Mature offshore oil field development: Solving a real options problem using stochastic dual dynamic integer programming

Oil and gas companies are facing low output prices and are forced to focus on the development of mature fields. Relevant investment decisions for operators include lifetime-enhancing activities, such as drilling new wells or permanent shutdown. We study the problem of optimal timing of investments i...

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Veröffentlicht in:Computers & operations research Jg. 136; S. 105480
Hauptverfasser: Bakker, Steffen J., Kleiven, Andreas, Fleten, Stein-Erik, Tomasgard, Asgeir
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Elsevier Ltd 01.12.2021
Pergamon Press Inc
Schlagworte:
Algorithms
Decommissioning
Expenditures
Integer programming
Mature oil field development
Multistage stochastic integer programming
Oil fields
Operations research
Real options
SDDiP
Shutdowns
Uncertainty
Upper bounds
Mature oil field development
Multistage stochastic integer programming
SDDiP
Real options
ISSN:0305-0548, 0305-0548
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Zusammenfassung:Oil and gas companies are facing low output prices and are forced to focus on the development of mature fields. Relevant investment decisions for operators include lifetime-enhancing activities, such as drilling new wells or permanent shutdown. We study the problem of optimal timing of investments in mature oil and gas fields in the presence of price uncertainty, which is an example of a complex real options problem consisting of a portfolio of interdependent options. We formulate a multistage stochastic integer programming model that incorporates a detailed representation of the uncertain oil price, and demonstrate how such a complex real options problem can be efficiently solved using the Stochastic Dual Dynamic Integer Programming algorithm. The paper presents a numerical example based on realistic data and discusses our computational results. We find that only a small number of Markov states are required to represent the uncertain price process, while obtaining convergence of the lower and upper bounds of the objective function. The value of stochastic solution of 11% is considerable in this example. It is concluded that the shutdown decision tends to be postponed as a result of high decommissioning costs, high discount rates, high price uncertainty and low operational expenditures, while it generally is accelerated if the decommissioning costs increase over time. •We show how to solve complex real options problems using stochastic dual dynamic integer programming.•We provide a new problem description for the development of mature offshore oil fields.•We estimate the STLT model using recent data on oil futures.•We find that the shutdown decision gets accelerated if decommissioning costs increase over time.
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ISSN:0305-0548
0305-0548
DOI:10.1016/j.cor.2021.105480