| 支持向量机与微电阻率成像测井识别火山岩岩性 |
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| 引用本文： | 张莹,潘保芝.支持向量机与微电阻率成像测井识别火山岩岩性[J].物探与化探,2011,35(5):634-638,642. |
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| 作者姓名： | 张莹 潘保芝 |
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| 作者单位： | 1. 广东海洋大学信息学院,广东湛江,524088
2. 吉林大学地球探测科学与技术学院,吉林长春,130026 |
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| 摘 要： | 针对火山岩储层,从岩石化学成分分类和岩石结构分类两个角度出发,提出了一种利用测井资料识别火山岩岩性的方法。基于取芯薄片鉴定资料获得对应井段的常规测井数据,利用统计学习理论中的支持向量机方法对其处理,得到地质上按岩石化学成分分类的火山岩岩性类别。建立地层微电阻率成像测井图像与不同结构火山岩岩性之间的对应关系,归纳出典型的微电阻率图像模式,从而得到地质上按岩石结构分类的火山岩岩性类别,结合上述两者结论确定最终岩性,实现了运用支持向量机算法处理常规测井资料与微电阻率图像模式相结合的火山岩岩性测井识别新方法。
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| 关 键 词： | 支持向量机 地层微电阻率成像测井 火山岩岩性识别 |
THE APPLICATION OF SVM AND FMI TO THE LITHOLOGIC IDENTIFICATION OF VOLCANIC ROCKS |
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| ZHANG Ying,PAN Bao-zhi.THE APPLICATION OF SVM AND FMI TO THE LITHOLOGIC IDENTIFICATION OF VOLCANIC ROCKS[J].Geophysical and Geochemical Exploration,2011,35(5):634-638,642. |
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| Authors: | ZHANG Ying PAN Bao-zhi |
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| Institution: | ZHANG Ying1,PAN Bao-zhi2 (1.College of Information,Guangdong Ocean University,Zhanjiang 524088,China,2.College of Geoexploration Science and Technology,Jilin University,Changchun 130026,China) |
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| Abstract: | From the viewpoint of chemical composition categorization and structure classification of rocks,an effective method was proposed to identify the lithology of volcanic rocks by using logging data.On the one hand,the conventional logging data could be obtained by core wafer identification.Thus,after processing the data with Support Vector Machines(SVM) method of statistical theory,we could get the lithologic type of the volcanic rocks,which are classified according to the chemical composition of rocks.On the ... |
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| Keywords: | Support Vector Machines formation micro-resistivity imaging logging lithologic identification of volcanic rock |
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