Quantifying Experimental Impacts on Non-Newtonian Foam Characterization for Flow Modeling in Porous Media: Insights From Foam-Quality and Flow Rate Scan Experiments

Abstract

Foam injection is a prominent technique for mitigating the effects of high gas mobility in porous media for Enhanced Oil Recovery, Carbon Capture, Utilization and Storage and well-stimulation. Experiments reveal that the foam's apparent viscosity exhibits shear-thinning behavior, meaning its viscosity decreases with superficial velocity. Foam parameters are commonly characterized using only single-velocity foam-quality scan data. However, this approach can introduce significant uncertainty when evaluating foam's apparent viscosity at different velocities. This study conducts foam-quality and flow rate scan experiments. Characterization of foam, using both single- and multi-velocity data, is performed using computational models and the solution of the associated inverse problems. Identifiability analysis and inverse and forward uncertainty quantification are performed to evaluate errors associated with the different data sets. The results demonstrate that relying only on foam-quality scan data leads to underestimation or overestimation of foam's apparent viscosity, with errors of up to 62.5%. The impact of these misfitting issues is assessed in a heterogeneous scenario, where differences in production levels, breakthrough time, and pressure drops are analyzed with errors of 2.5%, 14.8%, and 45%, respectively. Therefore, this study underscores the importance of aligning laboratory experiments with parameter estimation methodologies that accurately characterize the non-Newtonian behavior of foams.