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Prediction of compressibility factor for gas condensate under a wide range of pressure conditions based on a three-parameter cubic equation of state.

Authors :
Li, Changjun
Peng, Yang
Dong, Jingya
Source :
Journal of Natural Gas Science & Engineering; Sep2014, Vol. 20, p380-395, 16p
Publication Year :
2014

Abstract

The gas compressibility factor as an essential thermodynamic parameter is often used to analyze PVT behavior in natural gas engineering. To accurately predicate it for various gas condensates, a data base containing 916 data sets covering a wide range of experimental conditions is employed to establish and test the prediction model based on a three-parameter cubic equation of state (EoS). The presented model which based on EPT EoS combines with Elliott-Daubert binary interaction coefficients correlation, Ahmed et al. splitting and Hosseinifar-Jamshidi characterization methods is superior to conventional empirical correlations with three mixing rules and two-parameter EoSs as SRK, PR, PRSV and MPR2. Statistical error analysis shows that it outperforms empirical correlations with average absolute relative errors of 1.45% and coefficient of determination of 0.989. At pressure and temperature up to 95.04 MPa and 429.3 K, respectively, the model also outperforms two-parameter EoSs with average absolute relative errors of 1.65% and coefficient of determination of 0.992. The presented model is efficient and practical for predicting the compressibility factor of gas condensate. Four three-parameter EoSs are evaluated at different temperatures and pressures. Three BIC determining methods are compared for various gas condensates. Six characterization methods for pseudo components are optimized. A new method is proposed for gas condensate at a wide range of pressure conditions. The accuracy of the method is better than applied empirical correlations and EoSs. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18755100
Volume :
20
Database :
Supplemental Index
Journal :
Journal of Natural Gas Science & Engineering
Publication Type :
Academic Journal
Accession number :
97660322
Full Text :
https://doi.org/10.1016/j.jngse.2014.07.021