西南石油大学学报(自然科学版) ›› 1998, Vol. 20 ›› Issue (2): 12-15.DOI: 10.3863/j.issn.1000-2634.1998.02.04

• 油气藏工程 • 上一篇    下一篇

基于神经网络的测井评价油层污染研究

夏宏泉 廖明光   

  1. (西南石油学院石油勘探系,四川 南充 637001)
  • 收稿日期:1997-12-23 修回日期:1900-01-01 出版日期:1998-04-20 发布日期:1998-04-20

Logging Evaluation of Reservoir Contamination Based on Neural Network

Xia Hong-quan Liao Ming-guang   

  1. Dept. of Petroleum Exploration,SWPI, Sichuan, 637001
  • Received:1997-12-23 Revised:1900-01-01 Online:1998-04-20 Published:1998-04-20

摘要: 利用测井资料,在剖析传统的测井评价油(气)层污染方法的基础上,介绍了利用BP神经网络这一现代数理统计新技术来实现测井多参数评定油气层污染程度的方法和技巧;以华北二连油田实际资料为例,建立了测井判释油气层污染的数学物理模型,并进行了模拟预测。结果表明:该法简便可行,对污染评价参数预测精度较高,对污染程度评价合理准确,可作为油(气)层污

关键词: 油层污染, 测井数据, 神经网络, 数学模型, 评价

Abstract: The damaged degree of formation can be assessed with logging information. Based on those normal process methods, some practical methods and technique to evaluate reservoir contamination by means of artificial neural network and log parameters are introduced in the paper. According to some wells data from Huabei-Erlian oilfield, we developed its neural network mathematical model to evaluate the damaged formation, and conducted modeling prediction. All the results show that this method is feasible and simple, and can accurately predict the contamination parameters and evaluate the damaged degree exactly and reasonably. It can be taken as a new and successful approach to evaluate formation contamination quantitatively. 

Key words: Reservoir contamination, Log data, Nerv network, Math’s model, Evaluation

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