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A prediction to the best artificial lift method selection on the basis of TOPSIS model

机译:基于TOPSIS模型的最佳人工举升方法选择的预测

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Artificial lift as a system adding energy to the fluid column in a wellbore to initiate and enhance production from the well is necessary when reservoir drives do not sustain acceptable rates or cause fluids to flow at all in some cases which use a range of operating principles, including pumping and gas lifting. Technique for order preference by similarity to ideal solution (TOPSIS) model or method is one of the most prevalent multi criteria decision making methods to solve problems involving selection from among a finite number of criteria and specify the attribute information in order to arrive at a choice. In this paper, a novel software method on the basis of technique for order preference by similarity to ideal solution model has been enabled to present the best artificial lift method selection for different circumstances of oil fields.
机译:当油藏驱动器无法维持可接受的速率或在某些情况下使用一系列操作原理导致流体完全流失时,必须使用人工举升作为向井眼中的液柱添加能量以启动和提高油井产量的系统,包括抽水和气举。通过与理想解决方案(TOPSIS)模型相似的方法进行订单偏好的技术是最普遍的多准则决策方法之一,用于解决涉及从有限数量的准则中进行选择并指定属性信息以得出选择的问题。在本文中,基于与理想解决方案模型相似的顺序偏好技术的一种新的软件方法已被启用,可以为油田的不同情况提供最佳的人工举升方法选择。

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