1) oil and water zone identification evaluation
油水层识别评价
2) 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。
3) oil and water layers evaluation
油水层评价
4) identification and evaluation
识别评价
1.
Starting from the basic problem of oil, gas and water layers identification and evaluation, the authors analyzed the present situation of mud lo.
从油气水层识别和评价的基本问题入手,分析了录井识别评价技术的现状;指出地层是否产水识别不准、特殊钻井条件下油气层识别困难是当前录井存在的主要问题,而地层是否含水缺乏检测手段、地层含气的检测手段单一是制约录井技术发展的瓶颈;介绍了开展岩心含水分析、微量气体分析研究工作的思路和进展情况,认为这两项技术的开发应用,有助于油气水层解释评价水平的提高,符合录井技术的发展方向,对于提高录井技术水平具有重要意义。
2.
In this paper, based on the requirements of the integrated management system, the identification and evaluation of the activities of the organization and management control program were established.
在已有的文献中,对单独的环境因素和危险源如何识别评价有较多的论述,但是多数方法较复杂,且适应性受到限制,对整合的体系如何有效地识别和评价环境因素和危险源没有详细的说明。
5) 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
6) oil water stratum identification model
油水层识别模型
补充资料：储层描述(见油气田储层评价)
储层描述(见油气田储层评价)
reseroir evaluation of oil and gas field
储层描述(reseroir evaluation of 011 and gasfield)见油气田储层评价。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条