期刊
JOURNAL OF SUPERCRITICAL FLUIDS
卷 119, 期 -, 页码 169-202出版社
ELSEVIER
DOI: 10.1016/j.supflu.2016.09.013
关键词
CCS; Phase equilibrium; E-PPR78 model; PC-SAFT model; Monte Carlo simulation
资金
- French National Agency for Research (ANR) through the SIGARRR project
- French petroleum company TOTAL
- National Nature Science Foundation of China [51404205]
- State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (Southwest Petroleum University) [PLN 1207]
To understand the role played by the impurities (such as N-2, Ar, H-2, CO, SO2, O-2 and NO) during the processes of Carbon Dioxide Capture and Storage (CCS), it is essential to know the thermodynamic properties of the CO2-impurities mixtures under the conditions of CO2 capture, transport and storage. Considering the variety of composition of these gas mixtures, it is necessary to have at one's disposal suitable models to predict their thermodynamic properties. In this work, two thermodynamic models: the E-PPR78 (Enhanced Predictive Peng-Robinson, 1978) and the PC-SAFT (Perturbed-Chain Statistical Associating Fluid Theory) models, are applied for describing the phase equilibria properties of 77 binary CCS mixtures containing CO2, gas impurities (SO2, O-2 and NO), water and hydrocarbons. Our research results indicate that both models are able to accurately predict the phase behavior of binary CCS mixtures. It was however necessary to adjust the binary interaction parameters (k(ij),(PC-SAFT)) within the PC-SAFT model to improve the prediction accuracy. Compared to the PC-SAFT model with one temperature-independent binary interaction parameter, the E-PPR78 model normally shows better prediction accuracy for the investigated systems. In addition, to extend the experimental database which was built for the evaluations of Equation-of-State (EoS) modeling, the Monte Carlo (MC) simulation method is employed in this work to generate phase-equilibrium data of a few CCS mixtures deemed as insufficiently described by experimental measurements reported in the open literature. (C) 2016 Elsevier B.V. All rights reserved.
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