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Self-potential Data (self-potential + data)

Distribution by Scientific Domains

Earth and Environmental Science	50%

Selected Abstracts

Reconstruction of the Water Table from Self-Potential Data: A Bayesian Approach

GROUND WATER, Issue 2 2009
A. Jardani
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 self-potential 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. [source]

The hydroelectric problem of porous rocks: inversion of the position of the water table from self-potential data

GEOPHYSICAL JOURNAL INTERNATIONAL, Issue 2 2004
A. Revil
SUMMARY The self-potential (SP) method is a fast and cheap reconnaissance tool sensitive to ground water flow in unconfined aquifers. A model based on the use of Green's functions for the coupled hydroelectric problem yields an integral equation relating the SP field to the distribution of the piezometric head describing the phreatic surface and to the electrical resistivity contrast through this phreatic surface. We apply this model to SP data measured on the south flank of the Piton de la Fournaise volcano, a large shield volcano located on Réunion island, Indian ocean. The phreatic surface, inverted with the help of the Simplex algorithm from the SP data, agrees well with the available information in this area [one borehole and electromagnetic (EM) data]. This interpretation scheme, which we call electrography, has many applications to the crucial problem of water supply in volcanic areas where drilling is expensive. [source]

Detection of preferential infiltration pathways in sinkholes using joint inversion of self-potential and EM-34 conductivity data

GEOPHYSICAL PROSPECTING, Issue 5 2007
A. Jardani
ABSTRACT The percolation of water in the ground is responsible for measurable electric potentials called self-potentials. These potentials are influenced by the distribution of the electrical conductivity of the ground. Because sinkholes are associated both with self-potential and electrical conductivity anomalies, a joint inversion of EM-34 conductivity and self-potential data is proposed as a way of delineating the location of these features. Self-potential and EM conductivity data were obtained at a test site in Normandy (France) where sinkholes and crypto-sinkholes are present over a karstic area in a chalk substratum overlain by clay-with-flint and loess covers. The presence of sinkholes and crypto-sinkholes is associated with negative self-potential anomalies with respect to a reference electrode located outside the area where the sinkholes are clustered. The sinkholes also have a conductivity signature identified by the EM-34 conductivity data. We used the simulated-annealing method, which is a global optimization technique, to invert jointly EM-34 conductivity and self-potential data. Self-potential and electrical conductivity provide clear complementary information to determine the interface between the loess and clay-with-flint formations. The sinkholes and crypto-sinkholes are marked by depressions in this interface, focusing the groundwater flow towards the aquifer contained in the chalk substratum. [source]