摘要
针对油田开采系统的各种复杂因素和在油田开发规划时资源约束水平可能是不确定的或有多个决策者参与决策的问题,利用多目标线性规划的扩展理论和方法——多准则多约束水平线性规划的理论和方法,研究了油田的措施产量优化分配问题。建立了以措施产油量最大、措施的总效益最好为目标,以在不同资源约束水平下的措施产量、费用和工作量为约束条件的油田措施产量分配的优化模型。与以往的模型相比,该模型的约束条件的右边是不固定的。根据模型的特殊性,提出利用多准则多约束水平线性规划的内点法求解,即按约束水平的个数将模型拆分成相应个数的多目标线性规划,利用多目标线性规划的内点法求出对应的非劣解,最后求出原模型的解。实例研究结果表明,笔者建立的模型和提出的解法可成功地解决油田措施增油阶段的资源约束水平不固定或发生变化时,油田的措施产量最优分配决策问题,可为决策制定者提供相应的备选规划方案。
In consideration of the problems of various complex factors in the oilfield exploitation system and uncertainties of resource constraint levels and several decision makers in oilfield development plan,the problem of oilfield production output distribution was studied by the expansion theory and method of multiple objective linear programming----the theory and method of multiple criteria and multiple constraint level linear programming.And an optimization model of oilfield production output distribution was established,its objectives were maximizing output and total benefit side.Compared with those old models,the tight side of constraint conditions of the model was not fixed.Based on the particularity of the model,the solution method was designed by interior-point approach of the multiple criteria and multiple constraint level linear programming.That is,the model was divided into the same number multiple objective linear programming according to the constraint level,the corresponding non-dominated solution was derived with interior-point method of multiple objective linear programming to establish the solution of the original model.The results show that the model and method can solve successfully the problem of the oilfield production optimization distribution when the resource constraint levels are not fixed or changeable at the oilfield production optimization stage,and provide the contingency plan for decision makers.
出处
《石油天然气学报》
CAS
CSCD
北大核心
2008年第5期124-128,共5页
Journal of Oil and Gas Technology
关键词
开发规划
措施产量
多准则多约束水平
线性规划
优化模型
development programming
improved production
multiple criteria and multiple constraint levels
linear programming
optimization model