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Hydraulic conductivity field characterization from the joint inversion of hydraulic heads and self‐potential data
Author(s) -
Soueid Ahmed A.,
Jardani A.,
Revil A.,
Dupont J. P.
Publication year - 2014
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2013wr014645
Subject(s) - hydraulic conductivity , electrokinetic phenomena , electrical resistivity tomography , piezometer , hydraulic head , streaming current , conductivity , inverse problem , soil science , groundwater , electrical resistivity and conductivity , environmental science , geology , geotechnical engineering , aquifer , materials science , engineering , soil water , mathematics , physics , quantum mechanics , mathematical analysis , electrical engineering , nanotechnology
Pumping tests can be used to estimate the hydraulic conductivity field from the inversion of hydraulic head data taken intrusively in a set of piezometers. Nevertheless, the inverse problem is strongly underdetermined. We propose to add more information by adding self‐potential data taken at the ground surface during pumping tests. These self‐potential data correspond to perturbations of the electrical field caused directly by the flow of the groundwater. The coupling is electrokinetic in nature that is due to the drag of the excess of electrical charges existing in the pore water. These self‐potential signals can be easily measured in field conditions with a set of the nonpolarizing electrodes installed at the ground surface. We used the adjoint‐state method for the estimation of the hydraulic conductivity field from measurements of both hydraulic heads and self potential during pumping tests. In addition, we use a recently developed petrophysical formulation of the streaming potential problem using an effective charge density of the pore water derived directly from the hydraulic conductivity. The geostatistical inverse framework is applied to five synthetic case studies with different number of wells and electrodes and thickness of the confining unit. To evaluate the benefits of incorporating the self‐potential data in the inverse problem, we compare the cases in which the data are combined or not. Incorporating the self‐potential information improves the estimate of hydraulic conductivity field in the case where the number of piezometers is limited. However, the uncertainty of the characterization of the hydraulic conductivity from the inversion of the self‐potential data is dependent on the quality of the distribution of the electrical conductivity used to solve the Poisson equation. Consequently, the approach discussed in this paper requires a precise estimate of the electrical conductivity distribution of the subsurface and requires therefore new strategies to be developed for the joint inversion of the hydraulic and electrical conductivity distributions.