| 基于人工神经网络实现裂缝性储集层的测井识别 |
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| 引用本文： | 梁利喜,许强,刘向君. 基于人工神经网络实现裂缝性储集层的测井识别[J]. 新疆石油天然气, 2005, 1(3): 51-53 |
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| 作者姓名： | 梁利喜 许强 刘向君 |
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| 作者单位： | 1. 成都理工大学"地质灾害与地质环境保护"国家专业实验室,四川,成都,610059
2. 西南石油学院"油藏地质及开发工程"国家重点实验室,四川,成都,610500 |
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| 摘 要： | 裂缝识别是长期困扰裂缝油气藏勘探的难题之一，单纯依靠常规测井资料进行裂缝识别，存在主观不确定性及多解性；成像测井直观准确，但成本较高。本文基于人工神经网络理论，开展了常规测井资料识别评价裂缝性储层的研究。结果表明，基于人工神经网络的裂缝性储集层常规测井识别，具有较好的效果。
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| 关 键 词： | 裂缝识别 常规测井 人工神经网络 |
| 文章编号： | 1673-2677（2005）03-0051-03 |
| 收稿时间： | 2005-08-17 |
| 修稿时间： | 2005-08-17 |
THE CONVENTIONAL LOGGING IDENTIFICATION OF FRACTURED FORMATION WITH ARTIFICIAL NEURAL NETWORK |
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| Liang Li-xi,Xu Qiang,Liu Xiang-jun. THE CONVENTIONAL LOGGING IDENTIFICATION OF FRACTURED FORMATION WITH ARTIFICIAL NEURAL NETWORK[J]. Xinjiang Oil & Gas, 2005, 1(3): 51-53 |
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| Authors: | Liang Li-xi Xu Qiang Liu Xiang-jun |
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| Affiliation: | Liang Li-xi,Xu Qiang,Liu Xiang-jun,Chengdu University of Technology,State Specialty Laboratory of Geohazard Prevention and Geoenvironment Protection,Sichuan,Chengdu,610059 |
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| Abstract: | It is known that the identification of fractures is difficult during fractured reservoirs exploration.Only with conventional logging data,the result is uncertain.Though image logging is a good way,it is expensive.In this paper,identification of fractured formation is researched with conventional logging data based on artificial neural network.The results show that accuracy of this way is high. |
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| Keywords: | fractures identification conventional logging artificial neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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