Summary

Surfactant-based enhanced oil recovery (EOR) is a promising technique because of surfactant's ability to mobilize previously trapped oil by significantly reducing capillary forces at the pore scale. However, the field-implementation of these techniques is challenged by the high cost of chemicals, which makes the margin of error for the deployment of such methods increasingly narrow. Some commonly recognized issues are surfactant adsorption, surfactant partitioning to the excess phases, thermal and physical degradation, and scale-representative phase behavior.

Recent contributions to the petroleum-engineering literature have used the hydrophilic/lipophilic-difference net-average-curvature (HLD-NAC) model to develop a phase-behavior equation of state (EoS) to fit experimental data and predict phase behavior away from tuned data. The model currently assumes spherical micelles and constant three-phase correlation length, which may yield errors in the bicontinuous region where micelles transition into cylindrical and planar shapes.

In this paper, we introduce a new empirical phase-behavior model that is based on chemical-potential (CP) trends and $HLD$ that eliminates NAC so that spherical micelles and the constant three-phase correlation length are no longer assumed. The model is able to describe all two-phase regions, and is shown to represent accurately experimental data at fixed composition and changing $HLD$ (e.g., a salinity scan) as well as variable-composition data at fixed HLD. Further, the model is extended to account for surfactant partitioning into the excess phases. The model is benchmarked against experimental data (considering both pure-alkane and crude-oil cases), showing excellent fits and predictions for a wide variety of experiments, and is compared to the recently developed $HLD$-NAC EoS model for reference.