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Etude de l’inversion jointe spatio-temporelle

par André REVIL - 11 mars 2013 ( dernière mise à jour : 12 mars 2013 )

Nous nous intéressons au problème de l’inversion jointe de données géophysiques couplées à des mesures in situ pour le suivi (monitoring) de différents types de systèmes géologiques comprenant des systèmes volcaniques, les circulations hydriques dans le sous-sol, le suivi de la fracturation hydraulique, et le suivi du front de saturation lors de la production d’un réservoir pétrolier.


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Fig. 1 : Temperature (°C) and soil CO2 concentration (in ppm) measurements with DC resistivity tomogram (in ohm m) along the profile Ginostra-Scari. Resistivity tomogram : vertical scaling factor 1.7, RMS error 16% at iteration 5 using a Gauss-Newton algorithm. Note the asymmetry in both the self-potential profile and resistivity tomogram between the SW and NE sections ; the extension of the hydrothermal system is well delimited to the SW and opened to the NE. The positive self-potential anomalies at 2200 m along the profile are associated with CO2 degassing structures and temperature anomaly. Note the two scales used for the temperature data in order to show the significant fluctuations (in the range 5 to 20 °C) outside the area characterized by the highest temperatures. A to L represents tectonic boundaries discussed in the main text (from Revil et al., 2011). We are currently working on using tome lapse tomography on this type of environment.

Revil A., A. Finizola, T. Ricci, E. Delcher, A. Peltier, S. Barde-Cabusson, G. Avard, T. Bailly, L. Bennati, S. Byrdina, J. Colonge, F. Di Gangi, G. Douillet, M. Lupi, J. Letort, and E. Tsang Hin Sun, Hydrogeology of Stromboli volcano, Aeolian Islands (Italy) from the interpretation of resistivity tomograms, self-potential, soil temperature, and soil CO2 concentration measurements, Geophysical Journal International, 186, 1078–1094, 2011.

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Fig. 2 : Comparison between the true saturation distribution and the inverted saturation distribution. Note that the position of the front is pretty well recovered through the inversion.

Zhang J., A. Revil, M. Karaoulis, 2013, Cross-well 4D resistivity tomography localizes the oil water encroachment front during water flooding, submitted to Geophysics.



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Fig. 3 : Left panel. Flow chart for the processing of the electrical potential data. (1) Instrumentation of the porous block. (2) Data acquisition showing the BioSemi EEG system and the laptop computer. (3) Signal condition of the raw data. (4) Mapping the voltage response using ordinary kriging. (5) Localization of the causative sources in the block. Right panel. Example of snapshot for the self-potential distribution associated with a hydromechanical event and its localization in the block using a combination of Gauss-Newton and genetic algorithms.

Haas A. K., A. Revil, M. Karaoulis, L. Frash, J. Hampton, M. Gutierrez, and M. Mooney, Electrical potential source localization reveals a borehole leak during hydraulic fracturing, Geophysics, 78, 2, D93–D113, 10.1190/GEO2012-0388.1, 2013.

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