The simulation of underground geological storage (UGS) of CO₂ requires reliable predictions of how it interacts with the surrounding brine and rock minerals. Existing models struggle to represent such complex real-life systems consistently.
This project will develop a more accurate thermodynamic framework, support the scientific assessment and industrial deployment of CO₂ storage and thus contribute to reducing greenhouse-gas emissions.
Carbon capture and storage (CCS) simulations require thermodynamic models that can describe real electrolyte systems. CO₂ partitions between phases, dissolves in brine, changes aqueous speciation and pH and can promote mineral dissolution and precipitation. These processes are coupled, influence storage capacity and must be represented consistently across relevant temperatures, pressures and salt concentrations.
This PhD project will develop a thermodynamic framework that also accounts for weak electrolytes relevant to CO₂ systems. An electrolyte equation of state, potentially based on CPA, PC-SAFT or SAFT-VR Mie, will be integrated with a theoretical description of the dielectric constant and an ion-pairing contribution. This will enable molecular interactions, chemical reactions and phase behaviour to be described within a consistent framework.
Chemical-equilibrium algorithms will be coupled to the equation of state so that phase equilibrium, electrolyte speciation and pH can be calculated simultaneously. The framework will subsequently be extended to solid–liquid equilibrium (SLE) to predict mineral dissolution and precipitation, including systems involving multiple pure solid phases.
The model will be implemented computationally and validated primarily against experimental data reported in the literature. Depending on the progress of the project, comparisons with available microfluidic CO₂-flow data may also be considered.
The project will provide a physically consistent, predictive and computationally efficient foundation for reservoir-scale CO₂-storage simulations. This could improve the evaluation of storage behaviour and support more efficient development of carbon capture and storage technologies.
Main supervisor:
Professor Xiaodong Liang
Co- supervisor:
Professor Georgios M. Kontogeorgis