Feedback Controllers for the Simulation of Field Processes
- Baris Güyagüler (Chevron) | Andreas T. Papadopoulos (Schlumberger) | Jared A. Philpot (Schlumberger)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- February 2010
- Document Type
- Journal Paper
- 10 - 23
- 2010. Society of Petroleum Engineers
- 5.5 Reservoir Simulation, 2 Well Completion, 2.2.2 Perforating, 5.3.9 Steam Assisted Gravity Drainage, 2.3 Completion Monitoring Systems/Intelligent Wells, 5.5.8 History Matching, 5.2.1 Phase Behavior and PVT Measurements, 5.4.1 Waterflooding, 7.6.6 Artificial Intelligence, 2.5.2 Fracturing Materials (Fluids, Proppant), 5.5.1 Simulator Development, 4.3.4 Scale, 4.1.5 Processing Equipment, 5.4.6 Thermal Methods
- 0 in the last 30 days
- 797 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 5.00|
|SPE Non-Member Price:||USD 35.00|
Control systems with feedback controllers are useful in reservoir simulation because they enable the maintenance of desired operating conditions of a field. This, in turn, helps to establish the value of implementing automated mechanisms in the field, and also in determining long-term field operating strategies. A generic controller framework is constructed within a reservoir simulator that enables the usage of different kinds of controller algorithms for managing a variety of field processes. In this study, three field processes are considered. First, average pressure within a reservoir region is maintained by adjusting the voidage-replacement ratio between a group of injectors and producers. Second, control systems are used for the prevention of gas/water coning for single and multiple wells. Finally, the average temperature within a reservoir region is maintained at a critical value by controlling flow into the formation, so as to operate with the desired mobility of heavy oil. Traditional proportional, integral, derivative (PID) controllers, as well as linear and nonlinear fuzzy controllers, are considered. The advantages and disadvantages of the approaches are discussed. Tuning control systems is a difficult process in practice. Several methods for tuning the parameters of these controllers are investigated, and rule-of-thumb values are suggested in this study. Synthetic and real reservoir models are used.
|File Size||1 MB||Number of Pages||14|
Alhuthali, A., Oyerinde, D., and Datta-Gupta, A. 2007. Optimal Waterflood Management UsingRate Control. SPE Res Eval & Eng 10 (5): 539-551.SPE-102478-PA. doi: 10.2118/102478-PA.
Åström, K. and Hägglund, T. 1995. PID Controllers: Theory, Design, andTuning, second edition. Research Triangle Park, North Carolina, USA:ISA.
Bieker, H.P., Slupphaug O., and Johansen, T.A. 2007. Real-Time Production Optimization ofOil and Gas Production Systems: A Technology Survey. SPE Prod &Oper 22 (4): 382-391. SPE-99446-PA. doi: 10.2118/99446-PA.
ECLIPSE Technical Description 2008.1. 2008. Houston: SchlumbergerGeoQuest.
Güyagüler, B. and Byer, T. 2008. A New Rate-Allocation-OptimizationFramework. SPE Prod & Oper 23 (4): 448-457.SPE-105200-PA. doi: 10.2118/105200-PA.
Güyagüler, B. and Ghorayeb, K. 2006. Integrated Optimization of FieldDevelopment, Planning, and Operation. Paper SPE 102557 presented at the SPEAnnual Technical Conference and Exhibition, San Antonio, Texas, USA, 24-27September. doi: 10.2118/102557-MS.
Havre, K. and Dalsmo, M. 2001. Active Feedback Control as theSolution to Severe Slugging. Paper SPE 71540 presented at the SPE AnnualTechnical Conference and Exhibition, New Orleans, Louisiana, USA, 30September-3 October. doi: 10.2118/71540-MS.
Kovacic, Z. and Bogdan, S. 2006. Fuzzy Controller Design: Theory andApplications. Boca Raton, Florida, USA: Control Engineering Series, CRCPress/Taylor & Francis Group.
Leemhuis, A.P., Nennie, E.D., Belfroid, S.P.C., Alberts, G.J.N., Peters, E.,and Joosten, G.J.P. 2008. GasConing Control for Smart Wells Using a Dynamic Coupled Well-ReservoirSimulator. Paper 112234 presented at the Intelligent Energy Conference andExhibition, Amsterdam, 25-27 February. doi: 10.2118/112234-MS.
Mata, D., Hernandez, A., Chirinos, N., Montoya, D., and Strefezza, M. 2003.Gas Lift Trouble Shoot AnalysisUsing Fuzzy Logic. Paper SPE 81166 presented at the SPE Latin American andCaribbean Petroleum Engineering Conference, Port-of-Spain, Trinidad and Tobago,27-30 April. doi: 10.2118/81166-MS.
Nikolaou, M., Cullick, A.S., Saputelli, L., Mijares, G., Sankaran, S., andReis, L. 2006. A ConsistentApproach Toward Reservoir Simulation at Different Time Scales. Paper SPE99451 presented at the Intelligent Energy Conference and Exhibition, Amsterdam,11-13 April. doi: 10.2118/99451-MS.
Oberwinkler, C. and Stundner, M. 2005. From Real-Time Data to ProductionOptimization. SPE Prod & Fac 20 (3): 229-239.SPE-87008-PA. doi: 10.2118/87008-PA.
Rivera, V.P. 1994. Fuzzy LogicControls Pressure in Fracturing Fluid Characterization Facility. Paper SPE28239 presented at the Petroleum Computer Conference, Dallas, 31 July-3 August.doi: 10.2118/28239-MS.
Saputelli, L., Nikolaou, M., and Economides, M.J. 2005. Self-Learning ReservoirManagement. SPE Res Eval & Eng 8 (6): 534-547. SPE84064-PA. doi: 10.2118/84064-PA.
Sarma, P., Chen, W.H., Durlofsky, L.J., and Aziz, K. 2008. Production Optimization With AdjointModels Under Nonlinear Control-State Path Inequality Constraints. SPERes Eval & Eng 11 (2): 326-339. SPE-99959-PA. doi:10.2118/99959-PA.
Sengul, M. and Bekkousha, M.A. 2002. Applied Production Optimization:i-Field. Paper SPE 77608 presented at the SPE Annual Technical Conferenceand Exhibition, San Antonio, Texas, USA, 29 September-2 October. doi:10.2118/77608-MS.
Shokir, E.M. El-M. 2006. ANovel Model for Permeability Prediction in Uncored Wells. SPE Res Eval& Eng 9 (3): 266-273. SPE-87038-PA. doi:10.2118/87038-PA.
Stenhouse, B. 2006. Learningson Sustainable Model-Based Optimisation--The Valhall Optimiser Field Trial.Paper SPE 99828 presented at the Intelligent Energy Conference and Exhibition,Amsterdam, 11-13 April. doi: 10.2118/99828-MS.
van Dijk, F., Goh, K.C., and van Lienden, J.W. 2008. Closing the Loop for Improved Oiland Gas Production Management. Paper 111997 presented at the IntelligentEnergy Conference and Exhibition, Amsterdam, 25-27 February. doi:10.2118/111997-MS.
Wang, S., Mohan, R., Shoham, O., Marelli, J.D., and Kouba, G.E. 2000. Optimal Control Strategy andExperimental Investigation of Gas-Liquid Compact Separators. Paper SPE63120 presented at the SPE Annual Technical Conference and Exhibition, Dallas,1-4 October. doi: 10.2118/63120-MS.
Weiss, W., Xie, X., Weiss, J., Subramanium, V., Taylor, A., and Edens, F.2004. Artificial Intelligence Usedto Evaluate 23 Single-Well Surfactant Soak Treatments. SPE Res Eval& Eng 9 (3): 209-216. SPE-89457-PA. doi:10.2118/89457-PA.
Zarei, F., Daliri, A., and Alizadeh, N. 2008. The Use of Neuro-Fuzzy Proxy in WellPlacement Optimization. Paper SPE 112214 presented at the IntelligentEnergy Conference and Exhibition, Amsterdam, 25-27 February. doi:10.2118/112214-MS.