DETERMINATION OF LITHOLOGY FROM WELL LOGS USING A NEURAL NETWORK

被引:3
|
作者
ROGERS, SJ [1 ]
FANG, JH [1 ]
KARR, CL [1 ]
STANLEY, DA [1 ]
机构
[1] US BUR MINES,TUSCALOOSA,AL 35486
来源
AAPG BULLETIN-AMERICAN ASSOCIATION OF PETROLEUM GEOLOGISTS | 1992年 / 76卷 / 05期
关键词
D O I
暂无
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
We have developed a computer program to automatically determine lithologies from well logs using a back-propagation neural network. Unlike a conventional serial computer, a neural network is a computational system composed of nodes (sometimes called neurons, neurodes or units) and the connections between these nodes. Neural computing attempts to emulate the functions of the mammalian brain, thus mimicking thought processes. The neural network approach differs from previous pattern recognition methods in its ability to "learn" from examples. Unlike conventional statistical methods, this new approach does not require sophisticated mathematics and a large amount of statistical data. This paper discusses the application of neural networks to a pattern recognition problem in geology: the determination of lithology from well logs, the neural network determined the lithology from well logs. The neural network determined the lithologies (limestone, dolomite, sandstone, shale, sandy and dolomitic limestones, sandy dolomite, and shale sandstone) from selected well logs in a fraction of the time required by an experienced human log analyst.
引用
收藏
页码:731 / 739
页数:9
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