Hydrogeophysics
Self Potential : A Geophysical tool to map groundwater flow patterns
Application to karstic sinkholes :
Jardani. A, J.P. Dupont, and A. Revil, 2006: Self-potential signals associated with preferential groundwater flow pathways in sinkholes. Journal Geophysical Research, VOL. 111, B09204, doi:10.1029/2005JB004231, (pdf)
Self-potential (SP) surveys have been conducted at a test site located in Normandy, in the northwest of France, in a chalk karst in spring and summer 2005. The spring survey showed circular negative SP signals associated with the position of sinkholes and crypto-sinkholes, while the survey conducted during the summer showed fewer anomalies with lesser magnitudes. The negative SP anomalies observed in the spring survey were several tens of millivolts less than a reference located outside the ridge along which the sinkholes are located. In addition to the SP surveys, we also performed a DC electrical resistivity survey. The electrical resistivity tomogram shows the position of the interfaces between the chalk and the overlying clay with flint and loess covers and the position of the sinkholes. A linear relationship is observed between the SP signals and the thickness of the loess layer. In addition, large negative SP anomalies are associated with the sinkholes themselves
Application to pumping and injection tests :
Jardani. A, A. Revil, W. Barrash, and A. Crespy, 2009: Reconstruction of the Water Table from Self-Potential Data: A Bayesian Approach. Ground water., 47(2):213-27, doi: 10.1111/j.1745-6584.2008.00513.x. (pdf)
Ground water flow associated with pumping and injection tests generates self-potential signals that can be measured at the ground surface and used to estimate the pattern of ground water flow at depth. We propose an inversion of the self-potential signals that accounts for the heterogeneous nature of the aquifer and a relationship between the electrical resistivity and the streaming current coupling coefficient. We recast the inversion of the self-potential data into a Bayesian framework. Synthetic tests are performed showing the advantage in using selfpotential signals in addition to in situ measurements of the potentiometric levels to reconstruct the shape of the water table. This methodology is applied to a new data set from a series of coordinated hydraulic tomography, self-potential, and electrical resistivity tomography experiments performed at the Boise Hydrogeophysical Research Site, Idaho. In particular, we examine one of the dipole hydraulic tests and its reciprocal to show the sensitivity of the self-potential signals to variations of the potentiometric levels under steady-state conditions. However, because of the high pumping rate, the response was also influenced by the Reynolds number, especially near the pumping well for a given test. Ground water flow in the inertial laminar flow regime is responsible for nonlinearity that is not yet accounted for in self-potential tomography. Numerical modeling addresses the sensitivity of the self-potential response to this problem.
Coupled Hydrogeophysical Inversion for Hydraulic Tomography
Soueid Ahmed*, A, A. Jardani, A. Revil, J.P. Dupont, 2016 . Specific storage and hydraulic conductivity tomography through the joint inversion of hydraulic heads and self-potential data. Advances in Water Resources. Volume 89, March 2016, Pages 80–90. (pdf)
(* Advised PhD student)
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.
Jardani, A., A. Revil, and J.P. Dupont, 2013: Stochastic joint inversion of hydrogeophysical data for salt tracer test monitoring and hydraulic conductivity imaging. Advances in Water Resources, 52, 62-77, doi: 10.1016/j.advwatres.2012.08.005, 2013. (pdf)
The assessment of hydraulic conductivity of heterogeneous aquifers is a difficult task using traditional hydrogeological methods (e.g., steady state or transient pumping tests) due to their low spatial resolution. Geophysical measurements performed at the ground surface and in boreholes provide additional information for increasing the resolution and accuracy of the inverted hydraulic conductivity field. We used a stochastic joint inversion of Direct Current (DC) resistivity and self-potential (SP) data plus in situ measurement of the salinity in a downstream well during a synthetic salt tracer experiment to reconstruct the hydraulic conductivity field between two wells. The pilot point parameterization was used to avoid over-parameterization of the inverse problem. Bounds on the model parameters were used to promote a consistent Markov chain Monte Carlo sampling of the model parameters. To evaluate the effectiveness of the joint inversion process, we compared eight cases in which the geophysical data are coupled or not to the in situ sampling of the salinity to map the hydraulic conductivity. We first tested the effectiveness of the inversion of each type of data alone (concentration sampling, self-potential, and DC resistivity), and then we combined the data two by two. We finally combined all the data together to show the value of each type of geophysical data in the joint inversion process because of their different sensitivity map. The results of the inversion revealed that incorporating the self-potential data improves the estimate of hydraulic conductivity field especially when the self potential data were combined to the salt concentration measurement in the second well or to the time-lapse cross-well electrical resistivity data.
