期刊
CHEMOSPHERE
卷 313, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chemosphere.2022.137550
关键词
Gas hydrate; Thermodynamic conditions; EOS; Phase behavior; Prediction modelling
Gas hydrate modelling is an important tool for predicting the thermodynamic conditions before the industrial-scale applications. This study proposes a more accurate prediction model compared to existing equations of state (EOS) for estimating the gas hydrate formation conditions. The performance of the proposed model is found to be better than the PR and SRK equations of state in most cases, highlighting the limitations of EOS and strengthening statistical modelling techniques for broader predictions of hydrate conditions.
Gas Hydrate modelling has gained huge attention in the past decade due to its increase in usage for various energy as well as environmental applications at an industrial scale. As the experimental approach is highly expensive and time-consuming, modelling is the best way to predict the conditions before the actual applications at industrial scales. The commercial software currently existing uses the equation of states (EOS) to predict the thermodynamic conditions of gas hydrates. But, in certain cases, the prediction by using EOS fails to predict the hydrate conditions accurately. Therefore, there arose a need for an accurate prediction model to estimate the hydrate formation conditions. So, in this work, an accurate prediction model has been proposed to predict the thermodynamic equilibrium conditions of the gas hydrate formation. The performance of prediction accuracy for the proposed model is compared with those of the SRK equation of state and Peng Robinson (PR) Equation of state. It was observed that in most of the cases the proposed model has predicted the thermodynamic conditions more accurately than the PR and SRK equation of state. This work helps in understanding the limitations of EOS for the prediction hydrate conditions. Also, the current work helps in strengthening the conventional statistical modelling technique to predict the hydrate conditions for a broader range.
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