Determination of Gas and Water Volume Fraction in Oil Water Gas Pipe Flow Using Neural Networks Based on Dual Modality Densitometry

  • Chunguo Jing
  • Guangzhong Xing
  • Bin Liu
  • Qiuguo Bai
Conference paper

DOI: 10.1007/11760191_182

Volume 3973 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Jing C., Xing G., Liu B., Bai Q. (2006) Determination of Gas and Water Volume Fraction in Oil Water Gas Pipe Flow Using Neural Networks Based on Dual Modality Densitometry. In: Wang J., Yi Z., Zurada J.M., Lu BL., Yin H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg

Abstract

The models of dual modality densitometry were developed. It can be used for measuring the gas volume fraction and water volume fraction in oil water gas pipe flow. The models are complex. In order to solve models, it often uses simplified models. This reduces measurement precision. The method of measuring gas and water volume fraction using neural networks was presented. The simulation data was gotten using Geant4. The radial basis function networks were trained and tested on computer simulation data. The results show that networks predicted gas volume fraction fit true gas fraction well and water volume fraction has some deviations.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Chunguo Jing
    • 1
    • 2
  • Guangzhong Xing
    • 1
  • Bin Liu
    • 1
  • Qiuguo Bai
    • 2
  1. 1.Yanshan UniversityQinhuangdaoChina
  2. 2.Northeastern University at QinhuangdaoQinhuangdaoChina