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Optimization and Engineering
Erschienen in: Optimization and Engineering 4/2017

19.09.2017

Optimization methods for petroleum fields development and production systems: a review

verfasst von: Cheng Seong Khor, Ali Elkamel, Nilay Shah

Erschienen in: Optimization and Engineering | Ausgabe 4/2017

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Abstract

In this review, we survey the widespread use of numerical optimization or mathematical programming approaches to develop and produce petroleum fields for design and operations; lift gas and rate allocation; and reservoir development, planning, and management. Early applications adopted linear programming alongside heuristics. With continuous advancements in computing speed and algorithms, we have been able to formulate more complex and meaningful models including nonlinear programs and mixed-integer linear and nonlinear programs. Various formulations and solution strategies have been used including continuous and discrete optimization, stochastic programming to handle uncertainty, and metaheuristics such as genetic algorithms to increase solution quality while reducing computational load.
Vorheriger Artikel Difference of convex functions algorithms (DCA) for image restoration via a Markov random field model
Nächster Artikel Petroleum refinery optimization

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Literatur
AbdulKarim A, Al-Dhubaib TA, Elrafie E, Alamoudi MO (2010) Overview of Saudi Aramcoś intelligent field program. In: SPE intelligent energy conference and exhibition, Jaarbeurs, Utrecht, The Netherlands. SPE, 23–25 March
Al-Hussainy R, Humphreys N (1996) Reservoir management: principles and practices. J Pet Technol 48(12):1129–1135CrossRef
Aliyev E, Durlofsky LJ (2015) Multilevel field-development optimization using a sequence of upscaled models. Paper SPE 173198 MS presented at SPE reservoir simulation symposium in Houston, Texas, USA, 23–25 February
Aronofsky JS (1983) Optimization methods in oil and gas development. Available from the online database of SPE at http://​www.​spe.​org (unpublished)
Aronofsky JS (1988) Computer applications in oil production: a viewpoint. J Pet Technol 40:143–148CrossRef
Aronofsky JS, Williams AC (1962) A use of linear programming and mathematical models in underground oil production. Manag Sci 8:394–407CrossRef
Aseeri A, Gorman P, Bagajewicz MJ (2004) Financial risk management in offshore oil infrastructure planning and scheduling. Ind Eng Chem Res 43(12):3063–3072CrossRef
Attra HD, Wise WB, Black WM (1961) Application of optimizing techniques for studying field producing operations. J Pet Technol 13:82–86CrossRef
Barnes DA, Humphrey K, Muellenberg L (1990) A production optimization system for Western Prudhoe Bay Field, Alaska. Paper SPE 20653 presented at the 65th annual technical conference and exhibition of the society of petroleum engineers held in New Orleans, Louisiana, USA, 23–26 Sept
Barnes RJ, Kokossis A, Shang Z (2007) An integrated mathematical programming approach for the design and optimisation of offshore fields. Comput Chem Eng 31:612–629CrossRef
Beggs HD (1991) Production optimization. OGCI Publications, Tulsa
Belotti P, Kirches C, Leyffer S, Linderoth J, Luedtke J, Mahajan A (2013) Mixed-integer nonlinear optimization. Acta Numer 22:1–131MATHCrossRefMathSciNet
Bertsimas D, King A, Mazumder R (2014) Statistics and machine learning via a modern optimization lens. The 2014–2015 Philip McCord Morse Lecture, INFORMS Annual Meeting
Bittencourt AC, Horne RN (1997) Reservoir development and design optimization. Paper SPE 38895 presented at the SPE annual technical conference and exhibition in San Antonio, Texas, USA, 5–8 Oct
Bixby RE (2012) A brief history of linear and mixed-integer programming computation. Doc Math Extra Volume Optim Stories 107–121
Bixby R, Rothberg E (2007) Progress in computational mixed integer programming—a look back from the other side of the tipping point. Ann Oper Res 149(1):37–41MATHCrossRefMathSciNet
Bohannon JM (1970) A linear programming model for optimum development of multi-reservoir pipeline systems. J Pet Technol 22:1429–1436CrossRef
Bouzarkouna Z, Ding DY, Auger A (2011) Well placement optimization with the covariance matrix adaptation evolution strategy and meta-models. Comput Geosci 16(1):75–92CrossRef
Brill JP (1987) Multiphase flow in wells. J Pet Technol 39(1):15–21CrossRef
Brown KE, Lea JF (1985) Nodal systems analysis of oil and gas wells. SPE Paper Disting Author Ser 14714:1751–1763
Buitrago S, Rodriguez E, Espin D (1996) Global optimization techniques in gas allocation for continuous flow gas lift systems. Paper SPE 35616 presented at the gas technology conference in Calgary, Alberta, Canada, 28 April–1 May
Busby D, Sergienko E (2010) Combining probabilistic inversion and multi-objective optimization for production development under uncertainty. In: ECMOR European conference on the mathematics of oil recovery, 12th, Oxford, UK, 6–9 Sept 2010
Busby D, Da Veiga S, Touzani S (2014) A workflow for decision making under uncertainty. Comput Geosci 18(3–4):519–533CrossRefMathSciNet
Cafaro DC, Grossmann IE (2014) Strategic planning, design, and development of the shale gas supply chain network. AIChE J 60(6):2122–2142CrossRef
Camponogara E, Nakashima PHR (2006) Solving a gas-lift optimization problem by dynamic programming. Eur J Oper Res 174(2):1220–1246MATHCrossRef
Camponogara E, Conto AM (2009) Lift-gas allocation under precedence constraints: MILP formulation and computational analysis. IEEE Trans Autom Sci Eng 6(3):544–551CrossRef
Camponogara E, Nazari LF, Meneses CN (2012) A revised model for compressor design and scheduling in gas-lifted oil fields. IIE Trans 44(5):342–351CrossRef
Carroll JA III, Horne RN (1992) Multivariate optimization of production system. J Pet Technol 44:782–831CrossRef
Carvalho MCA, Pinto JM (2006a) A bilevel decomposition technique for the optimal planning of offshore platforms. Braz J Chem Eng 23(1):67–82CrossRef
Carvalho MCA, Pinto JM (2006b) An MILP model and solution technique for the planning of infrastructure in offshore oilfields. J Pet Sci Eng 51:97–110CrossRef
Chang Y, Bouzarkouna Z, Devegowda D (2015) Multi-objective optimization for rapid and robust optimal oilfield development under geological uncertainty. Comput Geosci 19(4):933–950CrossRef
Charnes A, Cooper WW (1961) Management Models and Industrial Applications of Linear Programming. Wiley, New York CityMATH
Cozad A, Sahinidis NV, Miller DC (2014) Learning surrogate models for simulation-based optimization. AIChE J 60(6):2211–2227CrossRef
Cullick AS, Heath D, Narayanan K, April J, Kelly J (2003) Optimizing multiple-field scheduling and production strategy with reduced risk. Paper SPE 84239 presented at the SPE annual technical conference and exhibition held in Denver, Colorado, USA, 5–8 Oct
Currie JC, Novotnak JF, Aasboee BT, Kennedy CJ (1997) Optimized reservoir management with mixed linear programming. SPE Comput Appl 9:103–106
Davidson JE, Beckner BL (2003) Integrated optimization for rate allocation in reservoir simulation. Paper SPE 79701 presented at the SPE reservoir simulation symposium held in Houston, Texas, USA, 3–5 February
Dawson RG, Fuller JD (1999) A mixed integer nonlinear program for oilfield production planning. INFOR 37(2):121–140
Dempster MAH, Hicks Pedron N, Medova EA, Scott JE, Sembos A (2000) Planning logistics operations in the oil industry. J Oper Res Soc 51(11):1271–1288MATHCrossRef
Devine MD, Lesso WG (1972) Models for the minimum cost development of offshore oil fields. Manag Sci 18(8):B378–B387CrossRef
Dias MAG (2004) Valuation of exploration and production assets: an overview of real options models. J Pet Sci Eng 44(1–2):93CrossRef
Dougherty EL (1972) Application of optimization methods to oilfield problems: proved, probable, possible. SPE paper 3978-MS presented at the fall meeting of the Society of Petroleum Engineers of the American Institute of Mining, Metallurgical, and Petroleum Engineers, Inc. held in San Antonio, Texas, USA, 8–11 Oct
Drouven MG, Grossmann IE (2016) Multi-period planning, design, and strategic models for long-term, quality-sensitive shale gas development. AIChE J 62(7):2296–2323CrossRef
Dunnett AJ, Adjiman CS, Shah N (2008) A spatially explicit whole-system model of the lignocellulosic bioethanol supply chain: an assessment of decentralised processing potential. Biotechnol Biofuels 1:13CrossRef
Dutta-Roy K, Kattapuram J (1997) A new approach to gas lift allocation optimization. Paper SPE 38333 presented at the SPE Western Regional Meeting, Long Beach, California
Eeg OS, Herring T (1997) Combining linear programming and reservoir simulation to optimize asset value. Paper SPE 37446 presented at the 1997 SPE production operations symposium held in Oklahoma City, Oklahoma, 9–11 March
Fang WY, Lo KK (1996) A generalized well-management scheme for reservoir simulation. SPE Reserv Eng 11:116–120CrossRef
Fathi Z, Ramirez WF (1984) Optimal injection policies for enhanced oil recovery. Part II: surfactant flooding. SPE J 24(3):333–341CrossRef
Forouzanfar F, Reynolds AC (2014) Joint optimization of number of wells, well locations and controls using a gradient-based algorithm. Chem Eng Res Des 92(7):1315–1328CrossRef
Fujii H, Horne RN (1995) Multivariate optimization of networked production systems. SPE Prod Facil 10:165–171CrossRef
Gao J, You F (2015a) Deciphering and handling uncertainty in shale gas supply chain design and optimization: novel modeling framework and computationally efficient solution algorithm. AIChE J 61(11):3739–3755. doi:10.​1002/​aic.​15032 CrossRef
Gao J, You F (2015b) Optimal design and operations of supply chain networks for water management in shale gas production: MILFP model and algorithms for the water-energy nexus. AIChE J 61:1184–1208. doi:10.​1002/​aic.​14705 CrossRef
Gao J, You F (2015c) Shale gas supply chain design and operations toward better economic and life cycle environmental performance: MINLP model and global optimization algorithm. ACS Sustain Chem Eng 3(7):1282–1291. doi:10.​1021/​acssuschemeng.​5b00122 CrossRef
Gao J, You F (2017) Economic and environmental life cycle optimization of noncooperative supply chains and product systems: modeling framework, mixed-integer bilevel fractional programming algorithm, and shale gas application. ACS Sustain Chem Eng 5:3362–3381CrossRef
Gao J, He C, You F (2017) Shale gas process and supply chain optimization. In: Kopanos GM, Liu P, Georgiadis MC (eds) Advances in energy systems engineering. Springer, Cham, pp 21–46CrossRef
Garcia-Diaz JC, Startzman R, Hogg GL (1996) A new methodology for minimizing investment in the development of offshore fields. SPE Prod Facil 11(1):22–29CrossRef
Goel V, Grossmann IE (2004) A stochastic programming approach to planning of offshore gas field developments under uncertainty in reserves. Comput Chem Eng 28:1409–1429CrossRef
Goel V, Grossmann IEA (2006) A class of stochastic programs with decision dependent uncertainty. Math Program 108(2–3):355 (Ser. B)MATHCrossRefMathSciNet
Goel V, Grossmann IE, El-Bakry AS, Mulkay EL (2006) A novel branch and bound algorithm for optimal development of gas fields under uncertainty in reserves. Comput Chem Eng 30:1076–1092CrossRef
Grimmett TT, Startzmann RA (1988) Optimization of offshore field development to minimize investment. SPE Drill Eng 403–413
Gupta V, Grossmann IE (2012a) An efficient multiperiod MINLP model for optimal planning of offshore oil and gas field infrastructure. Ind Eng Chem Res 51(19):6823–6840CrossRef
Gupta V, Grossmann IE (2012b) Modeling and computational strategies for optimal development planning of offshore oilfields under complex fiscal rules. Ind Eng Chem Res 51(44):14438–14460CrossRef
Gupta V, Grossmann IE (2014) Multistage stochastic programming approach for offshore oilfield infrastructure planning under production sharing agreements and endogenous uncertainties. J Pet Sci Eng 124:180–197CrossRef
Gupta V, Grossmann IE (2017) Offshore oilfield development planning under uncertainty and fiscal considerations. Optim Eng 18(1):3–33MATHCrossRef
Güyagüler B, Horne RN (2004) Uncertainty assessment of well placement optimization. SPE Reserv Eval Eng 7:24–32CrossRef
Güyagüler BR, Horne N, Rogers L, Rosenzweig JJ (2002) Optimization of well placement in a Gulf of Mexico waterflooding project. SPE Reserv Eval Eng 5:229–236CrossRef
Haugen KK (1996) A stochastic dynamic programming model for scheduling of offshore petroleum fields with resource uncertainty. Eur J Oper Res 88:88–100MATHCrossRef
Haugland D, Hallefjord A, Asheim H (1988) Models for petroleum field exploitation. Eur J Oper Res 37:58–72MATHCrossRef
Hepguler G, Barua S, Bard W (1997) Integration of a field surface and production network with a reservoir simulator. SPE Comput Appl 9:88–93
Horesh L, Conn AR, Jimenez EA, van Essen GM (2015) Reduced space dynamics-based geo-statistical prior sampling for uncertainty quantification of end goal decisions. In: Al-Baali M, Grandinetti L, Purnama A (eds) Numerical analysis and optimization: NAO-III, Muscat, Oman, January 2014. Springer, Cham
Hou J, Zhou K, Zhang X-S, Kang X-D, Xie H (2015) A review of closed-loop reservoir management. Pet Sci 12(1):114–128CrossRef
Humphries TD, Haynes RD (2015) Joint optimization of well placement and control for nonconventional well types. J Pet Sci Eng 126:242–253CrossRef
Huppler JD (1974) Scheduling gas field production for maximum profit. SPE J 14:279–294CrossRef
Ierapetritou MG, Floudas CA, Vasantharajan S, Cullick AS (1999) Optimal location of vertical wells: a decomposition approach. AIChE J 45(4):844–859CrossRef
Isebor OJ, Durlofsky LJ, Echeverra Ciaurri D (2014a) A derivative-free methodology with local and global search for the constrained joint optimization of well locations and controls. Comput Geosci 18(3–4):463–482CrossRef
Isebor OJ, Echeverra Ciaurri D, Durlofsky LJ (2014b) Generalized field development optimization using derivative-free procedures. Soc Pet Eng J 19:891–908
Iyer RR, Grossmann IE (1998) A bilevel decomposition algorithm for long-range planning of process networks. Ind Eng Chem Res 37:474–481CrossRef
Iyer RR, Grossmann IE, Vasantharajan S, Cullick AS (1998) Optimal planning and scheduling of offshore oil field infrastructure investment and operations. Ind Eng Chem Res 37:1380–1397CrossRef
Jonsbraten TW (1998) Oil-field optimization under price uncertainty. J Oper Res Soc 49(8):811–818CrossRef
Jonsbraten TW, Wets RJ, Woodruff DL (1998) A class of stochastic programs with decision dependent random elements. Ann Oper Res 82:83–106MATHCrossRefMathSciNet
Kanu EP, Mach J, Brown KE (1981) Economic approach to oil production and gas allocation in continuous gas lift. J Pet Technol 33:1887–1892CrossRef
Kang CA, Brandt AR, Durlofsky LJ, Jayaweera I (2016) Assessment of advanced solvent-based post-combustion CO\(_{2}\) capture processes using a bi-objective optimization technique. Appl Energy 179:1209–1219CrossRef
Khor CS, Elkamel A (2010) Superstructure optimization for oil refinery design. Pet Sci Technol 28(14):1457–1465CrossRef
Khor CS, Chachuat B, Shah N (2012) A superstructure optimization approach for water network synthesis with membrane separation-based regenerators. Comput Chem Eng 42(11):48–63CrossRef
Knudsen BR, Foss B (2013) Shut-in based production optimization of shale-gas systems. Comput Chem Eng 58:54–67CrossRef
Kosmidis VD, Perkins JD, Pistikopoulos EN (2004) Optimization of well oil rate allocations in petroleum fields. Ind Eng Chem Res 43:3513–3527CrossRef
Krogstad S, Lie K-A, Myner O, Nilsen HM, Raynaud X, Skaflestad B (2015) MRST-AD—an open-source framework for rapid prototyping and evaluation of reservoir simulation problems.. 2015 Reservoir Simulation Symposium, Houston, Texas, USA, 23–25 Feb. doi:10.​2118/​173317-MS
Landmark (2001) VIP-EXECUTIVE technical reference. Landmark Graphics Corporation, Houston, Texas, USA
Lang ZX, Horne RN (1983) Optimum production scheduling using reservoir simulators: a comparison of linear programming and dynamic programming techniques. Paper SPE 12159 presented at the 58th annual technical conference and exhibition in San Francisco, California, USA, 5–8 Oct
Lasdon L, Coffman PE Jr, MacDonald R, McFarland JW, Sepehrnoori K (1986) Optimal hydrocarbon reservoir production policies. Oper Res 23:40–54CrossRef
Lee AS, Aronofsky JS (1958) A linear programming model for scheduling crude oil production. J Pet Technol 10(7):51–54CrossRef
Le Ravalec M, Tillier E, Da Veiga S, Enchery G, Gervais V (2012) Advanced integrated workflows for incorporating both production and 4d seismic-related data into reservoir models. Oil Gas Sci Technol Rev IFP Energies Nouv 67(2):207–220CrossRef
Lie K-A (2016) An introduction to reservoir simulation using MATLAB: user guide for the Matlab Reservoir Simulation Toolbox (MRST). SINTEF ICT
Ligero EL, Xavier AM, Schiozer DJ (2005). Value of information during appraisal and development of petroleum fields. In: Proceedings of 18th international congress of mechanical engineering, Ouro Preto, MG-Brasil
Lin X, Floudas CA (2003) A novel continuous-time modeling and optimization framework for well platform planning problems. Optim Eng 4:65–95MATHCrossRefMathSciNet
Liu P, Pistikopoulos EN, Li Z (2010) Energy systems engineering: methodologies and applications. Front Energy Power Eng China 4(2):131–142CrossRef
Lira-Barragan LF, Ponce-Ortega JM, Guilln-Goslbez G, El-Halwagi MM (2016) Optimal water management under uncertainty for shale gas production. Ind Eng Chem Res 55(5):1322–1335CrossRef
Litvak ML, Clark AJ, Fairchild JW, Fossum MP, MacDonald CD, Wood ARO (1997) Integration of Prudhoe Bay surface pipeline network and full field reservoir models. Paper SPE 38885 presented at the 1997 SPE annual technical conference and exhibition held in San Antonio, Texas, USA, 5–8 Oct
Lo KK, Holden CW (1992) Use of well management schemes for rate forecasts. Paper SPE 24071 presented at the SPE Western Regional Meeting held in Bakersfield, California, 30 March–1 April
Lu Q, Fleming GC (2012) Gas lift optimization using proxy functions in reservoir simulation. SPE Reserv Eval Eng 15(1):11. doi:10.​2118/​140935-PA
Mattax CC (1990) Doherty series. In: Henry L (ed) Reservoir simulation, vol 17. SPE monograph. Society of Petroleum Engineers (SPE), Richardson
Mulvey JM, Rosenbaum DP, Shetty B (1997) Strategic financial risk management and operations research. Eur J Oper Res 97:1MATHCrossRef
McFarland JW, Lasdon L, Loose V (1984) Development planning and management of petroleum reservoirs using tank models and nonlinear programming. Oper Res 32(2):270–289CrossRef
Nagurney A, Li D (2016) Competing on supply chain quality. Springer Series in Supply Chain Management, vol. 2. Springer, Berlin
Nagurney A, Qiang Q, Nagurney LS (2010) Environmental impact assessment of transportation networks with degradable links in an era of climate change. Int J Sustain Transp 4:154–171CrossRef
Nishikiori N, Redner RA, Doty DR, Schmidt Z (1989) An improved method for gas lift allocation optimization. SPE paper 19711 presented at the 64th annual technical conference and exhibition of the SPE in San Antonio, Texas, USA, 8–11 Oct
Nygreen B, Christiansen M, Haugen K, Bjrkvoll T, Kristiansen O (1998) Modeling Norwegian petroleum production and transportation. Ann Oper Res 82:251–268MATHCrossRef
Onwunalu JE, Durlofsky LJ (2010) Application of a particle swarm optimization algorithm for determining optimum well location and type. Comput Geosci 14:183–198MATHCrossRef
Ozdogan U, Horne RN (2006) Optimization of well placement under time-dependent uncertainty. SPE Reserv Eval Eng 9:135–145CrossRef
Palke MR, Horne RN (1997) Nonlinear optimization of well production considering gas lift and phase behaviour. Paper SPE 37428 presented at the 1997 SPE production operations symposium held in Oklahoma City, Oklahoma, 9–11 March
Pan Y, Horne RN (1998) Improved methods for multivariate optimization of field development scheduling and well placement design. Paper SPE 49055 presented at the SPE annual technical conference and exhibition in New Orleans, Louisiana, USA, 27–30 Sept
Pascual-Gonzlez J, Jimnez-Esteller L, Guilln-Goslbez G, Siirola JJ, Grossmann IE (2016) Macro-economic multi-objective inputoutput model for minimizing CO\(_{2}\) emissions: application to the U.S. economy. AIChE J 62(10):3639–3656CrossRef
Queipo NV, Zerpa LE, Goicochea JV, Verde AJ, Pintos SA, Zambrano A (2003) A model for the integrated optimization of oil production systems. Eng Comput 19(23):130–141CrossRef
Ranyard JC (1988) A history of OR and computing. J Oper Res Soc 39(12):1073–1086CrossRef
Rardin RL, Uzsoy R (2001) Experimental evaluation of heuristic optimization algorithms: a tutorial. J Heuristics 7:261–304MATHCrossRef
Rassenfoss S (2016) Four answers to the question: What can I learn from analytics? J Pet Technol 68(10):30–35CrossRef
Redden JD, Sherman TAG, Blann JR (1974) Optimizing gas-lift systems. Paper SPE 5150 presented at the 49th annual fall meeting of the society of petroleum engineers of the American Institute of Mining, Metallurgical, and Petroleum Engineers, Inc. (AIME) held in Houston, Texas, USA, 6–9 Oct
Rockafellar RT, Wets RJ-B (1991) Scenarios and policy aggregation in optimisation under uncertainty. Math Oper Res 16:119–147MATHCrossRefMathSciNet
Rosenwald GW, Green DW (1974) A method for determining the optimum location of wells in a reservoir using mixed-integer programming. SPE J 14(1):44–54CrossRef
Rowan G, Warren JE (1967) A systems approach to reservoir engineering: optimum development planning. J Can Pet Technol 6:84–94CrossRef
Samsatli S, Samsatli NJ, Shah N (2015a) BVCM: a comprehensive and flexible toolkit for whole system biomass value chain analysis and optimisation mathematical formulation. Appl Energy 147:131–160CrossRef
Samsatli S, Staffell I, Samsatli NJ (2015b) Whole-system optimisation of integrated wind-electricity-hydrogen networks for decarbonising the domestic transport sector in Great Britain. Int J Hydrog Energy 41:1–29
Saputelli LA, Nikolaou M, Economides MJ (2005) Self-learning reservoir management. SPE Reserv Eval Eng 8:534–547MATHCrossRef
Saputelli L, Nikolaou M, Economides MJ (2006) Real-time reservoir management: a multi-scale adaptive optimization and control approach. Comput Geosci 10:61–96MATHCrossRefMathSciNet
Sarma P, Durlofsky LJ, Aziz K (2005) Efficient closed-loop production optimization under uncertainty. SPE Paper 94241. Presented at the SPE Europec/EAGE annual conference, Madrid, 3–16 June 2005
Sarma P, Chen WH, Durlofsky LJ, Aziz K (2006a) Production optimization with adjoint models under nonlinear control-state path inequality constraints. SPE Paper 99959. Presented at the SPE intelligent energy conference and exhibition, Amsterdam, 11–13 April
Sarma P, Durlofsky LJ, Aziz K, Chen WH (2006b) Efficient real-time reservoir management using adjoint-based optimal control and model updating. Comput Geosci 10(1):3–36MATHCrossRefMathSciNet
Sarma P, Durlofsky LJ, Aziz K (2008a) Kernel principal component analysis for an efficient, differentiable parameterization of multi-point geostatistics. Math Geo Sci 40:332MATH
Sarma P, Durlovsky LJ, Aziz K (2008b) Computational techniques for closed-loop reservoir modeling with application to a realistic reservoir. Pet Sci Technol 26(1011):1120–1140CrossRef
Schulze-Riegert R, Ghedan S (2007) Modern techniques for history-matching. In: 9th international forum on reservoir simulation, Abu Dhabi, UEA, 9--13 Dec
Scicon (1991) MGG User Guide Version 3.1. Milton Keynes, England
See BA, Horne RN (1983) Optimal reservoir production scheduling by using reservoir simulation. SPE J 23:717–726CrossRef
Shirangi MG, Durlofsky LJ (2015) Closed-loop field development optimization under uncertainty
Simulation Sciences (SimSci) (1999) Input Manual for NETOPT. Simulation Sciences Inc, Brea, California, USA
Stackel AW, Brown HM (1979) Predictive well management in reservoir simulation—a case study. SPE paper 7698 presented at the 8th symposium on reservoir simulation at Denver, Colorado, USA
Stoisits RF, Batesole EC, Champion JH, Park DH (1992) Application of nonlinear adaptive modeling for rigorous representation of production facilities in reservoir simulation. Paper SPE 24898 presented at the 67th annual technical conference and exhibition of the society of petroleum engineers held in Washington, DC, USA, 4–7 Oct
Stoisits RF, Scherer PW, Schmidt SE (1994) Gas optimization at the Kuparuk River field. Paper SPE 28467 presented at the 69th annual technical conference and exhibition of the society of petroleum engineers held in New Orleans, Louisiana, USA, 25–28 Sept
Stoisits RF, Crawford KD, MacAllister DJ, McCormack MD (1999) Production optimization at the Kuparuk River field utilizing neural networks and genetic algorithms. Paper SPE 52177 presented at the 1999 Mid-Continent Operations Symposium held in Oklahoma City, Oklahoma, USA, 28–31 March
Sullivan JA (1982) A computer model for planning the development of an offshore gas field. J Pet Technol 34:1555–1564CrossRef
Tarhan B, Grossmann IE, Goel V (2009) Stochastic programming approach for the planning of offshore oil or gas field infrastructure under decision-dependent uncertainty. Ind Eng Chem Res 48:3078–3097CrossRef
Tarhan B, Grossmann IE, Goel V (2013) Computational strategies for non-convex multistage MINLP models with decision dependent uncertainty. Ann Oper Res 203(1):141–166MATHCrossRefMathSciNet
Tavallali MS, Karimi IA (2016) Integrated oil-field management: from well placement and planning to production scheduling. Ind Eng Chem Res 55(4):978–994CrossRef
Tavallali MS, Karimi IA, Teo KM, Baxendale D, Ayatollahi S (2013) Optimal producer well placement and production planning in an oil reservoir. Comput Chem Eng 55:109–125CrossRef
Tavallali MS, Karimi IA, Halim A, Baxendale D, Teo KM (2014) Well placement, infrastructure design, facility allocation, and production planning in multireservoir oil fields with surface facility networks. Ind Eng Chem Res 53(27):11033–11049CrossRef
Tavallali MS, Karimi IA, Baxendale D (2016) Process systems engineering perspective on the planning and development of oil fields. AIChE J 62(8):2586–2604CrossRef
Ulstein NL, Nygreen B, Sagli JR (2007) Tactical planning of offshore petroleum production. Eur J Oper Res 176(1):550–564MATHCrossRef
van den Berg F, Perrons RK, Moore I, Schut G (2010) Business value from intelligent fields. In: SPE intelligent energy conference and exhibition, Jaarbeurs, Utrecht, The Netherlands. SPE, 23–25 March
van den Heever SA, Grossmann IE (2000) An iterative aggregation/disaggregation approach for the solution of a mixed-integer nonlinear oilfield infrastructure planning model. Ind Eng Chem Res 39:1955–1971CrossRef
van den Heever SA, Grossmann IE, Vasantharajan S, Edwards K (2000) Integrating complex economic objectives with the design and planning of offshore oilfield infrastructures. Comput Chem Eng 24:1049–1055CrossRef
van den Heever SA, Grossmann IE, Vasantharajan S, Edwards K (2001) A Lagrangean decomposition heuristic for the design and planning of offshore hydrocarbon field infrastructures with complex economic objectives. Ind Eng Chem Res 40(13):2857–2875CrossRef
Vafi K, Brandt A (2016) GHGfrack: an open-source model for estimating greenhouse gas emissions from combustion of fuel during drilling and hydraulic fracturing. Environ Sci Technol 50(14):7913–7920CrossRef
Varma VA, Reklaitis GV, Blau GE, Pekny JF (2007) Enterprise-wide modeling & optimization—an overview of emerging research challenges and opportunities. Comput Chem Eng 31(56):692–711CrossRef
Vasantharajan S, Al-Hussainy R, Heinemann RF (2006) Applying optimization technology in reservoir management. J Pet Technol 58:82–88CrossRef
Wallace DJ, van Spronsen E (1983) Reservoir simulation model with platform production/injection constraints for development planning of volatile oil reservoirs. SPE paper 12261 presented at the reservoir simulation symposium in San Francisco, California, USA, 15–18 Nov
Wang P, Litvak M (2004) Gas lift optimization for long-term reservoir simulations. SPE paper 90506 presented at the SPE annual technical conference and exhibition in Houston, Texas, USA, 26–29 Sept
Wang P, Litvak ML (2008) Gas lift optimization for long-term reservoir simulations. SPE Reserv Eval Eng 11(1):7. doi:10.​2118/​90506-PA
Wang P, Litvak M, Aziz K (2002a) Optimization of production from mature fields. Presented at the 17th world petroleum congress in Rio de Janeiro, Brazil, 15 Sept
Wang P, Litvak M, Aziz K (2002b). Optimization of production operations in petroleum fields. SPE Paper 77658 presented at the SPE annual technical conference and exhibition in San Antonio, Texas, 29 Sept–2 Oct
Wang H, Ciaurri DE, Durlofsky LJ (2011) Optimal well placement under uncertainty using a retrospective optimization framework. In: SPE reservoir simulation symposium
Weiss JL, Masino WH, Starley GP, Bolling JD (1990) Large scale facility expansion evaluations at the Kuparuk River Field. Paper SPE 20046 presented at the 60th California Regional Meeting Held in Ventura, California, USA, 4–6 April
Yang L, Grossmann IE, Mauter MS, Dilmore RM (2015) Investment optimization model for freshwater acquisition and wastewater handling in shale gas production. AIChE J 61:1770–1782. doi:10.​1002/​aic.​14804 CrossRef
Yeten B, Durlofsky LJ, Aziz K (2003) Optimization of nonconventional well type, location, and trajectory. SPE J 8:200–210CrossRef
Zabalza-Mezghani I, Manceau E, Feraille M, Jourdan A (2004) Uncertainty management: From geological scenarios to production scheme optimization. J Pet Sci Eng 44:11–25CrossRef
Zhang Q, Shah N, Wassick J, Helling R, Egerschot PV (2014) Sustainable supply chain optimisation: an industrial case study. Comput Ind Eng 74:68–83CrossRef
Metadaten
Titel
Optimization methods for petroleum fields development and production systems: a review
verfasst von
Cheng Seong Khor
Ali Elkamel
Nilay Shah
Publikationsdatum
19.09.2017
Verlag
Springer US
Erschienen in
Optimization and Engineering / Ausgabe 4/2017
Print ISSN: 1389-4420
Elektronische ISSN: 1573-2924
DOI
https://doi.org/10.1007/s11081-017-9365-2

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