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

Susara A. Heever () and Ignacio E. Grossmann ()
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Susara A. Heever: Carnegie Mellon University
Ignacio E. Grossmann: Carnegie Mellon University

Chapter Chapter 10 in Handbook on Modelling for Discrete Optimization, 2006, pp 291-315 from Springer

Abstract: 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.

Keywords: Oilfield planning; MINLP; aggregation; decomposition (search for similar items in EconPapers)
Date: 2006
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DOI: 10.1007/0-387-32942-0_10

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