1) lithofacies identification
岩相识别
1.
This paper studies and explores the application of K-means clustering algorithm to lithofacies identification.
本文研究和探索K-均值方法在岩相识别中的应用。
2) well logs
岩相识别
1.
In this paper,Two ANN models-D-Kohonen NN and D-BP NN, for automatic recognitions of lithofacies from well logs by analysis of well logging facies have been developcd on SUN workstation.
在实际应用中对比了ＡＷ岩相识别和传统多元统计岩相识别的效果，证明了ＡＮＮ模式识别技术用于测井相分析的可行性和优越性。
3) volcanic subfacies identification
火山岩亚相识别
4) lithologic identification
岩性识别
1.
A lithologic identification method of igneous rocks and its application:a case of the igneous reservoir in Block Zao-35;
火成岩岩性识别方法及其应用研究——以大港枣园油田枣35块火成岩油藏为例
2.
Aiming at the fuzzy character that exists in complex lithologic identification,the problems of lithologic identification are researched by cross plot and fuzzy clustering algorithm.
针对复杂岩性识别中存在的模糊性,应用交会图和模糊聚类方法对复杂岩性储层的岩性识别问题进行了研究。
3.
Because the effect of lithology is far in excess of fluid,lithologic identification is espe- cially important in the area.
徐深气田储层主要以火山岩为主,而火山岩储层岩性复杂多变,其岩性的影响远远超过流体的影响,因此岩性识别对该地区显得尤为重要。
5) lithological discrimination
岩性识别
1.
On the basis of analyzing the speciality of the limestone reservoir which is micrite muscovite quality, the lithological discrimination method and reservoir dividing standards of it are established with combination of oil well and core a-nalysis data.
本文在对泥晶白云质灰岩储层的特殊性进行分析的基础上,结合测井和岩心分析资料,建立了泥晶白云质灰岩储层岩性识别方法和储层划分标准,并结合试油资料,总结了该类储层流体性质的识别方法和解释标准,在实际生产应用中取得了较好的效果。
2.
This system, which is developed on the basis of FORWARD platform and can be run in Sun workstation and microcomputers, is made up of the 3D horizontal well description and reservoir spread subsystem, the environmental correction subsystem lithological discrimination subsystem and interpretation subsystem.
本系统由水平井三维描述及油藏展布子系统、水平井环境校正子系统、水平井岩性识别子系统、水平井解释子系统构成,基于FORWARD平台开发并能在Sun工作站和微机上运行,使用Visual C++/Matlabe/Fortran为编程工具混编而成,较为先进的人机交互式界面系统,将上述子系统融为一体,突出了本系统界面友好、自动化程度高、可用性强的特点。
3.
Based on it,this paper introduces the evaluation research and applications from lithological discrimination,reservoir identification and reservoir parameter determination.
在此基础上,本文从火山岩岩性识别、储层识别、储层参数确定等方面开展了测井评价研究与应用,总结出适合地区特点、可操作性强的火山岩储层测井评价方法,效果显著。
6) lithologic recognition
岩性识别
1.
The study has been carried out for application of BP neural networks technique to lithologic recognition in logging interpretation of volcanic rocks in view of the speciality of volcanic reservoir (complexity.
针对火山岩储层的特殊性(复杂性、离散性和随机性),应用BP神经网络技术对火山岩测井解释中岩性识别问题进行了研究。
2.
By applying the algorithms to some examples and practical lithologic recognition, the results show that the algorithms are effective.
针对ＢＰ网络存在易陷入局部极小和收敛速度慢的问题，本文根据遗传算法的特长，在网络学习算法中使用遗传算法，克服了上述弊端，在岩性识别的样本学习中，取得了较好的结果。
补充资料：嘲四相（宣宗时曹确、杨收、徐商、路岩同秉
【诗文】：
确确无余事，钱财总被收。商人都不管，货赂几时休。
【注释】：
【出处】：
全唐诗：卷872-5
确确无余事，钱财总被收。商人都不管，货赂几时休。
【注释】：
【出处】：
全唐诗：卷872-5
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