Measurement and PC-SAFT modelling of three-phase behaviour

Area of Science:

• Thermodynamics
• Chemical Engineering
• Physical Chemistry

Background:

• Multi-component systems with complex interactions present modeling challenges in thermodynamics.
• Three-liquid-phase systems are vital for applications like separation processes, catalysis, and enhanced oil recovery (EOR).
• Optimal surfactant flooding for EOR relies on formulations exhibiting three-phase behavior to achieve low interfacial tension.

Purpose of the Study:

• To apply the Perturbed Chain Statistical Association Fluid Theory (PC-SAFT) equation of state for predicting equilibrium in triphasic systems.
• To evaluate the PC-SAFT model's predictive capability using only pure-component parameters for ternary systems relevant to EOR.
• To assess the model's accuracy against experimental data for specific water-surfactant-oil systems.

Main Methods:

• Utilized the PC-SAFT equation of state for thermodynamic modeling.
• Focused on predicting phase equilibrium in ternary systems: (water + [C10mim][NTf2] + n-dodecane) and (water + [C12mim][NTf2] + n-dodecane).
• Employed solely pure-component parameters for initial model predictions, with optional binary interaction parameters for refinement.

Main Results:

• The PC-SAFT model accurately predicted the three-phase behavior of the studied ternary systems without requiring any fitting parameters.
• Excellent agreement was observed between experimental and predicted compositions for the systems at 298.15 K and atmospheric pressure.
• Slightly higher deviations at 348.15 K were noted, which could be mitigated by introducing a single binary interaction parameter.

Conclusions:

• The PC-SAFT equation of state is a powerful tool for predicting triphasic behavior in systems relevant to enhanced oil recovery.
• The model's ability to predict phase equilibrium using only pure-component parameters offers a significant advancement for upstream oil operations.
• This approach enables faster and more cost-effective initial screening of potential surfactants for EOR applications.