The design of production systems of gas fields is a difficult task because
of the nonlinear nature of the optimization problem and the complex
interactions between each operational parameter. Conventional methods, which
are usually stated in precise mathematical forms, cannot include the
uncertainties associated with vague or imprecise information in the objective
and constraint functions.
This paper proposes a fuzzy nonlinear programming approach to accommodate
these uncertainties and applies it to a variety of optimization processes.
Specifically, the fuzzy λ-formulation is combined with a hybrid
coevolutionary genetic algorithm for the optimal design of gas-production
systems. Both the multiple conflicting objective and constraint functions for
production systems of gas fields are formulated in a feasible fuzzy domain.
Then, the genetic algorithm is used as a primary optimization scheme for
solving the optimum gas-production rates of each well and the pipeline segment
diameters to minimize the investment cost with a given set of constraints in
order to enhance the ultimate recovery.
The synthetic-optimization method can find a global compromise solution and
offer a new alternative with significant improvement over the existing
conventional techniques. The reliability of the proposed approach is validated
by a synthetic practical example yielding more-improved results. This method
constitutes an offering of a powerful tool for cost savings in the planning and
optimization of gas-production operations.
© 2010. Society of Petroleum Engineers
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- Original manuscript received:
15 April 2007
- Meeting paper published:
12 June 2006
- Revised manuscript received:
30 July 2009
- Manuscript approved:
29 September 2009
- Published online:
4 March 2010
- Version of record:
17 June 2010