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Safety evaluation of casing string based on BP artificial neural network

机译:基于BP人工神经网络的套管串安全评估

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In the traditional safety assessment of casing string, some influencing factors are ignored for modelling convenience, which makes the casing string safety assessment effect of oil and gas well not very ideal. For complexity and randomness of casing load and its properties parameters in complex well conditions, BP artificial neural network is created in MATLAB based on the analysis of the influencing factors of casing string security. Casing string section whose safety assessment is more mature is taken as a sample to train the BP neural network. The trained network is applied to make case assessment. At the same time, GUI interface is applied to implement the visualization. The results show that safety evaluation of the casing string can be achieved by using BP neural network. The accuracy of the casing string network safety evaluation is high. It will realize the visualization of safety evaluation and provide more accurate and effective reference for the design of casing string.
机译:在套管弦的传统安全评估中,一些影响因素被忽略了建模方便,这使得石油和天然气的套管串安全评估效果不是非常理想的。对于套管负荷的复杂性和随机性以及复杂井条件中的特性参数,基于套管串安全性影响因素的MATLAB中创建了BP人工神经网络。套管字符串部分,其安全评估更加成熟,作为培训BP神经网络的样本。培训的网络应用于进行案例评估。同时,将应用GUI接口来实现可视化。结果表明,通过使用BP神经网络,可以实现壳体串的安全评估。套管串网络安全评估的准确性高。它将实现安全评估的可视化,为壳体串的设计提供更准确和有效的参考。

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