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Multicriteria modeling and tradeoff analysis for oil load dispatch and hauling operations at Noble energy

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Abstract

Noble Energy produces and sells tens of thousands of barrels of oil a day in the Wattenberg field in northeastern Colorado, one of the largest natural gas deposits in the United States. This paper describes a new mathematical model that was built and implemented to support the company’s business decisions regarding its current and future sales, dispatch, and transportation operations. The corresponding multicriteria optimization model is formulated and solved as a multi-period, multi-objective mixed-integer program that considers the maximization of revenue and sales, and the avoidance of temporary production shut-ins and sell-outs to guarantee long-term contractual obligations with its partnering well owners, haulers, and markets. A theoretical tradeoff analysis is presented to validate model decisions with current operational practice, and a small computational case study on an original data set demonstrates the use of this model to find efficient dispatch schedules and gain further insights into the tradeoffs between the different decision criteria.

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References

  • Barnhart C, Laporte G (eds) (2006) Transportation. In: Handbooks in operations research and management science, vol 14. Elsevier, Amsterdam

  • Ben-Tal A, El Ghaoui L, Nemirovski A (2009) Robust optimization. Princeton Series in Applied Mathematics. Princeton University Press, Princeton

    Google Scholar 

  • Bertsimas D, Brown D, Caramanis C (2011) Theory and applications of robust optimization. SIAM Rev 53:464–501

    Article  MATH  MathSciNet  Google Scholar 

  • Birge JR, Louveaux F (1997) Introduction to stochastic programming. Springer Series in Operations Research. Springer, New York

    Google Scholar 

  • Bixby RE, Lee EK (1998) Solving a truck dispatching scheduling problem using branch-and-cut. Oper Res 46(3):355–367

    Article  MATH  Google Scholar 

  • Blouin S, Guay M, Rudie K (2007) An application of discrete-event theory to truck dispatching. Cent Eur J Oper Res 15:369–391

    Article  MATH  MathSciNet  Google Scholar 

  • Butler BRR (1988) Applications of OR in the oil industry. Math Program 42(1, (Ser. B)):99–112

  • Cafaro VG, Cafaro DC, Mendez CA, Cerda J (2010) Oil-derivatives pipeline logistics using discrete-event simulation. In: Johansson B, Jain S, Montoya-Torres J, Hugan J, Yucesan E (eds) Proceedings of the 2010 winter simulation conference, pp 2101–2113

  • Cao C, Gu X, Xin Z (2010) Stochastic chance constrained mixed-integer nonlinear programming models and the solution approaches for refinery short-term crude oil scheduling problem. Appl Math Model 34:3231–3243

    Article  MATH  MathSciNet  Google Scholar 

  • Cheng L, Duran MA (2004) Logistics for world-wide crude oil transportation using discrete event simulation and optimal control. Comput Chem Eng 28(6–7):897–911

    Article  Google Scholar 

  • Coelho LC, Cordeau J-F, Laporte G (2014) Thirty years of inventory routing. Transp Sci 48(1):1–19

    Article  Google Scholar 

  • Current J (1993) Multiobjective transportation network design and routing problems: taxonomy and annotation. Eur J Oper Res 65(1):4–19

    Article  MATH  Google Scholar 

  • Current J, Min HK (1986) Multiobjective design of transportation networks: taxonomy and annotation. Eur J Oper Res 26(2):187–201

    Article  MathSciNet  Google Scholar 

  • de Kok AG, Graves SC (eds) (2003) Supply chain management: design, coordination and operation. In: Handbooks in operations research and management science, vol 11. Elsevier, Amsterdam

  • De La Cruz JM, De Andres-Toro B, Herran A, Porta EB, Blanco PF (2003) Multiobjective optimization of the transport in oil pipelines networks. In: Proceedings of the 2003 IEEE conference on emerging technologies and factory automation, ETFA ’03, vol 1, pp 566–573

  • Dempster MAH, Pedron NH, Medova EA, Scott JE, Sembos A (2000) Planning logistics operations in the oil industry. J Oper Res Soc 51(11):1271–1288

    Article  MATH  Google Scholar 

  • Ehrgott M, Gandibleux X (eds) (2002) Multiple criteria optimization: state of the art annotated bibliographic surveys. International Series in Operations Research & Management Science, vol 52. Kluwer Academic Publishers, Boston

  • Engau A (2009) Tradeoff-based decomposition and decision-making in multiobjective programming. Eur J Oper Res 199(3):883–891

    Article  MATH  MathSciNet  Google Scholar 

  • Engau A (ed) (2012) Wattenberg oil load dispatch and hauling operations. Final Report of the Spring 2012 Mathematics Clinic sponsored by Noble Energy, Department of Mathematical and Statistical Sciences, University of Colorado Denver

  • Engau A, Wiecek MM (2007) 2D decision-making for multicriteria design optimization. Struct Multidiscip Optim 34(4):301–315

    Article  MATH  MathSciNet  Google Scholar 

  • Figueira JR, Greco S, Ehrgott M (eds) (2005) Multiple criteria decision analysis—state of the art surveys. International Series in Operations Research & Management Science, vol 78. Springer, New York

  • Garvin W, Crandall H, John J, Spellman R (1957) Applications of linear programming in the oil industry. Manag Sci 3(4):407–430

    Article  MATH  MathSciNet  Google Scholar 

  • Graves SC, Rinnooy Kan AHG, Zipkin PH (eds) (1993) Logistics of production and inventory. Handbooks in operations research and management science, vol 4 . Elsevier, Amsterdam

  • Infanger G (ed) (2011) Stochastic programming. International Series in Operations Research & Management Science, vol 150. Springer, New York

  • Kleywegt AJ, Nori VS, Savelsbergh MWP (2002) The stochastic inventory routing problem with direct deliveries. Transp Sci 36(1):94–118

    Article  MATH  Google Scholar 

  • Klingman D, Phillips N, Steiger D, Wirth R, Padman R, Krishnan R (1987) An optimization based integrated short-term refined petroleum product planning system. Manag Sci 33(7):813–830

    Article  Google Scholar 

  • Leiras A, Hamacher S, Elkamel A (2010) Petroleum refinery operational planning using robust optimization. Eng Optim 42(12):1–13

    Article  MathSciNet  Google Scholar 

  • Lukac Z, Hunjet D, Neralic L (2008) Solving the production–transportation problem in the petroleum industry. Revista Investigacíon Operacional 29(1):63–70

    MATH  MathSciNet  Google Scholar 

  • Matuszczak RA (1973) Wattenberg Field, Denver Basin, Colorado. Mt Geol 10(3):99–107

    Google Scholar 

  • MirHassani SA (2008) An operational planning model for petroleum products logistics under uncertainty. Appl Math Comput 196(2):744–751

    Article  MATH  MathSciNet  Google Scholar 

  • MirHassani SA, Noori R (2011) Implications of capacity expansion under uncertainty in oil industry. J Pet Sci Eng 77(2):194–199

    Article  Google Scholar 

  • Neiro SMS, Pinto JM (2004) A general modeling framework for the operational planning of petroleum supply chains. Comput Chem Eng 28:871–896

    Article  Google Scholar 

  • Neiro SMS, Pinto JM (2005) Multiperiod optimization for production planning of petroleum refineries. Chem Eng Commun 192(1):62–88

    Article  Google Scholar 

  • Rocha R, Grossmann IE, de Aragao MP (2009) Petroleum allocation at PETROBRAS: mathematical model and a solution algorithm. Comput Chem Eng 33(12):2123–2133

    Article  Google Scholar 

  • Ronen D (1995) Dispatching petroleum products. Oper Res 43(3):379–387

    Article  MATH  Google Scholar 

  • Shen Q, Chu F, Chen H (2011) A Lagrangian relaxation approach for a multi-mode inventory routing problem with transshipment in crude oil transportation. Comput Chem Eng 35(10):2113–2123

    Article  Google Scholar 

  • Ta CH, Ingolffson A, Doucette J (2010) Haul truck allocation via queueing theory. Technical Report. Department of Mechanical Engineering, University of Alberta

  • Tahar RM, Abduljabbar WK (2010) A novel transporting system model for oil refinery. Am J Eng Appl Sci 2(1):138–143

    Article  Google Scholar 

  • Van Roy TJ (1989) Multi-level production and distribution planning with transportation fleet optimization. Manag Sci 35(12):1443–1453

    Article  Google Scholar 

  • Zhong Z, You F (2011) Oil spill response planning with consideration of physicochemical evolution of the oil slick: a multiobjective optimization approach. Comput Chem Eng 35(8):1614–1630

    Article  Google Scholar 

Download references

Acknowledgment

The sponsorship by Noble Energy of the Spring 2012 Mathematics Clinic "Wattenberg Oil Load Dispatch and Hauling Optimization" in the Department of Mathematical and Statistical Sciences at the University of Colorado Denver and the participation of several other students is gratefully acknowledged.

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Authors and Affiliations

  1. Department of Mathematical and Statistical Sciences, University of Colorado Denver, 1201 Larimer Street, Suite 400, Denver, CO, 80204, USA

    Alexander Engau & Casey Moffatt

  2. Research and Development, Production Analysis and Optimization Group, Noble Energy, Inc., 1625 Broadway, Suite 2200, Denver, CO, 80202, USA

    Wesley Dyk

Authors
  1. Alexander Engau
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  2. Casey Moffatt
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  3. Wesley Dyk
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Corresponding author

Correspondence to Alexander Engau.

Additional information

This paper is based on parts of the Spring 2012 Mathematics Clinic “Wattenberg Oil Load Dispatch and Hauling Optimization” conducted in partnership between Noble Energy and the Department of Mathematical and Statistical Sciences at the University of Colorado Denver.

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Engau, A., Moffatt, C. & Dyk, W. Multicriteria modeling and tradeoff analysis for oil load dispatch and hauling operations at Noble energy. Optim Eng 16, 73–101 (2015). https://doi.org/10.1007/s11081-014-9259-5

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  • DOI: https://doi.org/10.1007/s11081-014-9259-5

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