Developing a robust correlation for prediction of sweet and sour gas hydrate formation temperature  

作　　者：Mohammad Mesbah Samaneh Habibnia Shahin Ahmadi Amir Hossein Saeedi Dehaghani Sareh Bayat 

机构地区：[1]Young Researchers and Elites Club,Science and Research Branch,Islamic Azad University,Tehran,Iran [2]Department of Chemical Engineering,Sahand University of Technology,Tabriz,Iran [3]Department of Environmental Health Engineering,Faculty of Environment Health Engineering,Zabol University of Medical Sciences,Zabol,Iran [4]Department of Petroleum Engineering,Faculty of Chemical Engineering,Tarbiat Modares University,Tehran,Iran [5]Department of Environmental Health Engineering,School of Public Health,Hamedan University of Medical Sciences,Hamedan,Iran

出　　处：《Petroleum》2022年第2期204-209,共6页油气（英文）

摘　　要：There are numerous correlations and thermodynamic models for predicting the natural gas hydrate formation condition but still the lack of a simple and unifying general model that addresses a broad ranges of gas mixture.This study was aimed to develop a user-friendly universal correlation based on hybrid group method of data handling(GMDH)for prediction of hydrate formation temperature of a wide range of natural gas mixtures including sweet and sour gas.To establish the hybrid GMDH,the total experimental data of 343 were obtained from open articles.The selection of input variables was based on the hydrate structure formed by each gas species.The modeling resulted in a strong algorithm since the squared correlation coefficient(R2)and root mean square error(RMSE)were 0.9721 and 1.2152,respectively.In comparison to some conventional correlation,this model represented not only the outstanding statistical parameters but also its absolute superiority over others.In particular,the result was encouraging for sour gases concentrated at H2S to the extent that the model outstrips all available thermodynamic models and correlations.Leverage statistical approach was applied on datasets to the discovery of the defected and doubtful experimental data and suitability of the model.According to this algorithm,approximately all the data points were in the proper range of the model and the proposed hybrid GMDH model was statistically reliable.

关 键 词：Hydrate formation temperature HFT Wide range of natural gas mixtures Unified correlation Group method of data handling GMDH Outlier detection 

分 类 号：TE311[石油与天然气工程—油气田开发工程]