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Decision-Making Technology of Well Candidates Selection in In-depth Profile Control Based on Projection Pursuit Clustering Model

机译:基于投影追踪聚类模型的深层剖面控制井候选选择决策技术

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Due to the long-term waterflooding,thief zone is widely developed in the mature field.As a result,the oil production drops and the water cut rises sharply.As an effective technology to extend the economic life of mature fields,in-depth profile control can fully exploit the remaining oil and improve oil recovery.The decision-making of well selection is key to in-depth profile control measures in the oilfield.]n order to solve this problem,we build several indicator sets to measure the need of in-depth profile control for the well candidates.Then we propose a projection pursuit clustering model for well candidates and use the gravitational search algorithm to find the optimal projection direction.Finally,the coefficient for decision-making is obtained based on the optimal projection direction and the technology of well candidates selection in in-depth profile control is established.We apply this method to Bei 301 block of Hailar and the prediction results are compared with the fuzzy synthesis decisionmaking method.The result shows that the well candidates in Bei 301 block of Hailar are divided into two categories according to their own characteristics in the projection pursuit process,that is,four wells need to take in-depth profile control measures in the nine well candidates.In the previous research,decisionmaking of well selection in in-depth profile control is almost based on fuzzy synthetic decision-making.In that method,the weight of indicators is determined artificially,featuring subjective nature.However,the method used for decision-making in this paper is based on the feature of well candidates and relatively objective compared with the previous method.The program execution time for these two methods shows that the one proposed in this study is more efficient and accurate.The method adopted in this study solves the artificial weighting problem in the current well selection decision-making and makes the result more objective,which can provide better guidance for the decisionmaking of well selection in in-depth profile control and extend the economic life of mature fields.
机译:由于长期的水上飞行,小偷区在成熟的领域中广泛发展。结果,石油产量下降和水切口急剧上升。一种有效的技术,扩展成熟田地的经济寿命,深入的剖面控制可以充分利用剩余的石油并改善石油回收。井选择的决策是油田中深入剖面控制措施的关键。] N命令解决这个问题,我们建立了几个指标集来衡量需要对于井候选的深度轮廓控制。该改变了一个投影追踪聚类模型,用于良好的候选,并使用重力搜索算法来找到最佳投影方向。最后,基于最佳投影方向获得决策系数建立了深入配置剖面控制中的井候选选择的技术。我们将这种方法应用于Hailar的Bei 301块,并将预测结果与模糊语法进行比较Hailare的结果表明,北方北方的井候选人分为两类,根据自己的特点,即投影追踪过程,即四个井需要在九个中进行深入的剖面控制措施霍尔克莱斯。在以前的研究中,在深入的型材控制中的井选择的决策几乎基于模糊的合成决策制定。在该方法中,指标的重量是人为地确定的,具有主观性。但是,使用的方法本文的决策是基于候选人的特征,与先前的方法相比,比较这两种方法的节目执行时间表明,本研究中提出的程序执行时间更有效和准确。此方法采用的方法研究解决了当前井选择决策中的人工加权问题,使结果更客观,这可以提供更好的指导f或者在深入的型材控制中的井选择作出决策,扩大了成熟领域的经济寿命。

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