1) discrimination of oil-water zone
油水层判别
2) identification of oil-water zone
油(气)水层判别
3) Distinguishing oil bearing reservoirs from water bearing reservoirs
油水层综合判别
4) oil and water layer identification
油水层识别
1.
In oil and water layer identification,using neural computing has disadvantages including complex network structure and long training time caused by large input information space dimension,and low matching accuracy of network caused by redundant attribute.
在油水层识别中,单纯使用神经计算存在因输入信息空间维数较大而使网络结构复杂、训练时间长,以及因冗余属性使网络拟合精度不高等缺点,为此基于属性约简和最优化原理提出一种简化的神经计算方法,主要包括基于粗糙集的样本属性约简算法,基于LM方法的稳定学习算法,以及基于黄金分割的隐含层节点数确定的优化算法等。
2.
In accordance with the characteristics of heavy oil reservoir in Tuha oilfield,this paper studies oil and water layer identification method and productivity prediction method on the basis of reservoir characteristic study combining with geochemical and logging data.
现场应用达到了油水层识别和产能预测的目的,产生了良好的经济效益和社会效益。
5) reservoir identifica-tion
储层判别
6) diagnostic horizon
判别层
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