HR: 08:15h
AN: H21G-02    [Abstracts]
TI: Gradual Deformation Method as a Geostatistical Based Inverse Method for the Estimation of Flow and Transport Parameters of a Heterogeneous Aquifer : Application to the Waste Isolation Pilot Plant Site (New Mexico, USA).
AU: * MOUCHE, E
EM: emmanuel.mouche@cea.fr
AF: Laboratoire des Sciences du Climat et de l'Environnement, UMR1572 CEA-CNRS, Orme des Merisiers, Gif sur Yvette, 91191 France
AU: ZAKHAROV, P
EM: paul.zakharov@cea.fr
AF: Laboratoire des Sciences du Climat et de l'Environnement, UMR1572 CEA-CNRS, Orme des Merisiers, Gif sur Yvette, 91191 France
AB: Gradual Deformation Method (GDM) is a geostatistical based inverse method developed since the end of the 90's by L.Y. Hu and coworkers of the French Institute of Petroleum (IFP) for oil reservoir simulations. This method aims to calibrate reservoir stochastic simulations on existing experimental data (pressure transient, well production, water cut, .). Basically GDM consists in optimizing successive combinations of independent realizations of a stochastic model until the minimum of a given objective function is reached. This objective function, for instance the root square mean error between model outputs and experimental data, depends on the combinations coefficients and experience shows that convergence is reached with a few coefficients only. GDM presents a number of advantages among which the preservation of the stochastic model : if the model is multi-gaussian the model remains multi-gaussian . From a physical point of view, GDM allows the inversion of tough problems like transient non linear flow in highly heterogeneous media. It has been successfully applied to synthetic fields and real 3D oil fields. Though the method is applicable to subsurface hydrology, only few attempts were made. The work presented here aims to show the applicability of GDM for the calibration of heterogeneous aquifer properties. It is a part of a research program on the inversion of flow and tracer tests in heterogeneous media and on their contribution in the calibration of aquifer properties. After a first step, where we show on synthetic fields how GDM works, we apply it, in a second step, to the WIPP (Waste Isolation Pilot Plant, New Mexico, USA) site, namely to the calibration of the transmissivity of the Culebra Dolomite aquifer. The WIPP site is famous in the geostatistical community as it served, ten years ago, as a test case for the intercomparison of geostatistical models. Here we calibrate the transmissivity field of the Culebra Dolomite with permanent data only, 46 transmissivity data and 37 head data . The incorporation of transient data (pumping data) is underway. Our results show that the method works pretty well and the root mean square error on head decrease during deformation from a value of 7 meters down to less than 3 meters, which is comparable to published results. The 100 calibrated transmissivity realizations are analyzed in a statistical framework, in terms of mean and variance. The impact on flow pathlines is also discussed.
DE: 1829 Groundwater hydrology
DE: 1869 Stochastic hydrology
DE: 3260 Inverse theory
SC: Hydrology [H]
MN: Fall Meeting 2005