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Real-time Diagnostics of Oil Production Equipment using Data Mining

机译:利用数据挖掘的石油生产设备的实时诊断

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摘要

In this paper, we consider the problem of increasing the efficiency of heavy oil production by a qualitative enhanced oil recovery (EOR) application. A novel approach, based on the analysis of data related to successful events is proposed. In particular, a synthesised model, targeted to automated search of wells for EOR application, is developed. For data processing, we present a novel approach based on a hybrid implementation of neural network analysis techniques and evolutionary algorithms. The presented approach enables the selection of EOR in fuzzy, difficult to formalise, oilfield conditions and consequently reduces the dependency on human factors.
机译:在本文中,考虑到通过定性增强的储存(EOR)应用提高重油效率的问题。提出了一种基于与成功事件相关的数据分析的新方法。特别地,开发了一种综合模型,用于自动搜索EOR应用程序的井。对于数据处理,我们提出了一种基于神经网络分析技术和进化算法的混合实施的新方法。所提出的方法使得能够在模糊中选择EOR,难以正式,油田条件,从而降低对人类因素的依赖。

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