| 辽河东部凹陷火成岩测井岩性识别方法与应用 |
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| 引用本文： | 王红菲,江玉龙,陆哲昆,王祝文.辽河东部凹陷火成岩测井岩性识别方法与应用[J].世界地质,2016,35(2):510-525. |
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| 作者姓名： | 王红菲 江玉龙 陆哲昆 王祝文 |
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| 作者单位： | 1. 吉林大学 地球探测科学与技术学院，长春 130026; 2. 中国电建集团 中南勘测设计研究院有限公司，长沙 410014; 3. 江西省交通设计研究院有限责任公司，南昌 330002 |
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| 摘 要： | 采用基于K-means聚类算法的RBF神经网络法对辽河盆地东部凹陷火成岩岩性进行识别。综合利用自然伽马、补偿中子、声波时差、密度与电阻率的实际测井资料,建立火成岩岩性识别的基础RBF神经网络。选取有岩芯和岩屑记录的若干井次试验验证,该方法清楚地识别出了玄武岩、粗面岩等6种火成岩,识别准确率平均可达70%以上。
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| 关 键 词： | 火成岩 岩性识别 K－means 聚类算法 ＲBF 神经网络 |
Lithologic identification and application for igneous rocks in eastern depression of Liaohe oil field |
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| WANG Hong-Fei,WANG Yu-Long,LU Zhe-Kun,WANG Zhu-Wen.Lithologic identification and application for igneous rocks in eastern depression of Liaohe oil field[J].World Geology,2016,35(2):510-525. |
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| Authors: | WANG Hong-Fei WANG Yu-Long LU Zhe-Kun WANG Zhu-Wen |
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| Institution: | 1. College of Geo- exploration Science and Technology，Jilin University，Changchun 130026，China; 2. PowerChina Zhongnan Engineering Corporation，Changsha 410014，China; 3. Communications Design Ｒesearch Institute Co． ，Ltd of Jiangxi Province，Nanchang 330002，China |
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| Abstract: | A new hydrid algorithm for training ＲBF network based on moving K- -means clustering algorithm was adopted to identify the types of igneous rocks in eastern depression of Liaohe oil field． By synthetically using natural gamma，neutron，acoustic，density and resistivity logging data，the basic ＲBF neural network of igneous li- thology identification has been established． Some wells with cores and cuttings are selected to test，the result shows that the method clearly identified the basalt and trachyte， 6 kinds of igneous rocks． The accuracy of recognition rate is more than 70%． |
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| Keywords: | igneous rock lithology identification K- - means clustering algorithm ＲBF neural network |
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