Multistage stochastic programming approach for offshore oilfield infrastructure planning under production sharing agreements and endogenous uncertainties
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The paper presents a new optimization model and solution approach for the investment and operations planning of offshore oil and gas field infrastructure. As compared to the conventional models where either fiscal rules or uncertainty in the field parameters is considered, the proposed model is the first one in the literature that includes both of these complexities in an efficient manner. In particular, a tighter formulation for the production sharing agreements based on our recent work, and a perfect positive or negative correlation among the endogenous uncertain parameters (field size, oil deliverability, water–oil ratio and gas–oil ratio) is considered to reduce the total number of scenarios in the resulting multistage stochastic formulation. To solve the large instances of the problem, a Lagrangean decomposition approach allowing parallel solution of the scenario subproblems is implemented in the GAMS grid computing environment. Computational results on a variety of oilfield development planning examples are presented to illustrate the efficiency of the model and the proposed solution approach.