| 人工神经网络技术在储层描述中的应用 |
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| 引用本文： | 邱立伟,康志江.人工神经网络技术在储层描述中的应用[J].石油实验地质,1999,21(2):166-169. |
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| 作者姓名： | 邱立伟 康志江 |
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| 作者单位： | 中国新星石油公司规划研究院, 北京 100083 |
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| 摘 要： | 建立在经验公式和线性假设基础上的常规测井解释方法其精度和成功率都较低。人工神经网络技术具有自适应、自学习的功能,其在测井解释研究中具有良好的应用前景。本文以实例说明了神经网络技术在测井孔隙度解释中所取得的成果。
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| 关 键 词： | 人工神经网络 BP网络 测井解释 孔隙度 |
| 收稿时间： | 1998-10-20 |
| 修稿时间： | 1998-10-20 |
APPLICATION OF ARTIFICIAL NEURAL NETWORKS TO RESERVOIR DESCRIPTION |
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| QIU Liwei,KANG Zhijiang.APPLICATION OF ARTIFICIAL NEURAL NETWORKS TO RESERVOIR DESCRIPTION[J].Petroleum Geology & Experiment,1999,21(2):166-169. |
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| Authors: | QIU Liwei KANG Zhijiang |
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| Affiliation: | Institute of petroleum, CNSPC, Beijing 100083, China |
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| Abstract: | The normal logging explaination methods based on experience formulas and the linear hypothesis show lower accuracy and successful rate. The artificial neural networks technique can adapt itself, learn itself. It has well prospect in logging explaination. This paper provides a case to illustrate the advantage of the artificial neural network technique in logging porosity explaination. |
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| Keywords: | artificial neural networks BP nets logging explaination porosity |
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