AQUALE SPRL

Noville-les-Bois, Belgium

AQUALE SPRL

Noville-les-Bois, Belgium
SEARCH FILTERS
Time filter
Source Type

Lesparre N.,University of Liège | Nguyen F.,University of Liège | Kemna A.,University of Bonn | Robert T.,AQUALE SPRL | And 3 more authors.
Geophysics | Year: 2017

Applications of time-lapse inversion of electrical resistivity tomography allow monitoring variations in the subsurface that play a key role in a variety of contexts. The inversion of timelapse data provides successive images of the subsurface properties showing the medium evolution. Image quality is highly dependent on the data weighting determined from the data error estimates. However, the quantification of errors in the inversion of time-lapse data has not yet been addressed. We have developed a methodology for the quantification of time-lapse data error based on the analysis of the discrepancy between normal and reciprocal readings acquired at different times. We applied the method to field monitoring data sets collected during the injection of heated water in a shallow aquifer. We tested different error models to indicate that the use of an appropriate time-lapse data error estimate yielded significant improvements in terms of imaging. An adapted inversion weighting for time-lapse data implies that the procedure does not allow an over-fitting of the data, so the presence of artifacts in the resulting images is greatly reduced. Our results determined that a proper estimate of time-lapse data error is mandatory for weighting optimally the inversion to obtain images that best reflect the evolution of medium properties over time. © 2017 Society of Exploration Geophysicists.


Hermans T.,University of Liège | Nguyen F.,University of Liège | Robert T.,AQUALE SPRL | Revil A.,Colorado School of Mines | Revil A.,CNRS Institute of Earth Sciences
Energies | Year: 2014

Low enthalpy geothermal systems exploited with ground source heat pumps or groundwater heat pumps present many advantages within the context of sustainable energy use. Designing, monitoring and controlling such systems requires the measurement of spatially distributed temperature fields and the knowledge of the parameters governing groundwater flow (permeability and specific storage) and heat transport (thermal conductivity and volumetric thermal capacity). Such data are often scarce or not available. In recent years, the ability of electrical resistivity tomography (ERT), self-potential method (SP) and distributed temperature sensing (DTS) to monitor spatially and temporally temperature changes in the subsurface has been investigated. We review the recent advances in using these three methods for this type of shallow applications. A special focus is made regarding the petrophysical relationships and on underlying assumptions generally needed for a quantitative interpretation of these geophysical data. We show that those geophysical methods are mature to be used within the context of temperature monitoring and that a combination of them may be the best choice regarding control and validation issues. © 2014 by the authors.

Loading AQUALE SPRL collaborators
Loading AQUALE SPRL collaborators