| 神经网络方法在储层孔隙度预测中的应用 |
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| 引用本文： | 李操,王继春.神经网络方法在储层孔隙度预测中的应用[J].内蒙古石油化工,2007(12). |
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| 作者姓名： | 李操 王继春 |
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| 作者单位： | 大庆油田有限责任公司勘探开发研究院 黑龙江大庆163712(李操)，辽河油田欢喜岭采油厂地质研究所 辽宁盘锦124114(王继春) |
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| 摘 要： | 储层参数预测对油田勘探具有重要意义。文章采用主成分变换优化法对海拉尔盆地某油田的11种地震属性进行标准化、主成分变换,计算结果说明,只需其中4种主成分用于储层预测。利用神经网络方法对储层孔隙度进行预测,预测结果与测井资料十分吻合,取得了较好的预测效果。
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| 关 键 词： | 孔隙度 储层预测 人工神经网络 地震属性 |
The Application of Reservoir Porosity Prediction Basing on Artificial Neural Network Method |
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| LI Cao,WANG Ji-chun.The Application of Reservoir Porosity Prediction Basing on Artificial Neural Network Method[J].Inner Mongulia Petrochemical Industry,2007(12). |
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| Authors: | LI Cao WANG Ji-chun |
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| Abstract: | It is very important to oilfield exploration that predicted reservoir parameter. In this paper the principal component transform method is used to standardize and transform the eleven seismic attributes in Hailaer Basin.The result of calculation indicated this reservoir prediction only need four principal component.The reservoir porosity is predicted by the artificial neural network method.The predicted result tallies with well log data and achieved good result. |
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| Keywords: | Porosity Reservoir Prediction Artificial Neural Network Seismic Attribute |
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