Water Resources Research 31(4), 913-924, April 1995
Solving the Estimation-Identification Problem
in Two-Phase Flow Modeling
Stefan Finsterle and Karsten Pruess
Lawrence Berkeley National Laboratory, Earth Sciences Division
University of California, Berkeley, CA 94720
Abstract.
A procedure is presented to solve the estimation-identification problem in
two-phase flow modeling. Given discrete observations made on the system response, an
optimum parameter set is derived for an appropriate conceptual model by solving the inverse
problem using standard optimization techniques. Subsequently, a detailed error analysis is
performed, and nonlinearity effects are considered. We discuss the iterative process of model
identification and parameter estimation for a ventilation test performed at the Grimsel Rock
Laboratory, Switzerland. A numerical model of the ventilation drift and the surrounding
crystalline rock matrix is developed. Evaporation of moisture at the drift surface and the
propagation of the unsaturated zone into the formation is simulated. A sensitivity analysis
is performed to identify the parameters to be estimated. Absolute permeability and two
parameters of van Genuchten's characteristic curves are subsequently determined based on
measurements of negative water potentials, evaporation rates, and gas pressure data. The
performance of the minimization algorithm and the system behavior for the optimum
parameter set are discussed. The study shows that a field experiment conducted under two-
phase flow conditions can be successfully reproduced by taking into account a variety of
physical processes, and that it is possible to reliably determine the two-phase hydraulic
properties that are related to the given conceptual model.
