In recent years geophysical methods have been used increasingly as tools for subsurface transport process characterization. Time-lapse electrical resistivity imaging (ERT) represents a powerful tool for solute transport characterization since a full picture of the spatio-temporal evolution of the process can be obtained. This method can provide spatially and temporally highly resolved information on subsurface parameters which are closely linked to both structural and transport properties. However, a quantitative interpretation of solute tracer experiments is made difficult by the uncertainty related to the ERT data inversion as well as to the a priori unknown hydraulic properties (e.g. porosity, hydraulic conductivity, storativity, etc.) in heterogeneous natural formations. For a conservative solute, also the (arbitrary) initial state of the plume, as defined by its concentration field, controls the subsequent evolution of solute cloud. Here an approach based on the Lagrangian formulation of transport and the ensemble Kalman Filter (EnKF) data assimilation technique is suggested to analyze cross-hole ERT data. The data consist of 3D cross-hole ERT images generated for a synthetic heterogeneous aquifer. Under the assumption that the solute spreads as a passive tracer, for high values of the Peclet number the spatial moments of the evolving plume are dominated by the porosity and the spatial distribution of the hydraulic conductivity. The assimilation of resistivity measurements in terms of low-order spatial concentration moments allows the update of the system state vector, including information about the spatial distribution of hydraulic conductivity. Thus, the assessment of both the concentration evolution and the delineation of the local aquifer heterogeneity can be achieved at the same time by the new methodology proposed to interpret time-lapse electrical images from tracer test experiments. Moreover, the influence of inherent uncertainty in ERT inversion of the same synthetic tracer test experiment is investigated.
Assessment of local hydraulic properties from Electrical Resistivity Tomography monitoring of tracer test experiments
CAMPORESE, MATTEO;CASSIANI, GIORGIO;SALANDIN, PAOLO
2008
Abstract
In recent years geophysical methods have been used increasingly as tools for subsurface transport process characterization. Time-lapse electrical resistivity imaging (ERT) represents a powerful tool for solute transport characterization since a full picture of the spatio-temporal evolution of the process can be obtained. This method can provide spatially and temporally highly resolved information on subsurface parameters which are closely linked to both structural and transport properties. However, a quantitative interpretation of solute tracer experiments is made difficult by the uncertainty related to the ERT data inversion as well as to the a priori unknown hydraulic properties (e.g. porosity, hydraulic conductivity, storativity, etc.) in heterogeneous natural formations. For a conservative solute, also the (arbitrary) initial state of the plume, as defined by its concentration field, controls the subsequent evolution of solute cloud. Here an approach based on the Lagrangian formulation of transport and the ensemble Kalman Filter (EnKF) data assimilation technique is suggested to analyze cross-hole ERT data. The data consist of 3D cross-hole ERT images generated for a synthetic heterogeneous aquifer. Under the assumption that the solute spreads as a passive tracer, for high values of the Peclet number the spatial moments of the evolving plume are dominated by the porosity and the spatial distribution of the hydraulic conductivity. The assimilation of resistivity measurements in terms of low-order spatial concentration moments allows the update of the system state vector, including information about the spatial distribution of hydraulic conductivity. Thus, the assessment of both the concentration evolution and the delineation of the local aquifer heterogeneity can be achieved at the same time by the new methodology proposed to interpret time-lapse electrical images from tracer test experiments. Moreover, the influence of inherent uncertainty in ERT inversion of the same synthetic tracer test experiment is investigated.Pubblicazioni consigliate
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