A Review of the Applications of the SAFT Equation of State in the Oil and Gas Industry

The accurate prediction of thermodynamic properties for complex petroleum fluids is critical for all stages of oil and gas operations, but traditional cubic equations of state (EOS) face fundamental limitations with asymmetric and associating mixtures. The Statistical Associating Fluid Theory (SAFT) offers a powerful, molecularly-based alternative, employing a "bottom-up" approach derived from statistical mechanics to link macroscopic properties to microscopic molecular features. This review synthetically examines the diverse applications of the SAFT framework in the petroleum industry, highlighting its superior performance over cubic EoS in crucial areas such as liquid density prediction, characterization of heavy C۷+ fractions, and modeling fluids under high-pressure, high-temperature (HPHT) conditions. SAFT's transformative impact is particularly evident in flow assurance, where its ability to explicitly model chain formation and association phenomena makes it an indispensable tool for predicting asphaltene precipitation, wax deposition, and gas hydrate formation. The review explores the evolution of the SAFT family, from the widely adopted industry standard Perturbed-Chain SAFT (PC-SAFT) to more advanced variants like SAFT-y Mie, which offer enhanced physical realism and predictive power for a range of specialized applications. A critical assessment is provided on the framework's limitations, primarily the challenges of pure-component parameterization, higher computational demands compared to cubic models, and known theoretical deficiencies. Future frontiers are discussed, including the development of group-contribution methods for enhanced predictability, integration with machine learning, and the extension of SAFT to emerging energy transition challenges like carbon capture and hydrogen storage. The paper concludes that despite its challenges, SAFT's robust physical foundation and versatility have established it as an essential and evolving tool for addressing the complex thermodynamic problems inherent in the modern energy landscape.

Keywords:

Statistical Associating Fluid Theory (SAFT) , PC-SAFT , Equation of State (EOS) , Oil and Gas Industry , Thermodynamic Modeling