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Analysis of Prediction of Pressure Data in Oil Wells Using Artificial Neural Networks

机译:基于人工神经网络的油井压力数据预测分析

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We present a methodology that integrates an artificial intelligent technology called Artificial Neural Networks (ANN´s) to develop and build a forecasting system that determines the behavior of the pressure of an oil reservoir, from its behavior, considered as reference in relation to four neighboring wells, which are producing at the same stratum. 356 data records were taken (a period of one year). During that period, it was observed that pressure curves show a decrease, which describes the behavior of the reservoir. It was also considered as an additional parameter the average pressure of the reservoir, whose information was obtained from the curves, describing the behavior of bottom pressure in the same stratum during the given period. Finally, we present the results of the predictions of pressure data, compared with the actual values of the reservoirs known, to discuss and assess the accuracy of the prediction of the proposed system.
机译:我们提出了一种方法,该方法集成了称为人工神经网络(ANN)的人工智能技术,以开发和构建预测系统,该预测系统根据油藏的行为来确定油藏压力的行为,该行为被视为与四个相邻油藏有关的参考在相同地层生产的油井。进行了356条数据记录(为期一年)。在此期间,观察到压力曲线呈下降趋势,这描述了油藏的行为。储层的平均压力也被视为一个附加参数,该平均压力是从曲线中获得的,描述了给定时间段内同一地层的底部压力的行为。最后,我们将压力数据的预测结果与已知储层的实际值进行比较,以讨论和评估所提出系统的预测准确性。

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