刘波, 鄢捷年, 李静. 泥页岩分类的BP神经网络方法[J]. 石油钻采工艺, 2003, 25(4): 20-22. DOI: 10.3969/j.issn.1000-7393.2003.04.007
引用本文: 刘波, 鄢捷年, 李静. 泥页岩分类的BP神经网络方法[J]. 石油钻采工艺, 2003, 25(4): 20-22. DOI: 10.3969/j.issn.1000-7393.2003.04.007
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Liu Bo, Yan Jienian, Li Jing. PREDICTION OF THE SHALE PERFORMANCE BY THE BP NEURAL NETWORK[J]. Oil Drilling & Production Technology, 2003, 25(4): 20-22. DOI: 10.3969/j.issn.1000-7393.2003.04.007
Citation: Liu Bo, Yan Jienian, Li Jing. PREDICTION OF THE SHALE PERFORMANCE BY THE BP NEURAL NETWORK[J]. Oil Drilling & Production Technology, 2003, 25(4): 20-22. DOI: 10.3969/j.issn.1000-7393.2003.04.007
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泥页岩分类的BP神经网络方法

PREDICTION OF THE SHALE PERFORMANCE BY THE BP NEURAL NETWORK

    摘要
  • 摘要: 为探讨X衍射资料与泥页岩理化性能之间的定性关系,建立一种智能化模型对泥页岩的类型进行快速识别。在分析泥页岩理化性能与X射线衍射资料数据关系的基础上,提出了用BP神经网络预测泥页岩理化性能参数的方法及相应的模型。并针对BP神经网络算法进行了改进,使模型网络训练时的收敛速度比常规方法快了4倍以上。通过现场试验数据验证,该模型预测符合率较高,能够满足实际应用的要求。

     

    Abstract: To analyse the relation between the X-Ray data and the shale performance.The model of BP neural network was designed here to predict the shale performance from by the X-Ray data.This model has been modified for good constringency rate more 4 times than that of the conventional methods.Thought the validation of the oil fields data,the model has a good performance and can meet the demand of the practical application.

     

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