Production,processing and transportation of natural gases can be significantly affected by clathrate hydrates.Knowing the gas analysis is crucial to predict the right conditions for hydrate formation.Nevertheless,Katz...Production,processing and transportation of natural gases can be significantly affected by clathrate hydrates.Knowing the gas analysis is crucial to predict the right conditions for hydrate formation.Nevertheless,Katz gas gravity method can be used for initial estimation of hydrate formation temperature （HFT） under the circumstances of indeterminate gas composition.So far several correlations have been proposed for gas gravity method,in which the most accurate and reliable one has belonged to Bahadori and Vuthaluru.The main objective of this study is to present a simple and yet accurate correlation for fast prediction of sweet natural gases HFT based on the fit to Katz gravity chart.By reviewing the error analysis results,one can discover that the new proposed correlation has the best estimation capability among the widely accepted existing correlations within the investigated range.展开更多
Hydrate formation in the oil and gas industries has been a serious problem for a long time. It may cause many difficulties for instance in gas pipelines blockages. In order to determine the hydrate forming condition, ...Hydrate formation in the oil and gas industries has been a serious problem for a long time. It may cause many difficulties for instance in gas pipelines blockages. In order to determine the hydrate forming condition, gas gravity method has been used. Several correlations have been proposed based on gas gravity method. Checking the accuracy of the applied correlations is important. In this paper, the leverage approach is used for this purpose. Leverage approach is a statistical method for detection outliers which identifies the applicability domain （AD） of hydrate data predicting correlations and the quality of the existing data. Moreover, the Williams plot is sketched, which is a graphical depiction for determination of the doubtful points. The obtained results showed the existing correlations are all statistically correct and valid to predict hydrate formation temperature, just one data point is out of the applicability domains, and none of the experimental data can be chosen as outliers.展开更多
文摘Production,processing and transportation of natural gases can be significantly affected by clathrate hydrates.Knowing the gas analysis is crucial to predict the right conditions for hydrate formation.Nevertheless,Katz gas gravity method can be used for initial estimation of hydrate formation temperature （HFT） under the circumstances of indeterminate gas composition.So far several correlations have been proposed for gas gravity method,in which the most accurate and reliable one has belonged to Bahadori and Vuthaluru.The main objective of this study is to present a simple and yet accurate correlation for fast prediction of sweet natural gases HFT based on the fit to Katz gravity chart.By reviewing the error analysis results,one can discover that the new proposed correlation has the best estimation capability among the widely accepted existing correlations within the investigated range.
文摘Hydrate formation in the oil and gas industries has been a serious problem for a long time. It may cause many difficulties for instance in gas pipelines blockages. In order to determine the hydrate forming condition, gas gravity method has been used. Several correlations have been proposed based on gas gravity method. Checking the accuracy of the applied correlations is important. In this paper, the leverage approach is used for this purpose. Leverage approach is a statistical method for detection outliers which identifies the applicability domain （AD） of hydrate data predicting correlations and the quality of the existing data. Moreover, the Williams plot is sketched, which is a graphical depiction for determination of the doubtful points. The obtained results showed the existing correlations are all statistically correct and valid to predict hydrate formation temperature, just one data point is out of the applicability domains, and none of the experimental data can be chosen as outliers.
