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Solving the Estimation‐Identification Problem in Two‐Phase Flow Modeling
Author(s) -
Finsterle Stefan,
Pruess Karsten
Publication year - 1995
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/94wr03038
Subject(s) - inverse problem , estimation theory , nonlinear system , sensitivity (control systems) , system identification , mathematics , mathematical optimization , flow (mathematics) , minification , inverse , control theory (sociology) , biological system , algorithm , computer science , engineering , mathematical analysis , data modeling , physics , geometry , control (management) , quantum mechanics , database , electronic engineering , artificial intelligence , biology
In this paper 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 are 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.