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Integrated development optimization model and its solving method of multiple gas fields

机译:多气田综合开发优化模型及其求解方法

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To optimize production schedule and production plan of multiple gas fields with certain amount of investment and constraints and to maximize their economic benefits under the production sharing contact (PSC) mode, a quantitative relationship was applied to describe the production performance depending on the development status of multiple gas fields in China and abroad. Furthermore, with the PSC-based net present value (NPV) as the objective function, a mixed integer nonlinear programming model for gas fields with optimized production schedule and productivity was established. An adaptive layer-embedded genetic algorithm was proposed to solve this model. Through handling the variables and constraints for solving this model and improving the genetic structure, genetic operators and termination conditions of standard genetic algorithm, modeling and solving techniques were formed for integrated and efficient development of multiple gas fields. Results obtained by three methods, i.e. multi-scheme comparison without mathematical model, standard genetic algorithm which induces penalty function to treat constraints, and adaptive layer-embedded genetic algorithm, were compared. The proposed optimization model is accurate, and the proposed layer-embedded genetic algorithm provides satisfactory convergence and calculation rate, ensuring that multiple gas fields could be exploited orderly.
机译:为了在一定的投资和约束条件下优化多个气田的生产进度和生产计划,并在生产共享联系(PSC)模式下最大化其经济效益,根据煤层气的开发状况,采用定量关系描述生产绩效。国内外多个气田。此外,以基于PSC的净现值(NPV)为目标函数,建立了具有优化生产进度和生产率的气田混合整数非线性规划模型。提出了一种自适应的嵌入式遗传算法来求解该模型。通过处理求解该模型的变量和约束条件,改善遗传结构,遗传算子和标准遗传算法的终止条件,形成了多种气田综合高效开发的建模和求解技术。比较了三种方法的结果,即没有数学模型的多方案比较,诱导惩罚函数以处理约束的标准遗传算法以及自适应层嵌入遗传算法。所提出的优化模型是准确的,所提出的基于层的遗传算法提供了令人满意的收敛性和计算速度,确保了多个气田的有序开采。

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