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| Keywords | |
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igneous rock |
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lithology identification |
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K- - means clustering algorithm |
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��BF neural network |
| Authors | |
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WANG Hong-Fei |
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WANG Yu-Long |
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LU Zhe-Kun |
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WANG Zhu-Wen |
| PubMed | |
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Article by Wang, H. F. |
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Article by Wang, Y. L. |
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Article by Lu, Z. K. |
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Article by Wang, Z. W. |
Lithologic identification and application for igneous rocks in eastern depression of Liaohe oil field
WANG Hong-Fei, WANG Yu-Long, LU Zhe-Kun, WANG Zhu-Wen
1. College of Geo- exploration Science and Technology��Jilin University��Changchun 130026��China; 2. PowerChina Zhongnan Engineering Corporation��Changsha 410014��China; 3. Communications Design ��esearch Institute Co�� ��Ltd of Jiangxi Province��Nanchang 330002��China
A new hydrid algorithm for training ��BF 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 ��BF 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%��