中国石油大学学报（自然科学版）2012，Vol.36Issue(1)：53-59,7.DOI:10.3969/j.issn.1673-5005.2012.01.009
基于核空间的模糊聚类方法在储层预测中的应用
Application of kernel fuzzy C-means method to reservoir prediction
摘要
Abstract
The kernel fuzzy C-means (FCM) method is a novel method for pattern recognition. The problems such as non-hyperspherical data and non-linear inter-class boundary are prevalent during seismic attributes clustering process, which could not be resolved effectively by traditional FCM method. The kernel function was introduced into traditional FCM method for these problems in reservoir prediction. The parameters including feature weights and fuzzy coefficient were optimized for different sensibility of seismic attributes, which could improve the effectiveness of this new kernel FCM method for reservoir prediction. The results of experiments on the artificial and real data show that the new kernel FCM method can describe the boundaries of gas-bearing carbonate reservoir more accurately.关键词
核空间/模糊聚类/地震属性/储层预测Key words
kernel space/ fuzzy clustering/ seismic attributes/ reservoir prediction分类
天文与地球科学引用本文复制引用
印兴耀,叶端南,张广智..基于核空间的模糊聚类方法在储层预测中的应用[J].中国石油大学学报（自然科学版）,2012,36(1):53-59,7.基金项目
国家油气重大专项课题(2011ZX05014-001-010HZ) （2011ZX05014-001-010HZ）
中国石油科技创新基金项目(2011D-5006-0301) （2011D-5006-0301）
中国石油大学(华东)自主创新科研计划项目(11CX05006A) （华东）
