Gas Lift Optimization Using Proxy Functions in Reservoir Simulation
- Qin Lu (Halliburton) | Graham C. Fleming (Halliburton)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- February 2012
- Document Type
- Journal Paper
- 109 - 119
- 2012. Society of Petroleum Engineers
- 5.5 Reservoir Simulation, 4.2.4 Risers, 4.2 Pipelines, Flowlines and Risers, 3.1 Artificial Lift Systems, 3.1.6 Gas Lift, 5.4.2 Gas Injection Methods
- Proxy functions, Reservoir simulation, Gas-lift optimization, Surface pipeline network
- 7 in the last 30 days
- 1,158 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 10.00|
|SPE Non-Member Price:||USD 30.00|
Artificial lift by means of gas injection into production wells or risers is frequently used to increase hydrocarbon production, especially when reservoir pressure declines. We propose an efficient optimization scheme that finds the optimal distribution of the available gas lift gas to maximize an objective function subject to surface-pipeline-network rate and pressure constraints. This procedure is a nonlinearly constrained optimization problem solved by the generalized reduced-gradient (GRG) method. The values of objective function, constraint functions, and derivatives needed for optimization can be evaluated through two methods. The first method repeatedly solves the full-network equations using Newton iteration, which takes into account the flow interactions among wells; however, this method can be computationally expensive. The second and more efficient method is a new approach proposed in this paper. It constructs a set of proxy functions that approximates the objective function and constraints as functions of gas lift rates. The proxy functions are obtained by solving part of the network that consists of a gas lifted well or riser, assuming a stable pressure at the terminal node where the partial network is decoupled from the rest of the network, and are used to inexpensively evaluate the objective function, constraints, and necessary derivatives for the optimizer. A procedure to predict the proxy functions on the basis of previous values can be used to reduce the number of partial-network solves, and the partial-network solution has been parallelized for faster simulation. These two methods can be applied at different timesteps during the course of the simulation. The proposed methods are implemented within a general-purpose black-oil and compositional reservoir simulator and have been applied to real-field cases.
|File Size||1 MB||Number of Pages||11|
Coats, B.K., Fleming, G.C., Watts, J.W., Rame, M., and Shiralkar, G.S. 2003.A Generalized Wellbore and Surface Facility Model, Fully Coupled to a ReservoirSimulator. Paper SPE 79704 presented at the SPE Reservoir Simulation Symposium,Houston, 3-5 February. http://dx.doi.org/10.2118/79704-MS.
Dutta-Roy, K. and Kattapuram, J. 1997. A New Approach to Gas-Lift AllocationOptimization. Paper SPE 38333 presented at the SPE Western Regional Meeting,Long Beach, California, USA, 25-27 June. http://dx.doi.org/10.2118/38333-MS.
Fang, W.Y. and Lo, K.K. 1996. A Generalized Well-Management Scheme forReservoir Simulation. SPE Res Eng 11 (2): 116-120.SPE-29124-PA. http://dx.doi.org/10.2118/29124-PA.
Fletcher, R. 1987. Practical Methods of Optimization, second edition,317-322. New York: John Wiley & Sons.
Gutierrez, F.A., Hallquist, A.E., Shippen, M.E., and Rashid, K. 2007. A NewApproach to Gas Lift Optimization Using an Integrated Asset Model. Paper IPTC11594 presented at the International Petroleum Technology Conference, Dubai,4-6 December. http://dx.doi.org/10.2523/11594-MS.
Hepguler, G., Barua, S., and Bard, W. 1997. Integration of a Field Surfaceand Production Network With a Reservoir Simulator. SPE Comp App 9 (3): 88-92. SPE-38937-PA. http://dx.doi.org/10.2118/38937-PA.
Kanu, E.P., Mach, J., and Brown, K.E. 1981. Economic Approach to OilProduction and Gas Allocation in Continuous Gas Lift. J Pet Technol 33 (10): 1887-1892. SPE-9084-PA. http://dx.doi.org/10.2118/9084-PA.
Killough, J.E. 1995. Ninth SPE Comparative Solution Project: A Reexaminationof Black-Oil Simulation. Paper SPE 29110 presented at the SPE ReservoirSimulation Symposium, San Antonio, Texas, USA, 12-15 February. http://dx.doi.org/10.2118/29110-MS.
Lasdon, L.S. and Waren, A.D. 1997. GRG2 User's Guide. Technical document,University of Texas at Austin, Austin, Texas (2 October 1997).
Litvak, M.L. and Darlow, B.L. 1995. Surface Network and Well TubingheadPressure Constraints in Compositional Simulation. Paper SPE 29125 presented atthe SPE Reservoir Simulation Symposium, San Antonio, Texas, USA, 12-15February. http://dx.doi.org/10.2118/29125-MS.
Rashid, K. 2010. Optimal Allocation Procedure for Gas-Lift Optimization.Ind. Eng. Chem. Res. 49 (5): 2286-2294. http://dx.doi.org/10.1021/ie900867r.
Rashid, K., Demirel, S., and Coue¨t, B. 2011. Gas-Lift Optimization withChoke Control using a Mixed-Integer Nonlinear Formulation. Ind. Eng. Chem.Res. 50 (5): 2971-2980. http://dx.doi.org/10.1021/ie101205x.
Shiralkar, G.S. and Watts, J.W. 2005. An Efficient Formulation forSimultaneous Solution of the Surface Network Equations. Paper SPE 93073presented at the SPE Reservoir Simulation Symposium, The Woodlands, Texas, USA,31 January-2 Feburary. http://dx.doi.org/10.2118/93073-MS.
Stoisits, R.F., Crawford, K.D., MacAllister, D.J., McCormack, M.D., Lawal,A.S., and Ogbe, D.O. 1999. Production Optimization at the Kuparuk River FieldUtilizing Neural Networks and Genetic Algorithms. Paper SPE 52177 presented atthe SPE Mid-Continent Operations Symposium, Oklahoma City, Oklahoma, USA, 28-31March. http://dx.doi.org/10.2118/52177-MS.
Wang, P. and Litvak, M. 2008. Gas Lift Optimization for Long-Term ReservoirSimulations. SPE Res Eval & Eng 11 (1): 147-153.SPE-90506-PA. http://dx.doi.org/10.2118/90506-PA.
Watts, J.W., Fleming, G.C., and Lu, Q. 2009. Determination of ActiveConstraints in a Network. Paper SPE 118877 presented at the SPE ReservoirSimulation Symposium, The Woodlands, Texas, USA, 2-4 February. http://dx.doi.org/10.2118/118877-MS.