神经网络模式识别沉积微相
Identification of Sedimentary Macrofacies with Neural Network
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摘要: 本文介绍用于沉积微相智能识别的神经网络模式识别方法。该方法利用关键并研究建立的测并相与地质相的对应关系作为识别模式，通过向识别模式学习获得模式识别智能知识，从而利用这些智能知识识别未知井、未知点的微相类型。本文方法成功地应用于中原油田文留地区沙四段海相的识别与划分。Abstract: This paper introduces an identification of sedimentary microfactes by the pattern recognition approach using neural network. The approach firstly established the relationship between the logging facies and geological facies according to the key-well study as an identified pattern,then obtained intelligent knowledge by learning from the identified pattern, and finally applied the knowledge to identify the microfacies in unknown wells and sites again. The approach was successfully applied in the recognition and subdivision of sedimentary microfacies of the 4th member of the Shahejie formation, Wenlin Area, Zhongyuan Oilfield.
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Key words:
- sedimentary microfacies /
- logging factes /
- pattern recognition /
- intelligent knowledge /
- neural network
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[1] 1.谈德辉.张微.电相研究.西南石油学院学报，1987(2).
2.廖明光，周南翔，谈德辉.模糊模式识别沉积微相.测井技术，1991(3).
3.殷勤业，杨宗凯，谈正.模式识别与神经网络.北京:机械工业出版社，1992.
4.Nielson R H. Theory of the Backpropagation Neural Network. Int. J, conf.on Neural Network. Washington1989. DC ,231一233.
5.Lippman R H. An Introduction to Compting with Neural Nets. IEEE Assp. 1987. 4:2-24. -
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