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A Mixed-Integer Nonlinear Programming Approach to the Optimal Planning of Offshore Oilfield Infrastructures

In: Handbook on Modelling for Discrete Optimization

Author

Listed:
  • Susara A. Heever

    (Carnegie Mellon University)

  • Ignacio E. Grossmann

    (Carnegie Mellon University)

Abstract

A multiperiod Mixed Integer Nonlinear Programming (MINLP) model for offshore oilfield infrastructure planning is presented where nonlinear reservoir behavior is incorporated directly into the formulation. Discrete decisions include the selection of production platforms, well platforms and wells to be installed/drilled, as well as the drilling schedule for the wells over the planning horizon. Continuous decisions include the capacities of the platforms, as well as the production profile for each well in each time period. For the solution of this model, an iterative aggregation/disaggregation algorithm is proposed in which logic-based methods, a bilevel decomposition technique, the use of convex envelopes and aggregation of time periods are integrated. Furthermore, a novel dynamic programming sub-problem is proposed to improve the aggregation scheme at each iteration in order to obtain an aggregate problem that resembles the disaggregate problem more closely. A number of examples are presented to illustrate the performance of the proposed method.

Suggested Citation

  • Susara A. Heever & Ignacio E. Grossmann, 2006. "A Mixed-Integer Nonlinear Programming Approach to the Optimal Planning of Offshore Oilfield Infrastructures," International Series in Operations Research & Management Science, in: Gautam Appa & Leonidas Pitsoulis & H. Paul Williams (ed.), Handbook on Modelling for Discrete Optimization, chapter 0, pages 291-315, Springer.
    • Handle: RePEc:spr:isochp:978-0-387-32942-0_10
    DOI: 10.1007/0-387-32942-0_10
    as

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