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논문검색

Modified Model of Pressure Gradient Prediction of Vertical Multiphase Flow Based on the Residual Model

초록

영어

Aiming at the problem of the large error between the pressure gradient of multiphase flow predicted by the model presented in literature [12] (denoted by Liao model) and the experimental pressure gradient, this paper firstly compares the error between the Liao model and the experimental data, and builds a correlation model (denoted by CM model) between error of the Liao model and gas liquid ratio according to the close relations between the two. And then combining the CM model and the Liao model, a new predicting method of pressure gradient which is denoted by LCM model is built, and the algorithm is given. Finally, this paper gives the numerical experiment results for ninety groups of experimental data. The numerical results show that the average relative error of LCM model is about 3.3% and the one of Liao model is about 38%. Based on the known data with 30% water content and with 90% water content, this paper uses LCM model to calculate the pressure gradient under the case of 60% water content and compares the LCM gradient with the experimental pressure gradient under the same condition. The average relative error of LCM model is 10.44%, but the one of Liao model is 41.54%. The results shows that the LCM model proposed in this paper improves the predicting precision of pressure gradient for multiphase flowing in a certain range.

목차

Abstract
 1. Introduction
 2. Results and Analysis of Liao Model Based on the Experimental Data
 3. Modified Model of Liao Error (CM model)
 4. Algorithm of LCM Model
 5. Numerical Results and Analysis of LCM Model
 6. Conclusion
 Acknowledgements
 References

저자정보

  • Dong Yong School of Information and Mathematics, Yangtze University, Jingzhou Hubei 434023, China
  • Liao Ruiquan Petroleum Engineering College, Yangtze University, Wuhan Hubei 430100, China; The Branch of Key Laboratory of CNPC for Oil and Gas Production, Yangtze University, Wuhan Hubei 430100, China; Key Laboratory of Exploration Technologies for Oil and Gas Resources, Yangtze University, Wuhan Hubei 430100, China
  • Li Mengxia School of Information and Mathematics, Yangtze University, Jingzhou Hubei 434023, China; Petroleum Engineering College, Yangtze University, Wuhan Hubei 430100, China; The Branch of Key Laboratory of CNPC for Oil and Gas Production, Yangtze University, Wuhan Hubei 430100, China; Key Laboratory of Exploration Technologies for Oil and Gas Resources, Yangtze University, Wuhan Hubei 430100, China
  • Luo Wei Petroleum Engineering College, Yangtze University, Wuhan Hubei 430100, China; The Branch of Key Laboratory of CNPC for Oil and Gas Production, Yangtze University, Wuhan Hubei 430100, China; Key Laboratory of Exploration Technologies for Oil and Gas Resources, Yangtze University, Wuhan Hubei 430100, China

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