Modeling of High Pressure and Temperature Microemulsion Experiments Using HLD-NAC Based Equation of State

Surfactant flooding is a promising technique that can reduce interfacial tension (IFT) between oil and water to ultra-low values, mobilizing previously trapped oil. For reservoirs at moderate to high pressures, understanding and modeling how pressure affects the phase behavior of a surfactant-brine-oil system is crucial to the design and implementation of efficient/cost-effective surfactant flooding project. Typical phase behavior experiments and models are done only at low pressures. Objective of this paper is to comprehensively model realistic range of pressure, temperature, and other parameters, using hydrophilic-lipophilic deviation (HLD) and net-average curvature (NAC) based equation-of-state (EoS). This paper shows how to model an anionic surfactant system consisting of a surfactant, co-solvent, brine (up to 10 wt%) and synthetic oil over a large range in pressure (up to 8000 psi), temperature (up to 60 °C), and compositions. The model is developed from measurements made using a high-pressure PVT cell. Parameters such as the oil-water ratio and the surfactant concentration were varied in ternary space under both atmospheric and reservoir conditions. Selected experimental results were then matched to our new EoS based on HLD-NAC. The advantage of this approach is that the tuned model can predict phase behavior in a unified way for all experiments. The pressure and temperature scans show that pressure has a significant effect on the surfactant microemulsion phase behavior, shifting it from an optimal three-phase system at low pressure to a nonoptimal two-phase system at high pressure. Further, multiple scans at different oil-water ratios show a shift in the optimum indicating that phase behavior partitioning of the various components is changing with oil saturation. In addition, we show how to determine the optimum pseudocomponent composition for such a ternary pseudocomponent system. We further show that the micellar correlation length in the three-phase region can be predicted well using linear functions with temperature, pressure, and salinity. The change in characteristic length is a critical aspect of modeling the phase behavior accurately with the HLD-NAC EoS, and ultimately to predict and scale the phase behavior for other reservoir conditions. We show that there is a well-defined optimum 3D surface in the pressure, temperature, and salinity space that can aid the design of surfactant floods for field use and reduce the risk of those projects. Further, the use of the tuned HLD-NAC EoS can define and reduce the number of experiments needed to model the optimum owing to a unified EoS prediction of the phase behavior. When input into a numerical simulator, the improved prediction of the size and shape of the two-phase lobes with changing pressure, temperature, and salinity will also improve estimations of surfactant slug size needed to maintain ultra-low IFTs.