摘要
由于其很好的自适应性和非线性映射能力,神经网络技术在石油领域得到了广泛的应用。结合模糊相关性分析和主成分分析的方法,利用改进的BP神经网络的方法,通过岩心和成像标定的常规测井数据实现对单井裂缝密度的识别,取得了很好的效果。
Because of its good adaptability and nonlinear mapping ability,neural network has been widely used in oil field.In this paper,combined with the fuzzy correlation analysis and principal component analysis method,the method of improved BP neural network,recognition of single well fracture density was realized based on conventional logging data,good results have been achieved.
出处
《当代化工》
CAS
2016年第9期2174-2175,2179,共3页
Contemporary Chemical Industry
关键词
BP神经网络
模糊相关性分析
主成分分析
测井
单井裂缝密度
BP neural network
fuzzy correlation analysis
principal component analysis
logging
single well fracture density
