AbstractA fugacity-based thermodynamic model for hydrate has been used to determine the equilibrium pressures of hydrate formation. This fugacity-based model uses the PRSV equation of state, which is used to represent the gas phases in the hydrate. The parameters of the model are fitted to the experimental data of binary guest hydrates. The present study is aimed at investigating binary mixtures of {\text{CH}_{4}}–{\text{H}_{2}}S, {\text{C}_{3}}{\text{H}_{8}}–{\text{N}_{2}}, {\text{N}_{2}}–{\text{CO}_{2}}, {\text{CH}_{4}}–i-butane, {\text{C}_{3}}{\text{H}_{8}}–i-butane, {\text{CH}_{4}}–n-butane, {\text{C}_{3}}{\text{H}_{8}}–n-butane, i-butane–{\text{CO}_{2}}, and n-butane–{\text{CO}_{2}} hydrates, which have not been modeled before. Unlike previous studies, the Kihara potential parameters were obtained using the second virial coefficient correlation and the data of viscosity for gases. The fugacity-based model provides reasonably good predictions for most of the binary guest hydrates ({\text{CH}_{4}}–{\text{C}_{3}}{\text{H}_{8}}). However it does not yield good prediction for hydrates of ({\text{CO}_{2}}–{\text{C}_{3}}{\text{H}_{8}}). The transitions of hydrate structure from sI to sII and from sII to sI have been also predicted by this model for binary guest hydrates. The AAD % calculated using the experimental data of natural gas hydrates is only 10 %, which is much lower than the AAD % calculated for the equilibrium data predicted by the VdP-w model.
Integrating Support Vector Regression with Genetic Algorithm for Hydrate Formation Condition Prediction
