利用混合遗传算法设计海底处理系统

Leonardo Sales, J. Jäschke, M. Stanko
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引用次数: 0

摘要

设计海底生产系统是一项由经验丰富的多学科工程师团队耗时数月完成的任务。在这项工作中,提出了一种计算机混合方法,利用遗传算法结合梯度搜索方法来寻找最优设计并支持海底生产系统设计。遗传算法用于优化生产系统结构,梯度法用于解决与流量、油藏产能、设备容量等相关的连续非线性变量。研究案例基于Goliat油田。将这种混合方法与一种精确方法进行了比较。与精确的方法相比,混合方法成功地找到了在更短的运行时间内最大化净现值的海底配置。所提出的方法为海底生产系统设计的建模和自动化决策提供了一种进步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Designing Subsea Processing Systems Using a Hybrid Genetic Algorithm
Designing a subsea production system is a task that takes several months to complete by an experienced and multidisciplinary team of engineers. In this work, a computerized hybrid method to find optimal designs and support subsea production system design using a genetic algorithm combined with a gradient search method is proposed. The genetic algorithm is formulated to optimize the structure of the production system, while the gradient method solves the continuous non-linear variables related to flow rates, reservoir deliverability, equipment capacities, and others. The study case is based on the Goliat field. This hybrid approach is compared with an exact method. The hybrid method successfully finds subsea configurations that maximize the net present value in shorter running times when compared to an exact method. The methodology presented provides an advancement toward modelling and automated decision-making in subsea production system design.
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