Article Sidebar

Download
PDF
Statistic
Read Counter : 2020 Download : 541

Downloads

Download data is not yet available.

Main Article Content

Abstract

This paper initially reviews existing empirical models which predict head or pressure increase of two-phase petroleum fluids in electrical submersible pumps (ESPs), then, proposes an alternative model, a fully connected cascade (FCC in short) artificial neural network to serve the same purpose. Empirical models of ESP are extensively in use; while analytical models are yet to be vastly employed in practice due to their complexity, reliance on over-simplified assumptions or lack of accuracy. The proposed FCC is trained and cross-validated with the same data used in developing a number of empirical models; however, the developed model presents higher accuracy than the aforementioned empirical models. The mean of absolute prediction error of the FCC for the experimental data not used in its training, is 68% less than the most accurate existing empirical model.

Keywords

Electrical submersible pumps Empirical models Cascade artificial neural networks Multiphase petroleum fluid.

Article Details

How to Cite
Mohammadzaheri, M., Tafreshi, R., Khan, Z., Ziaiefar, H., Ghodsi, M., Franchek, M., & Grigoriadis, K. (2019). MODELLING OF ELECTRICAL SUBMERSIBLE PUMPS FOR PETROLEUM MULTIPHASE FLUIDS, AN INTELLIGENT APPROACH SUPPORTED BY A CRITICAL REVIEW AND EXPERIMENTAL RESULTS. The Journal of Engineering Research [TJER], 16(2), 77–86. https://doi.org/10.24200/tjer.vol16iss2pp77-86
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX

References

  1. Barrios L. Prado M.G.(2011), Modeling two- phase flow inside an electrical submersible pump stage. Journal of Energy Resources Technology, 133(4): 1-10.
  2. Cirilo, R. (1998), Air-water flow through electric submersible pumps, a Master dissertation at the Department of Petroleum Engineering, University of Tulsa, USA.
  3. Duran J. M. Prado M.G. (2003), ESP stages air-water two-phase performance-modeling and experiment-tal data. SPE Report, No. 87626.
  4. Estevam V. (2002), A phenomenological analysis about centrifugal pump in two-phase flow operation. A PhD thesis at Faculdade de Engenharia Mecânica, Universidade Estadual de Campinas, Brazil.
  5. Gambo J. Prado M.G. (2010), Visualization study of performance breakdown in two-phase performance of an electrical submersible pump, International Pump Users Symposium, Houston, USA.
  6. Hunter D.H. Yu, M.S. Pukish III, J. Kolbusz and B. M. Wilamowski (2012), Selection of proper neural network sizes and architectures - A comparative study. IEEE Transactions on Industrial Informatics, 8(2): 228-240.
  7. Kirvelis R. Davies D. (2003), Enthalpy balance model leads to more accurate modelling of heavy oil production with an electric submersible pump. Chemical Engineering Research and Design, 81(3): 342-351.
  8. Lea J. F. Bearden J. (1982), Effect of gaseous fluids on submersible pump performance. Journal of Petroleum Technology 34(12): 922-930.
  9. Machado, A. P. F. Resende C.Z. Cavalieri D.C. (2019), Estimation and prediction of motor load torque applied to electrical submersible pumps. Control Engineering Practice 84: 284-296.
  10. Mohammadzaheri M.A. AlQallaf Ghodsi M. Ziaiefar H. (2018), Development of a fuzzy model to estimate the head of gaseous petroleum fluids driven by electrical submersible pumps. Fuzzy Information and Engineering 10(1): 99-106.
  11. Mohammadzaheri M. Chen L. (2008), Intelligent modeling of MIMO nonlinear dynamic process plants for predictive control purposes. The 17th World Congress of The International Federation of Automatic Control, Seoul, Korea.
  12. Mohammadzaheri M. Chen L. (2010), Intelligent predictive control of model helicopters' yaw angle. Asian Journal of Control. 12(6): 1-13.
  13. Mohammadzaheri M. Chen L. A. Ghaffari and J. Willison (2009), A combination of linear and nonlinear activation functions in neural networks for modeling a de-superheater. Simulation Modelling Practice and Theory. 17(2): 398-407.
  14. Mohammadzaheri M. Mirsepahi A. Asef-afshar O. and Koohi H. (2007), Neuro-fuzzy modeling of superheating system of a steam power plant. Applied Mathematical Sciences. 1: 2091-2099.
  15. Mohammadzaheri M. Tafreshi R. Khan Z, Franchek M. and Grigoriadis K. (2015), Modeling of petroleum multiphase fluids in ESPs, an intelligent approach. Offshore Mediterranean Conference, Ravenna, Italy.
  16. Mohammadzaheri, M., R. Tafreshi, Z. Khan, M. Franchek and K. Grigoriadis (2016), An intelligent approach to optimize multiphase subsea oil fields lifted by electrical submersible pumps. Journal of Computational Science 15: 50-59.
  17. Moré J.J. (1978), The Levenberg-Marquardt algorithm: implementation and theory. Lecture Notes in Mathematics, vol. 630, Springer, Berlin, Heidelberg: 105-116.
  18. Nguyen D. Widrow B. (1990), Improving the learning speed of 2-layer neural networks by choosing initial values of the adaptive weights. International Joint Conference on Neural Networks. San Diego, USA, 17-21 June, 1990.
  19. Romero M (1999), An evaluation of an electrical submersible pumping system for high GOR wells, a Master dissertation at University of Tulsa, USA.
  20. Sachdeva R (1988), Two-phase flow through electric submersible pumps, a PhD thesis at University of Tulsa, USA.
  21. Sachdeva R. Doty D. and Schmidt Z. (1992), Performance of axial electric submersible pumps in a gassy well, SPE Rocky Mountain Regional Meeting. Casper, USA.
  22. Sun D. Prado M. (2005), Modeling gas-liquid head performance of electrical submersible pumps. Journal of Pressure Vessel Technology, 127(1): 31-38.
  23. Turpin J.L. Lea J.F. Bearden J.L. (1986), Gas-liquid flow through centrifugal pumps—correlation of data, The Third International Pump Symposium, College Station, Texas, USA.
  24. Wilamowski (2012), Selection of proper neural network sizes and architectures—a comparative study. IEEE Transactions on Industrial Informatics. 8(2): 228-240.
  25. Zhou D. Sachdeva R. (2010), Simple model of electric submersible pump in gassy well. Journal of Petroleum Science and Engineering. 70(3): 204-213.
  26. Zhu J. Zhang H.Q. (2016), Mechanistic modeling and numerical simulation of in-situ gas void fraction inside ESP impeller. Journal of Natural Gas Science and Engineering. 36: 144-154.
  27. Zhu J. Zhang H.Q. (2017), Numerical study on electrical-submersible-pump two-phase performance and bubble-size modeling. SPE Production & Operations. 32(3): 267-278.
  28. Zhu J. Zhu H, Wang Z.J. Zhang, R. Cuamatzi-Melendez, J. A. M. Farfan and H.Q. Zhang (2018), Surfactant effect on air/water flow in a multistage electrical submersible pump (ESP). Experimental Thermal and Fluid Science 98: 95-111.