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A simple and inexpensive design for volume fraction prediction in three-phase flow meter: Single source-single detector

机译:三相流量计中体积分数预测的简单廉价设计:单源 - 单次检测器

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摘要

The problem of how to correctly predict the volume fraction in three-phase flows in sensitive operational conditions is an important parameter in the oil and petroleum industry. This research presents a new methodology for volume fraction percentage prediction in water-gasoil-air multiphase systems based on transmitted gamma ray method and multilayer perceptron (MLP). The detection system uses an appropriate single source-single detector set-up, consists of a dual-energy gamma-ray source and one NaI(Tl) detector. The experimental setup provides the required data for training and testing the network. Using this proposed method, the volume fraction was predicted in water-gasoil-air three-phase flows with mean relative error percentage (MRE%) less than 4.64% and root mean square error (RMSE) of 1.49. MER% quantities for each phase of water, gasoil and air were calculated 3.72, 4.54 and 5.65, respectively. Also, the RMSE quantities were measured 0.79, 1.46 and 1.98 for water, gasoil and air, respectively. The results revealed that a good agreement is between the predicted volume fraction percentage and actual data due to the comparison of the performance of the proposed method (MLP) and the relationship derived from empirical data. The old systems used were adequately complicated whereas the new design is certainly very simple. Also, radiation safety and shielding conditions ans electronic requirements are optimized. So the cost is minimized as low as possible.
机译:如何正确预测敏感操作条件下三相流量的体积分数是石油和石油工业中的重要参数。本研究提出了一种基于透射的伽马射线法和多层感知(MLP)的水 - 空气多相系统体积分数百分比预测的新方法。检测系统使用适当的单源 - 单次检测器设置,包括双能伽马射线源和一个NAI(TL)检测器。实验设置提供了用于培训和测试网络的所需数据。使用该方法,在水 - 空气三相流动中预测体积分数,其平均相对误差百分比(MRE%)小于4.64%,根均方误差(RMSE)为1.49。水,胃和空气的每相的MER%量分别计算3.72,4.54和5.65。而且,水分,胃和空气的测量0.79,1.46和1.98的RMSE量。结果表明,由于所提出的方法(MLP)的性能和源自经验数据的关系,良好的一致性是预测的体积分数百分比和实际数据。使用的旧系统充分复杂,而新设计肯定是非常简单的。此外,辐射安全和屏蔽条件ANS电子需求优化。因此,成本尽可能低。

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