Mechanistic Modeling of Nanoparticle-stabilized Supercritical CO2 Foams and its Implication in Field-scale EOR Applications

Previous experimental studies show that nanoparticle-stabilized supercritical CO2 foams (or, NP CO2 foams) can be applied as an alternative to surfactant foams, in order to reduce CO2 mobility in gas injection enhanced oil recovery (EOR). These nanoparticles, if chosen correctly, can be an effective foam stabilizer attached at the fluid interface in a wide range of physicochemical conditions.

By using NP CO2 foam experiments available in the literature, this study performs two tasks: (i) presenting how a mechanistic foam model can be used to fit experimental data and determine required model parameters, and (ii) investigating the sweep efficiency in a condition similar to Lisama Field, in Colombia, by using relevant gas mobility reduction data in CMG STARS simulations, contrasting NP CO2 foams to surfactant foams in both dry and wet foam injection methods.

The results show how the model can successfully reproduce coreflood experimental data, creating three different foam states (weak-foam, strong-foam and intermediate states) and two steady-state strong-foam regimes (high-quality and low-quality regimes). When the gas mobility reduction factors ranging up to 10 from the model fit are applied in the field-scale simulations, the use of nanoparticles improves oil recovery compared to gas-water co-injection, but not as efficient as successful surfactant foam injection does. This implies that although nanoparticle-stabilized foams do provide some benefits, there still seems some room to improve stability and strength of resulting foams.