Dimensionless Analysis and Scale-Up of Experiments with Heavy Oil

Abstract This study investigates the scaling criteria used to evaluate immiscible water and chemical floods, and miscible solvent injection and VAPEX processes by deriving dimensionless groups. We present findings from various flooding experiments and evaluate the interplay between viscous and capillary forces as functions of oil viscosity, injection velocity, and porous media characteristics. Updated dimensionless times, capillary numbers, and diffusion numbers were derived from the results of different core floods, which accurately predict recovery performance for different solvent and chemical types, injection rates, and rock properties. The capillary number (Nca) and dimensionless time (tD) are the most commonly used dimensionless numbers to characterize oil recovery performance in porous media. Nca balances forces at a given moment, and tD captures the displacement process over time. However, none of these individual numbers accurately correlate with the recovery factor. To address this, we incorporated viscosity ratios, oil density, reservoir thickness, porosity, and permeability, and adjusted the exponent for each term in new dimensionless numbers. We propose combined dimensionless scales to predict oil production in immiscible and miscible floods. The effect of each dimensionless group in our proposed numbers on oil recovery was examined through sensitivity analysis. The proposed updated dimensionless numbers successfully predicted oil recovery for water flooding, chemical flooding, and solvent injection in heavy oil systems. It was found that while traditional dimensionless numbers failed to accurately correlate with the recovery factor, our modified dimensionless numbers improved oil recovery prediction across varying viscosity ratios, solvent types, injection velocities, and core porosities and permeabilities. Incorporating oil density and reservoir height into Nenniger's dissolution term enabled the development of a new capillary number, Nca*, which improved the prediction of oil recovery during solvent injection processes. Our results showed increased recovery efficiency with higher Nca* values, as viscous forces overcame capillary forces. Dimensionless parameters provide accurate scaling from laboratory to field conditions. While extensive dimensionless analysis has been conducted on waterflooding, little work has focused on developing scaling laws for solvent flooding in heavy oil reservoirs. Our study demonstrated that the incorporation of viscosity ratio and dissolution term improved the accuracy of the existing dimensionless numbers in predicting oil production during immiscible and miscible flooding.