An Improved HLD-NAC Model for Microemulsion Phase Behavior Study

Microemulsion phase behavior studies are essential for screening surfactants for improving oil production. The paper presents a modified Hydrophilic-Lipophilic Deviation – Net Average Curvature (HLD-NAC) model to explicitly express the solubilization ratio with respect to a newly defined inherent parameter representing surfactant properties. It also provides a workflow to extract the critical parameters from experimental results for numerical simulation of a chemical flooding process. The equations were derived to calculate the window of Winsor Type III microemulsion. The HLD-NAC model was improved to make the solubilization ratio explicitly expressed with the inherent parameter composed of head area (as), tail length (L) and molecular weight of the surfactants (Mw). An innovated workflow was developed to integrate the microemulsion phase behavior scanning results with the HLD-NAC model. The HLD-NAC model was validated with experimental data of various surfactant formulations. The inherent parameter was applied in the improved HLD-NAC model, making it efficient for modeling microemulsion phase behavior scanning. The data of solubilization ratio and phase volume fraction were well fit in the model without needing to know the details of surfactant properties. This simplified the input of HLD-NAC parameters and made the output more accurate. The HLD-NAC model was successfully validated by experiments with various formulations including surfactant with alcohol, surfactant mixtures, and sodium carbonate-surfactant mixtures. By automatically obtaining the inherent parameter, the improved HLD-NAC model provides a promising application of microemulsion phase behavior in numerical simulation of chemical flooding. The HLD-NAC model is modified by defining an inherent parameter from experimental results of microemulsion phase behavior scanning. This makes it applicable to generate the solubilization ratio parameter for numerical simulation of chemical flooding.