Published 2019-02-02
Keywords
- fuzzy logic,
- kalman filter,
- linear quadratic regulator,
- oil production,
- progressive cavity pump
How to Cite
Abstract
Progressive Cavity Pumps (PCP) is an artificial fluid lift method widely used in oil wells of Colombia, Canada and Venezuela, where the pump is driven by a rod connected to the motor located at the surface. Efficiency in energy production is critical, and the current control techniques used are based on discrete changes, seeking for an operational point. This approach can be improved, and optimization techniques proposed are presented in this paper. Strategies of control based on continuous adjustments of motor speed and fuzzy logic together with a downhole pressure sensor are simulated for this nonlinear system. Utilization of Kalman filtering, for estimation of the fluid level in wells that are not instrumented, is proposed. Linear Quadratic Regulator (LQR) also is used to optimize production performance. Results show good performance compared with current techniques.
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References
J. Chen, H. Liu, F. Wang, G. Shi, G. Cao, y H. Wu, “Numerical prediction on volumetric efficiency of progressive cavity pump with fluid–solid interaction model, ” J. Pet. Sci. Eng., vol. 109, pp. 12-17, 2013. doi: 10.1016/j.petrol.2013.08.019
T. Ernst et al., "Back Spin Control in Progressive Cavity Pump for Oil Well," 2006 IEEE/PES Transmission & Distribution Conference and Exposition: Latin America, Caracas, 2006, pp. 1-7. doi: 10.1109/TDCLA.2006.311587
M. Lehman, “Progressing cavity pumps in oil and gas production,” World Pumps, vol. 2004, no. 457, pp. 20-22, 2004.
B. Nesbitt, Handbook of Pumps and Pumping. Pumping Manual International. Amsterdam: Elsevier Science, 2006.
Gasparri, A. A. Romero, y E. Ferrigno, “PCP Production Optimization in Real Time With Surface Controller,” SPE Artificial Lift Conference-Americas, 2013. doi: 10.2118/165057-MS
M. Wells and J.F. Lea, Gas Well Deliquification. Elsevier. 2008. doi: 10.1016/B978-0-7506-8280-0.X5001-X
K. A. Woolsey, “Improving Progressing Cavity Pump performance through automation and surveillance,” SPE Progressing Cavity Pumps Conference, 2010.
“Lufkin well manager - progressing cavity pump controller,” 2016 General Electric Company, 2013.
J. Eck y L. Fry, “Eck et al. - 1999 - Downhole monitoring the story so far,” Oilfield Review, vol. 3, no. 3, pp. 18-29, 1999.
M. Changela and A. Kumar, “Designing a controller for two tank interacting system,” International Journal of Science and Research, vol. 4, no. 5, pp. 589-593, 2015.
M. E. Dreier, W L. McKeown, and H. WScott, Fuzzy Logic and Neural Network Handbook. McGraw-Hill, Inc., 1996.
C-T Chen, Linear System Theory and Design. , New York, USA: Oxford University Press, 2013.
K. Chate, O. E. Prado and C. Rengifo, “Comparative Analysis between Fuzzy Logic Control, LQR Control with Kalman Filter and PID Control for a Two Wheeled Inverted Pendulum” en Advances in Automation and Robotics Research in Latin America, Springer, 2017, pp. 144-156.
T. Nguyen, H. Tu, E. Al-Safran and A. Saasen, “Simulation of single-phase liquid flow in progressing cavity pump,” J. Pet. Sci. Eng., vol. 147, pp. 617–623, 2016. doi: 10.1016/j.petrol.2016.09.037
H. B. Bradley, Petroleum Engineering Handbook. Texas, USA: Society of Petroleum Engineers, 1987.
H. Klee and R. Allen, Simulation of Dynamic Systems. CRC Press, 2012.