Optimal Distribution of Lift Gas in Gas Lifted Oil Field Using MPC and Unscented Kalman Filter
In gas lifted oil fields, the lift gas should be distributed optimally among the wells which share gas from a common source to maximize total oil production. One of the objectives of the paper is to show that a linear MPC consisting of a control objective and an economic objective can be used both as an optimizer and a controller for gas lifted systems. The MPC is based on linearized model of the oil field developed from first principles modeling. Simulation results show that the total oil production is increased by 3.4%. Difficulties in accurately measuring the bottom hole pressure using sensors in harsh operating conditions can be resolved by using an Unscented Kalman Filter (UKF) for estimation. In oil fields where input disturbance (total supply of gas) is not measured, UKF can also be used for disturbance estimation. Increased total oil production due to optimization leads to increased profit.
[1] G. Takacs, Gas Lift Manual. Tulsa, Oklahoma City: Pennwell Corporation,
2005.
[2] H. Zhong, Y. Li, and Y. Liu, "An approach for optimization of gaslift
allocation to a group of wells and oil field," in 3rd International
Symposium of National Key Laboratory for Oil and Gas Reservoir
Exploitation, Chengu, China, 2004, pp. 1-11.
[3] V. D. Kosmidis, J. Perkins, and E. Pistikopoulos, "A mixed integer
optimization formulation for the well scheduling problem on petroleum
fields," Journal of Computers and Chemical Engineering, vol. 29, pp.
1523-1541, 2005.
[4] E. Camponogara and P. H. R. Nakashima, "Solving a gas-lift optimization
problem by dynamic programming," European Journal of
Operational Research, vol. 174, pp. 1220-1246, 2006.
[5] D. Saepudin, E. Soewono, K. Sidarto, A. Gunawan, S. Siregar, and
P. Sukarno, "An investigation on gas lift performance curve in an oil
producing well," International Journal of Mathematics and Mathematical
Science, vol. 2007, pp. 1-15, 2007.
[6] T. Ray and R. Sarker, "Genetic algorithm for solving a gas lift optimization
problem," Journal of Petroleum Science and Engineering, vol. 59,
pp. 84-96, 2007.
[7] P. Sukarno, S. Saepudin, E. Soewono, K. Sidarto, and A. Gunawan,
"Optimization of gas injection allocation in a dual gas lift well system,"
Journal of Energy Resources Technology, vol. 131, Issue 3, 2009.
[8] K. Rashid, "Optimal allocation procedure for gas-lifted optimization,"
Industrial and Engineering Chemistry Research, vol. 49, pp. 2286-2294,
2010.
[9] A. Plucenio, D. Pagano, E. Camponogara, A. Traple, and A. Teixeira,
"Gas-lift optimization and control with nonlinear mpc," vol. 7, no. 1.
Koc University Campus, Turkey: 7th IFAC International Symposium on
Advanced Control of Chemical Processes, Jul 12-15 2009.
[10] R. Sharma, K. Fjalestad, and B. Glemmestad, "Modeling and control
of gas lifted oil field with five oil wells." V¨aster˚as, Sweden: 52nd
International Conference of Scandinavian Simulation Society, SIMS
2011, Sep 29-30 2011, pp. 47-59, iSBN: 978-91-977493-7-4.
[11] ANSI/ISA.S75.01, Flow Equations for Sizing Control Valves, Standards
and Recommended Practices for Instrumentation and Control, 10th ed.,
1989.
[12] PVTsim, "Pvt simulation program developed for reservoir engineers,
flow assurance specialists, pvt lab engineers and process engineers
(online)," Available at: ¡http://www.pvtsim.com¿ (Accessed: 20 January
2011), 2008.
[13] K. E. Brown and H. D. Beggs, The technology of artificial lift methods,
Volume 1, Inflow Performance, Multiphase flow in pipes, The flowing
well. Tulsa, Oklahoma, ISBN: 0-87814-031-X: PennWell Publishing
Company, 1977.
[14] American.Petroleum.Institute, API gas lift manual, Book 6 of the Vocational
Training series, third edition ed. Washington DC 2005-4070,
USA: Exploration and Production Department, 1994.
[15] D. Simon, Optimal State Estimation: Kalman, Hinf and nonlinear approaches.
Hoboken, New Jersey: John Wiley & Sons, Inc., Publication,
2006, iSBN: 13 978-0-471-70858-2.
[16] D. D. Ruscio and B. Foss, "On model based predictive control." Corfu,
Greece: The 5th IFAC Symposium on Dynamics and Control of Process
Systems, June 8-10 1998.
[1] G. Takacs, Gas Lift Manual. Tulsa, Oklahoma City: Pennwell Corporation,
2005.
[2] H. Zhong, Y. Li, and Y. Liu, "An approach for optimization of gaslift
allocation to a group of wells and oil field," in 3rd International
Symposium of National Key Laboratory for Oil and Gas Reservoir
Exploitation, Chengu, China, 2004, pp. 1-11.
[3] V. D. Kosmidis, J. Perkins, and E. Pistikopoulos, "A mixed integer
optimization formulation for the well scheduling problem on petroleum
fields," Journal of Computers and Chemical Engineering, vol. 29, pp.
1523-1541, 2005.
[4] E. Camponogara and P. H. R. Nakashima, "Solving a gas-lift optimization
problem by dynamic programming," European Journal of
Operational Research, vol. 174, pp. 1220-1246, 2006.
[5] D. Saepudin, E. Soewono, K. Sidarto, A. Gunawan, S. Siregar, and
P. Sukarno, "An investigation on gas lift performance curve in an oil
producing well," International Journal of Mathematics and Mathematical
Science, vol. 2007, pp. 1-15, 2007.
[6] T. Ray and R. Sarker, "Genetic algorithm for solving a gas lift optimization
problem," Journal of Petroleum Science and Engineering, vol. 59,
pp. 84-96, 2007.
[7] P. Sukarno, S. Saepudin, E. Soewono, K. Sidarto, and A. Gunawan,
"Optimization of gas injection allocation in a dual gas lift well system,"
Journal of Energy Resources Technology, vol. 131, Issue 3, 2009.
[8] K. Rashid, "Optimal allocation procedure for gas-lifted optimization,"
Industrial and Engineering Chemistry Research, vol. 49, pp. 2286-2294,
2010.
[9] A. Plucenio, D. Pagano, E. Camponogara, A. Traple, and A. Teixeira,
"Gas-lift optimization and control with nonlinear mpc," vol. 7, no. 1.
Koc University Campus, Turkey: 7th IFAC International Symposium on
Advanced Control of Chemical Processes, Jul 12-15 2009.
[10] R. Sharma, K. Fjalestad, and B. Glemmestad, "Modeling and control
of gas lifted oil field with five oil wells." V¨aster˚as, Sweden: 52nd
International Conference of Scandinavian Simulation Society, SIMS
2011, Sep 29-30 2011, pp. 47-59, iSBN: 978-91-977493-7-4.
[11] ANSI/ISA.S75.01, Flow Equations for Sizing Control Valves, Standards
and Recommended Practices for Instrumentation and Control, 10th ed.,
1989.
[12] PVTsim, "Pvt simulation program developed for reservoir engineers,
flow assurance specialists, pvt lab engineers and process engineers
(online)," Available at: ¡http://www.pvtsim.com¿ (Accessed: 20 January
2011), 2008.
[13] K. E. Brown and H. D. Beggs, The technology of artificial lift methods,
Volume 1, Inflow Performance, Multiphase flow in pipes, The flowing
well. Tulsa, Oklahoma, ISBN: 0-87814-031-X: PennWell Publishing
Company, 1977.
[14] American.Petroleum.Institute, API gas lift manual, Book 6 of the Vocational
Training series, third edition ed. Washington DC 2005-4070,
USA: Exploration and Production Department, 1994.
[15] D. Simon, Optimal State Estimation: Kalman, Hinf and nonlinear approaches.
Hoboken, New Jersey: John Wiley & Sons, Inc., Publication,
2006, iSBN: 13 978-0-471-70858-2.
[16] D. D. Ruscio and B. Foss, "On model based predictive control." Corfu,
Greece: The 5th IFAC Symposium on Dynamics and Control of Process
Systems, June 8-10 1998.
@article{"International Journal of Information, Control and Computer Sciences:49208", author = "Roshan Sharma and Bjørn Glemmestad", title = "Optimal Distribution of Lift Gas in Gas Lifted Oil Field Using MPC and Unscented Kalman Filter", abstract = "In gas lifted oil fields, the lift gas should be distributed optimally among the wells which share gas from a common source to maximize total oil production. One of the objectives of the paper is to show that a linear MPC consisting of a control objective and an economic objective can be used both as an optimizer and a controller for gas lifted systems. The MPC is based on linearized model of the oil field developed from first principles modeling. Simulation results show that the total oil production is increased by 3.4%. Difficulties in accurately measuring the bottom hole pressure using sensors in harsh operating conditions can be resolved by using an Unscented Kalman Filter (UKF) for estimation. In oil fields where input disturbance (total supply of gas) is not measured, UKF can also be used for disturbance estimation. Increased total oil production due to optimization leads to increased profit.
", keywords = "gas lift, MPC, oil production, optimization, Unscented
Kalman filter.", volume = "6", number = "9", pages = "1081-12", }
