摘要
从神经网络的机理、特点出发,探讨了采用神经网络技术进行测井岩性识别的可行性及优越性,并以十红滩地区的找矿目的层为对象,进行了岩性分析与对比,为该方法的进一步应用开拓了前景。
Starting with the mechanism and characteristics of neural networks, the authors discussed the risibility and superior to identify the lithology with artificial neural networks. Lithology identification of the third lithological member (the main set of uranium ore body occuring) of Shihongtan uranium deposit with this methods are consistent with real documentation, which indicate that the new method is practical on lithology identification for sandstone and can be used in uranium resource prospecting and exploration.
出处
《铀矿地质》
CAS
CSCD
2009年第4期236-239,256,共5页
Uranium Geology
关键词
人工神经网络
B—P算法
样本
岩性识别
artificial neural networks
B-P algorithm
sample
lithology identification