| 模糊贴近度在储层识别中的应用 |
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| 引用本文： | 冯国庆李允,谈德辉. 模糊贴近度在储层识别中的应用[J]. 西南石油大学学报(社会科学版), 2016, 21(4): 46-49. DOI: 10.3863/j.issn.1000-2634.1999.04.013 |
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| 作者姓名： | 冯国庆李允 谈德辉 |
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| 作者单位： | 1.西南石油学院研究生部,四川南充637001; 2.西南石油学院; 3.西南石油学院成人教育学院 |
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| 摘 要： | 为了克服测井解释中通常采用的最大隶属原则进行决策分析导致信息丢失所引起的判别结果的偏差,将模糊数学中的非对称贴近度分析法与神经网络结合起来,充分利用各分量信息建立了一种基于模糊贴近度的神经网络识别法。通过临盘油田实际资料解释表明,在储层识别中采用该方法可大大改善解释效果。
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| 关 键 词： | 模糊贴近度 神经网络 储层 识别 |
| 收稿时间： | 1998-11-03 |
APPLICATION OF FUZZY CLOSENESS DEGREE IN RESERVOIR RECOGNITION |
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| FENG Guo-qing LI Yun TAN De-hui. APPLICATION OF FUZZY CLOSENESS DEGREE IN RESERVOIR RECOGNITION[J]. Journal of Southwest Petroleum University(Social Sciences Edition), 2016, 21(4): 46-49. DOI: 10.3863/j.issn.1000-2634.1999.04.013 |
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| Authors: | FENG Guo-qing LI Yun TAN De-hui |
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| Affiliation: | Southwest Petroleum Inst |
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| Abstract: | A neural network recognition method is established based on fuzzy closeness degree by combination of non-symmetric closeness degree in mathematics and neural network to overcome deviated interpretation which is resulted from losing information when tactics analysis is conducted by the maximum belonging rules in well logging interpretation. Practical interpretation ofling pan oilfield indicates the method will greatly improve the effect of interpretation |
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| Keywords: | fuzzy closeness degree neural network reservoir recognition |
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