Abstract
The application of CO2 injection and storage technology relies on a thorough understanding of the underlying physical processes.
In the absence of extensive experimental databases, accurate thermodynamic models play a crucial role in the prediction of properties required for the design and operation of injection-storage systems.
Real CO2 injection and storage applications encounter the presence of several impurities, which increase the challenge of accurately predicting related properties.
This work explores the prediction accuracy of CO2 binary mixtures, focusing on properties of practical importance, including thermodynamic properties like density, speed of sound, and transport properties such as viscosities and thermal conductivities.
Several widely used modeling approaches are applied to the available experimental data, enabling a systematic comparison of their predictive performance.
In addition, the multiparameter Helmholtz energy-based equation of state EOSCG21, developed primarily for CO₂-related applications, is presented and evaluated.
The study highlights the current state of property prediction for CO₂ mixtures and identifies the areas where experimental data remain limited.
The results provide insight into the strengths and limitations of existing modeling approaches and help target areas that could enhance the modeling of CO2 injection and storage systems.