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Journal of Petrochemical Universities
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2017, Vol.30 No.5  Publication date:31 October 2017
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  • Analysis on the Movement Characteristics of Bypass  Pig and PigGenerated Slug Dissipation
  • Chen Jianheng, He Limin, Lyu Yuling, Li Xiaowei
  • 2017, 30 (5): 66-71. DOI:10.3969/j.issn.1006-396X.2017.05.013
  • Abstract ( ) PDF ( 4484KB ) ( )   
  • In order to analyze the movement rules of bypass pig and the characteristics of piggenerated slug dissipation, a dynamic bypass pigging simulation for a real deepwater gas field was conducted. The movement characteristics of pig velocity and the piggenerated slug dissipation were analyzed through changing the pressure drop coefficient and bypass fraction. The study shows that the pig velocity turns out to be powerlaw distribution with the change of pressure drop coefficients, and within the sensitive range, a small change of the pressure drop coefficient will lead to a huge fluctuation of the pig velocity. The average pig velocity has the tendency of linear reduction with the rise of bypass fraction, the change of which helps to control the pig velocity. By taking advantage of bypass gases to carry and sweep the liquid loading in front of the pig,the running resistance can be reduced, thus the stick phenomena of the pig at the bottom of the riser is avoided. The existence of bypass fraction makes the piggenerated slug dissipate along the pigging period. With the increase of the bypass fraction, the hold up of liquid in the slug is reduced, and the liquid film zone is prolonged, thus making the piggenerated slug volume decrease remarkably. For the optimization of the bypass fraction, an overall consideration should be given to the reasonable scope of pig velocity variations and the piggenerated slug volume, making sure it's within the processing capacity of a slug catcher.
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  • Prediction of Natural Gas Hydrate Formation Based on Support Vector Machine (SVM)CV
  • Gong Qingjun,Ma Guiyang,Pan Zhen,et al
  • 2017, 30 (5): 80-85. DOI:10.3969/j.issn.1006-396X.2017.05.015
  • Abstract ( ) PDF ( 2254KB ) ( )   
  • Natural gas hydrate has the advantages of abundant reserves, large calorific value and low emission, which can mitigate the environmental pollution problems caused by traditional fossil energy. The generation process of natural gas hydrate form is a system with multicomponents and multiphysical states. The nucleation process is complex, which needs to consider the effects of pressure, temperature, promoters, stirring speed and so on. It is difficult to accurately predict the hydrate formation, because the hydrate formation process not only involves thermodynamics problems but also dynamics problems. In our paper, the support vector machine theory combined with experimental data was used to establish support vector machine prediction model for predicting natural gas hydrate equilibrium pressure. The prediction accuracy was estimated by using the mean square error, the square correlation coefficient, the square absolute percentage error and the average absolute error. The results are 8.370 08×10-5,99.897 6%,0.542 4%,1.990 0%,respectively. The pretreatment origin data were normalized ([1,2]) and the nuclear parameter g(4)and punishment factor c(1.414 2) were optimized by using cross validation methods. Simulation results show that the equilibrium pressure obtained by support vector prediction model is good in agreement with the equilibrium obtained by experiments. The better ideal prediction effects prove that the model has advantages of accuracy and reliability. It can provide certain reference for research on natural gas hydrate in future.
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