| 用自组织神经网络自动识别岩相 |
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| 引用本文： | 薛林福,潘保芝. 用自组织神经网络自动识别岩相[J]. 吉林大学学报(地球科学版), 1999, 29(2): 144-147 |
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| 作者姓名： | 薛林福 潘保芝 |
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| 作者单位： | 1. 长春科技大学地球科学学院,长春,130026
2. 长春科技大学地球探测与信息技术学院,长春,130026 |
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| 基金项目： | 高等学校博士学科点专项科研项目;9418701; |
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| 摘 要： | ＢＰ神经网络技术以其强大的学习能力已广泛应用于许多领域,取得了很好效果。但当不具备已知样本时,该技术很难应用。本文采用改进的自组织神经网络,对测井资料进行自动岩相识别,并在松辽盆地进行了实际应用。通过与已知资料对比,证实该方法是一种有效的岩相自动识别方法,具有良好的应用前景。
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| 关 键 词： | 自组织神经网络 岩相 自动识别 测井资料 |
| 修稿时间： | 1998-05-04 |
IDENTIFY LITHOFACIES AUTOMATICALLY USING SELF-ORGANIZING NEURAL NETWORK |
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| Xue Linfu,Pan Baozhi. IDENTIFY LITHOFACIES AUTOMATICALLY USING SELF-ORGANIZING NEURAL NETWORK[J]. Journal of Jilin Unviersity:Earth Science Edition, 1999, 29(2): 144-147 |
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| Authors: | Xue Linfu Pan Baozhi |
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| Abstract: | Back propagation neural network technique has been applied to many areas due to itspowerful capacity of learning and achieved good results. When there is no known samples for learning,the technique can not be applied successfully. The paper applied the self--organizing neural network toidentify automatically lithology from log data. The method was applied to Songliao basin and it is verified by comparing with the known lithology column in some real wells that the technique is successful for lithology identification. |
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| Keywords: | self-organizing neural network lithofacies automatic identification log data |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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