| 应用人工神经网络技术预测曲流河砂体分布 |
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| 引用本文： | 杨凤丽 周祖翼. 应用人工神经网络技术预测曲流河砂体分布[J]. 同济大学学报(自然科学版), 1999, 27(1): 115-118 |
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| 作者姓名： | 杨凤丽 周祖翼 |
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| 作者单位： | 同济大学海洋地质与地球物理系!上海，200092，同济大学海洋地质与地球物理系!上海，200092，石油大学资源系!东营，257062，石油大学资源系!东营，257062 |
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| 摘 要： | 曲流河相沉积砂体由于其单层薄，横向上不稳定，变化大等特点，给实际的石油勘探开发和预测工作造成了很大的困难，根据某油田曲流河砂体的沉积特点，利用人工神经网络技术和多种地震特征参数信息，对曲流河砂体的横向分布进行了预测和评价，钻探结果表明，与实际情况吻合较好。
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| 关 键 词： | 曲流河砂体 人工神经网络 砂体预测 评价 |
Prediction of Meandering Stream Sandstone Bodies Using the Artificial Neural Network Technique |
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| Yang Fengli Zhou Zuyi. Prediction of Meandering Stream Sandstone Bodies Using the Artificial Neural Network Technique[J]. Journal of Tongji University(Natural Science), 1999, 27(1): 115-118 |
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| Authors: | Yang Fengli Zhou Zuyi |
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| Abstract: | The oil exploration, development and reservoir prediction for meandering stream sandstone bodies meet lots of difficulties because of their single thin layer, transverse instability and great variations. Based on their sedimentation characteristics, the artificial neural network technique is applied to predict the lateral distribution of meandering stream sandstone bodies and evaluate their petroleum prospects, using different types of seismic attributes. The drilling results show that the prediction results tally with the actual situation. |
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| Keywords: | Meandering stream sandstone bodies Back propagation neural networks Sandstone bodies prediction |
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