A Multiple Objective Optimization under Parameter Uncertainty for Measure Program of Oil Field
油田措施配置多目标随机规划

measure programming is very essential to extend the time limit of stable production, to plan reasonable measures to oil field to enhance the oil recovery rate and the final recovery . Some determinate models have been established on the programming of oilfield production-stabilizing measures, in which parameters are all pre-determined. In fact, many production-factors can not be determined in advance. In this paper, the multi-object model with random parameters has been constructed for the measure programming . The model can be efficaciously solved with the genetic algorithm, which has the characteristic of whole area searching and highly effective. The method has been applied to the practical oil field and shows that the random programming method is very efficient to make oilfield development plan and can be used as a powerful tool.