Hydrates always are considered as a threat to petroleum industry due to the operational problems it can cause.These problems could result in reducing production performance or even production stoppage for a long time....Hydrates always are considered as a threat to petroleum industry due to the operational problems it can cause.These problems could result in reducing production performance or even production stoppage for a long time.In this paper, we were intended to develop a LSSVM algorithm for prognosticating hydrate formation temperature(HFT) in a wide range of natural gas mixtures. A total number of 279 experimental data points were extracted from open literature to develop the LSSVM. The input parameters were chosen based on the hydrate structure that each gas species form. The modeling resulted in a robust algorithm with the squared correlation coefficients(R^2) of 0.9918. Aside from the excellent statistical parameters of the model, comparing proposed LSSVM with some of conventional correlations showed its supremacy, particularly in the case of sour gases with high H_2S concentrations, where the model surpasses all correlations and existing thermodynamic models. For detection of the probable doubtful experimental data, and applicability of the model, the Leverage statistical approach was performed on the data sets. This algorithm showed that the proposed LSSVM model is statistically valid for HFT prediction and almost all the data points are in the applicability domain of the model.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Hydrates always are considered as a threat to petroleum industry due to the operational problems it can cause.These problems could result in reducing production performance or even production stoppage for a long time.In this paper, we were intended to develop a LSSVM algorithm for prognosticating hydrate formation temperature(HFT) in a wide range of natural gas mixtures. A total number of 279 experimental data points were extracted from open literature to develop the LSSVM. The input parameters were chosen based on the hydrate structure that each gas species form. The modeling resulted in a robust algorithm with the squared correlation coefficients(R^2) of 0.9918. Aside from the excellent statistical parameters of the model, comparing proposed LSSVM with some of conventional correlations showed its supremacy, particularly in the case of sour gases with high H_2S concentrations, where the model surpasses all correlations and existing thermodynamic models. For detection of the probable doubtful experimental data, and applicability of the model, the Leverage statistical approach was performed on the data sets. This algorithm showed that the proposed LSSVM model is statistically valid for HFT prediction and almost all the data points are in the applicability domain of the model.
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.
