(83d) A Novel Density Gradient Theory for Surfactant Molecules – Applied to Oil/Water Interfaces

In the upstream operations of the oil & gas industry, water and surfactant can be injected into the reservoir for enhanced oil recovery (EOR). The surfactant mobilizes trapped oil by reducing the interfacial tension (IFT) between oil and water, and thus increased the oil recovery efficiency. Predicting the IFT of water/oil/surfactant mixtures is essential for the design of EOR processes. To interpolate and extrapolate expensive experimental data, different theoretical and simulation methods have been developed to model the interfacial properties of reservoir mixtures. Among these methods, density gradient theory (DGT) has become a fast and accurate tool in the interfacial property prediction of many alkane mixtures. However, several physical and numerical issues of DGT restrict its application in more complex systems such as water containing and surfactant containing systems. In this paper, we presented a novel density gradient theory to predict the interfacial properties of water/oil/surfactant mixtures, and also extended our stabilized density gradient theory (SDGT) algorithm to fit with the new model. A characteristic of surfactant molecules is the ability to span the interface; however, conventional DGT uses a single position for the molecule, which limits its ability and accuracy to describe the surfactant behavior. In this work we redefined the DGT free energy to include head and tail components of a surfactant molecule by introducing a chain free energy functional. We also optimized the SDGT algorithm to speed up calculations with associating molecules (e.g., water and surfactant molecules). By taking advantage of the optimized SDGT algorithm, the new DGT was applied to calculate the IFT of several water/oil/surfactant mixtures. The numerical stability of the optimized SDGT algorithm was tested, and the IFT calculation results were quantitatively verified with laboratory data.