On the Identifiability of Relative Permeability and Foam Displacement Parameters in Porous Media Flow

Abstract

This study focuses on analyzing parameter identifiability in foam displacement models during two‐phase flow in porous media, with a particular emphasis on calibrating relative permeability and foam parameters. We employ the profile likelihood technique and Bayesian inference for identifiability analysis. Successful parameter estimation is demonstrated through steady‐state experiments for relative permeability and foam quality scan experiments when both types of experimental data are available and obtained from the same core sample. However, non‐identifiability issues arise when only foam quality scan data is accessible. Additionally, we investigated a standard practice that fits foam parameters using foam quality scan data obtained from one core sample and permeability values obtained from another core sample, but from the same reservoir. Our results show that this practice is ineffective in correctly estimating foam parameters, leading to misestimation of crucial foam model parameters. These findings underscore the importance of a mandatory relative permeability experiment on a representative core sample from the reservoir for accurate characterization of foam parameters. Without it, misestimation of foam model parameters hinders the proper understanding of foam effects on sweeping porous media.