A. J. Whitcomb

Physics-Informed Machine Learning for CO2 Solubility in Brines: Robustness to Noise and Out-Of-Distribution Conditions

Accurate prediction of CO2 solubility in formation brines is central to carbon storage design because dissolution trapping reduces CO2 mobility and supports long term containment. Yet, solubility data and correlations are often limited in coverage, uncertain at high salinity and pressure, and can be unreliable when e...