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Offshore oilfield development planning under uncertainty and fiscal considerations

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Abstract

The development planning of an offshore oil and gas field infrastructure involves critical investment and operating decisions at an early stage of the project that impact the overall project profitability. These strategic/tactical decisions need to be made considering sufficient reservoir details, fiscal contracts with the government and uncertainty in the field parameters to be useful in practice. However, it makes the optimization problem difficult to model and solve. With this motivation, the objective of this paper is to present a comprehensive review of a unified modeling framework and solution strategies to address the issues of complex fiscal rules and endogenous uncertainties in the development planning of offshore oil and gas field infrastructure that relies on our recent work in this area. In particular, the paper emphasizes the need to have as a basis an efficient deterministic model that can account for various alternatives in the decision making process for a multi-field site incorporating sufficient level of details, while being computationally tractable for large instances. Consequently, such a model can be effectively extended to include other complexities, for instance a production sharing agreement and endogenous uncertainties. Computational results on the deterministic as well as multistage stochastic instances of the problem are discussed.

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References

  • Babusiaux D, Favennec JP, Bauquis PR, Bret-Rouzaut N, Guirauden D (2007) Oil and Gas exploration and production: reserves, costs, contracts. Technip edition, chap. 4

  • BP Statistical Review of World Energy (2011)

  • Caroe CC, Schultz R (1999) Dual decomposition in stochastic integer programming. Oper Res Lett 24:37–45

    Article  MathSciNet  MATH  Google Scholar 

  • Fisher ML (1985) An applications oriented guide to lagrangian relaxation. Interfaces 15:10–21

    Article  Google Scholar 

  • Goel V, Grossmann IE (2004) A stochastic programming approach to planning of offshore gas field developments under uncertainty in reserves. Comput Chem Eng 28(8):1409–1429

    Article  Google Scholar 

  • Goel V, Grossmann IE (2006) A class of stochastic programs with decision dependent uncertainty. Math Progr Ser B 108(2–3):355–394

  • Gupta V (2013) Modeling and computational strategies for optimal oilfield development planning under fiscal rules and endogenous uncertainties, PhD thesis, Carnegie Mellon University, Pittsburgh

  • Gupta V, Grossmann IE (2011) Solution strategies for multistage stochastic programming with endogenous uncertainties. Comput Chem Eng 35:2235–2247

    Article  Google Scholar 

  • 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):6823–6840

    Article  Google Scholar 

  • Gupta V, Grossmann IE (2012b) Modeling and computational strategies for offshore oilfield development planning under complex fiscal rules. Ind Eng Chem Res 51:14438–14460

    Article  Google Scholar 

  • Gupta V, Grossmann IE (2014a) Multistage stochastic programming approach for offshore oilfield infrastructure planning under production sharing agreements and endogenous uncertainties. J Petrol Sci Eng 124:180–197

    Article  Google Scholar 

  • Gupta V, Grossmann IE (2014b) A new decomposition algorithm for multistage stochastic programs with endogenous uncertainties. Comput Chem Eng 62:62–79

    Article  Google Scholar 

  • Johnston D (1994) Petroleum fiscal systems and production sharing contracts. PennWell Publishing Co., Tulsa

    Google Scholar 

  • Jonsbraten TW, Wets RJB, Woodruff DL (1998) A class of stochastic programs with decision dependent random elements. Ann Oper Res 82:83–106

    Article  MathSciNet  MATH  Google Scholar 

  • Mouret S, Grossmann IE, Pestiaux P (2011) A new Lagrangian decomposition approach applied to the integration of refinery planning and crude-oil scheduling. Comput Chem Eng 35:2750–2766

    Article  Google Scholar 

  • Oliveira F, Gupta V, Hamacher S, Grossmann IE (2013) A Lagrangean decomposition approach for oil supply chain investment planning under uncertainty with risk considerations. Comput Chem Eng 50:184–195

    Article  Google Scholar 

  • Ruszczynski A (1997) Decomposition methods in stochastic programming. Math Progr Ser B 79:333–353

    MathSciNet  MATH  Google Scholar 

  • Sunley EM, Baunsgaard T, Simard D (2002) Revenue from the oil and gas sector: issues and country experience. IMF conference paper

  • Tarhan B, Grossmann IE (2008) A multistage stochastic programming approach with strategies for uncertainty reduction in the synthesis of process networks with uncertain yields. Comput Chem Eng 32:766–788

    Article  Google Scholar 

  • 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(6):3078–3097

    Article  Google Scholar 

  • Tarhan B, Grossmann IE, Goel V (2011) Computational strategies for non-convex multistage MINLP models with decision-dependent uncertainty and gradual uncertainty resolution. Ann Oper Res. doi:10.1007/s10479-011-0855-x

    MATH  Google Scholar 

  • Tarhan B, Gupta V, Grossmann IE (2013) Improving dual bound for stochastic MILP models using sensitivity analysis, manuscript in preparation

  • Tordo S (2007) Fiscal systems of hydrocarbons: design issues. Working paper 123/07, World Bank, Washington, D.C.

  • World Bank (2007) Contracts for petroleum development—Part 1–3. Petroleum Sector Briefing Note No. 7

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Acknowledgments

The author would like to acknowledge Center for Advanced Process Decision-making, Carnegie Mellon University, Pittsburgh for the financial support of this work.

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Authors and Affiliations

  1. Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    Vijay Gupta & Ignacio E. Grossmann

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  1. Vijay Gupta
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  2. Ignacio E. Grossmann
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Correspondence to Ignacio E. Grossmann.

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Gupta, V., Grossmann, I.E. Offshore oilfield development planning under uncertainty and fiscal considerations. Optim Eng 18, 3–33 (2017). https://doi.org/10.1007/s11081-016-9331-4

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  • DOI: https://doi.org/10.1007/s11081-016-9331-4

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