1) 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。
2) oilfield flooded layer identification
油田水淹层识别
1.
Algorithm of oilfield flooded layer identification based on Boosting;
基于Boosting的油田水淹层识别算法
3) oil and water zone identification evaluation
油水层识别评价
4) oil water stratum identification model
油水层识别模型
5) oil-water identification chart
油水层识别图版
6) oil/gas/water layer identification
油气水层识别
1.
In well-logging interpretation,oil/gas/water layer identification is virtually pattern identification.
测井解释过程中的油气水层识别实质是一个模式识别问题。
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参考词条