节点文献

运用多地震属性和神经网络预测岩性

Litholoy Prediction with Multiple Seismic Attributes and Neural Network

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 崔丽玲齐龙瑜刘松芬胡北来

【Author】 Cui Liling Qi Longyu Liu Songfen Hu Beilai (College of Physics Science,Nankai University,Tianjin 300071,China)

【机构】 南开大学物理科学学院南开大学物理科学学院 天津 300071天津 300071

【摘要】 利用多地震属性和 BP 神经网络可以得到胜利油田垦71地区的岩性预测,由井附近的地震道中可以提取井数据和多地震属性,并由此得到岩性信息,再用 BP 网络对岩性信息进行标定,岩性分布是基于训练好的网络和该地区的多地震属性进行计算的,结果与该区域未参加训练的井资料相比符合率为75%。

【Abstract】 The lithology prediction in the Ken-71 area of Shengli Oil Field is achieved by multiple seismic at- tributes and Backpropagation(BP)neural network.We use BP neural network to calibrate the lithology infor- mation extracted from the well logs and multiple seismic attributes extracted from the trace near the well.The lithology distributions are calculated based on well trained network and multiple seismic attributes of the area. The calculated results are about 75% agreement with the data of the wells in the area which are not in the training network.

【基金】 Supported by the National Natural Science Foundation of China(60274051);The Study and Application of Artificial Intelligence Litholoy Identification and Prediction Technology(2003BA613A-10-05)
  • 【文献出处】 南开大学学报(自然科学版) ,Acta Scientiarum Naturalium Universitatis Nankaiensis , 编辑部邮箱 ,2007年02期
  • 【分类号】P315.9
  • 【被引频次】11
  • 【下载频次】265
节点文献中: 

本文链接的文献网络图示:

本文的引文网络