HR: 1340h
AN: H23A-1006    [Abstracts]
TI: Use of high-resolution geophysical data to characterize the porosity distribution in heterogeneous aquifers: Influence of inversion and data integration method on hydrological predictions
AU: * Dafflon, B
EM: baptiste.dafflon@unil.ch
AF: Institute of Geophysics, University of Lausanne, Lausanne, 1015, Switzerland
AU: Irving, J
EM: james.irving@unil.ch
AF: Institute of Geophysics, University of Lausanne, Lausanne, 1015, Switzerland
AU: Holliger, K
EM: klaus.holliger@unil.ch
AF: Institute of Geophysics, University of Lausanne, Lausanne, 1015, Switzerland
AB: Knowledge of the detailed distribution of hydrological parameters in heterogeneous aquifers is a key prerequisite for accurate simulation of groundwater flow and contaminant transport. The integration of high-resolution geophysical data into the subsurface characterization problem has been shown in many cases to significantly improve our knowledge of hydrological parameters by providing information at spatial scales that are unattainable using conventional measurement techniques. However, the hydrological significance of many of the choices made during the complex process of geophysical data integration (e.g., data processing and inversion techniques, integration/simulation methodology) has not been fully evaluated. In addition, evaluation of how much benefit is brought by the geophysical data for various types of hydrological models has not been thoroughly investigated. Understanding these issues is critical to making wise decisions about how to use the geophysical data. Here, we examine some of these issues for the case of porosity characterization in saturated heterogeneous aquifers using crosshole ground-penetrating radar (GPR) and borehole porosity log data. To begin, we generate a number of different porosity fields that exhibit varying degrees of continuity and structural complexity. Next, we simulate the collection of crosshole GPR data between several boreholes in these fields, and the collection of porosity log data at the borehole locations. The synthetic GPR data are then tomographically inverted for the spatial distribution of electromagnetic wave velocity using a variety of inversion techniques. Together with the synthetic porosity logs, the resulting tomographic images are used to reconstruct the porosity field through Monte- Carlo conditional simulations. To accomplish this, we again use a variety of methods, including sequential simulation and simulated annealing. The resulting realizations of porosity, obtained using the various combinations of inversion and data integration techniques, are then used as basis information to infer the hydraulic conductivity field and perform groundwater flow and contaminant transport simulations. This allows us to assess the hydrological significance of our choice of geophysical inversion and data integration methods.
DE: 1829 Groundwater hydrology
DE: 1835 Hydrogeophysics
DE: 3252 Spatial analysis (0500)
DE: 3275 Uncertainty quantification (1873)
DE: 6982 Tomography and imaging (7270, 8180)
SC: Hydrology [H]
MN: 2007 Fall Meeting