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A genetic algorithm integrated with Monte Carlo simulation for the field layout design problem

机译:与蒙特卡罗模拟集成的遗传算法,用于现场布局设计问题

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摘要

Oil and gas production is moving deeper and further offshore as energy companies seek new sources, making the field layout design problem even more important. Although many optimization models are presented in the revised literature, they do not properly consider the uncertainties in well deliverability. This paper aims at presenting a Monte Carlo simulation integrated with a genetic algorithm that addresses this stochastic nature of the problem. Based on the results obtained, we conclude that the probabilistic approach brings new important perspectives to the field development engineering.
机译:随着能源公司寻求新来源,石油和天然气产量正在越来越深,野外布局设计问题更为重要。 虽然在修订的文献中呈现了许多优化模型,但它们没有正确考虑在良好的可递送性方面的不确定性。 本文旨在提出与遗传算法集成的蒙特卡罗模拟,该遗传算法解决了该问题的这种随机性质。 根据获得的结果,我们得出结论,概率方法为现场开发工程带来了新的重要观点。

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  • 来源
    《Oil & gas science and technology》 |2018年第2期|共17页
  • 作者单位

    Federal University of Ceara Operational Research in Production and Logistics Laboratory Campus do Pici Bl. 714 Fortaleza CE 60.440-900 Brazil;

    Federal University of Ceara Department of Industrial Engineering Operational Research in Production and Logistics Laboratory Campus do Pici Bl. 714 Fortaleza CE 60.440-554 Brazil;

    Federal University of Ceara Department of Industrial Engineering Operational Research in Production and Logistics Laboratory Campus do Pici Bl. 714 Fortaleza CE 60.440-554 Brazil;

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  • 正文语种 eng
  • 中图分类 化学工业;
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