Correlation/Prediction of CO2 Solubility in Single-Salt and Multi-Salt Brines Using PR EOS Incorporated With Modified Alpha Functions and BIP Correlations

Abstract

Abstract Accurate prediction of CO2 solubility in brine is of high significance for carbon capture, utilization, and storage (CCUS); however, no generalized methodology has been made available to successfully tackle such a technical challenge. In this study, a pragmatic and robust technique has been developed and generalized to correlate the CO2 solubility in single-salt brines using the Peng-Robinson equation of state (PR EOS) together with the modified alpha functions and binary interaction parameter (BIP) correlations. A comprehensive CO2 solubility database is firstly built to cover a large range of temperatures, pressures, salt concentrations, while five different salts (i.e., NaCl, KCl, CaCl2, MgCl2, and Na2SO4) are involved. By integrating with the modified alpha functions and BIP correlations, such a generalized model is found to yield an average absolute relative deviation (AARD) of 5.24%, 5.82%, 7.64%, 6.04%, and 4.61% for the correlated CO2 solubility in the aforementioned five single-salt brines, respectively. Compared with the existing correlations, the PR EOS-based model is better than the existing OLI, SP 2010, and DS 2006 models but only slightly inferior to the PSUCO2 model under certain conditions. By combining a new BIP correlation, the newly proposed model has been extended to predict the CO2 solubility in multi-salt brines with an AARD of 7.21%. In addition to its simplicity and high accuracy, this new model can be used to not only determine other physical properties including density, enthalpy, and interfacial tension of CO2-brine systems, but seamlessly integrate with any reservoir simulators, allowing for accurately evaluating and predicting performance of CO2 enhanced oil recovery and storage capacity under various conditions.