and Exhibition 2024, NSG 2024
04 Pubblicazione in atti di convegno::04d Abstract in atti di convegno
Coupling ERT and SRT data through cross-gradient joint inversion and clustering on structured meshes incorporating topography / Penta de Peppo, G.; Cercato, M.; De Donno, G.. - (2024), pp. 1-5. (Intervento presentato al convegno 30th European Meeting of Environmental and Engineering Geophysics, Held at the Near Surface Geoscience Conference and Exhibition 2024, NSG 2024 tenutosi a Helsinki, Finlandia) [10.3997/2214-4609.202420062].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1731759
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