Modelling of phase equilibria in CH4–C2H6–C3H8–nC4H10–NaCl–H2O systems

Abstract

A thermodynamic model is presented for the mutual solubility of CH4–C2H6–C3H8–nC4H10–brine systems up to high temperature, pressure and salinity. The Peng–Robinson model is used for non-aqueous phase fugacity calculations, and the Pitzer model is used for aqueous phase activity calculations. The model can accurately reproduce the experimental solubilities of CH4, C2H6, C3H8 and nC4H10 in water or NaCl solutions and H2O solubility in the non-aqueous phase. The experimental data of mutual solubility for the CH4–brine subsystem are sufficient for temperatures exceeding 250°C, pressures exceeding 1000bar and NaCl molalities greater than 6molal. Compared to the CH4–brine system, the mutual solubility data of C2H6–brine, C3H8–brine and nC4H10–brine are not sufficient. Based on the comparison with the experimental data of H2O solubility in C2H6-, C3H8- or nC4H10-rich phases, the model has an excellent capability for the prediction of H2O solubility in hydrocarbon-rich phases, as these experimental data were not used in the modelling.Predictions of hydrocarbon solubility (at temperatures up to 200°C, pressures up to 1000bar and NaCl molalities greater than 6molal) were made for the C2H6–brine, C3H8–brine and nC4H10–brine systems. The predictions suggest that increasing pressure generally increases the hydrocarbon solubility in water or brine, especially in the lower-pressure region. Increasing temperature usually decreases the hydrocarbon solubility at lower temperatures but increases the hydrocarbon solubility at higher temperatures. Increasing water salinity dramatically decreases the hydrocarbon solubility.The experimental solubility data for hydrocarbon mixtures in water are not sufficient or systematic. Comparisons were made between the experimental data and the results of the model calculations. Most of the experimental data can be well predicted by this model with slightly higher discrepancies. More systematic experimental studies are needed to improve the model.