Thermodynamic modeling and correlations of CH4, C2H6, CO2, H2S, and N2 hydrates with cage occupancies

Abstract

Abstract The present work focuses on developing a framework for accurate prediction of thermodynamic conditions for single-component hydrates, namely CH4, CO2, N2, H2S, and C2H6 (coded in MATLAB). For this purpose, an exhaustive approach is adopted by incorporating eight different equations of states, namely Peng–Robinson, van der Waals, Soave–Redlich–Kwong, Virial, Redlich–Kwong, Tsai-Teja, Patel, and Esmaeilzadeh–Roshanfekr, with the well-known van der Waals–Platteeuw model. Overall, for I–H–V phase region, the Virial and van der Waals equation of state gives the most accurate predictions with minimum AAD%. For L w–H–V phase region, Peng–Robinson equation of state is found to yield the most accurate predictions with overall AAD of 3.36%. Also, genetic programming algorithm is adopted to develop a generalized correlation. Overall, the correlation yields quick estimation with an average deviation of less than 1%. The accurate estimation yields a minimal AAD of 0.32% for CH4, 1.93% for C2H6, 0.77% for CO2, 0.64% for H2S, and 0.72% for N2. The same correlation can be employed for fitting phase equilibrium data for other hydrates too. The tuning parameter, n, is to be used for fine adjustment to the phase equilibrium data. The findings of this study can help for a better understanding of phase equilibrium and cage occupancy behavior of different gas hydrates. The accuracy in phase equilibria is intimately related to industrial applications such as crude oil transportation, solid separation, and gas storage. To date, no single correlation is available in the literature that can accurately predict phase equilibria for multiple hydrate species. The novelty of the present work lies in both the accuracy and generalizability of the proposed correlation in predicting the phase equilibrium data. The genetic programming generalized correlation is convenient for performing quick equilibrium prediction for industrial applications.

Keywords

• Gas hydrate
• Thermodynamic modeling
• van der Waals–Platteeuw
• CH4
• Genetic programming
• Correlation