首页|Assessing uncertainties and identifiability of foam displacement models employing different objective functions for parameter estimation
Assessing uncertainties and identifiability of foam displacement models employing different objective functions for parameter estimation
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NSTL
Foam injection in porous media is often used to control the gas fingering in multi-phase flow. Mathematical models of foam dynamics involve non-Newtonian formulations. To numerically simulate these complex phenomena, experimental data is gathered and used to estimate the parameter values of models via optimization techniques. The present work improves this procedure by introducing a new objective function based on the mobility reduction factor and does not require further experimental observations other than those usually obtained in core-flooding experiments. A series of numerical experiments were carried out to show the features and robustness of the proposed approach. In particular, the identifiability analysis results show that key parameters of the models are practically non-identifiable when using traditional objective functions that rely only on apparent viscosity. When the proposed objective function is used for parameter estimation, the identifiability issues are solved. In addition, the uncertainty quantification analysis revealed that lower uncertainty is achieved when using the new objective function when compared to the one that uses only apparent viscosity. In summary, we show that the new objective function generates better-calibrated models with high fidelity and low uncertainties and alleviates parameter non-identifiability issues. Therefore, the results suggest the new objective function is better suited for calibrating foam displacement models for enhanced oil recovery.
NSTL
