石油地球物理勘探2024，Vol.59Issue(4)：865-874,10.DOI:10.13810/j.cnki.issn.1000-7210.2024.04.024
引导模糊C均值聚类算法在联合反演综合解释中的应用
Application of guided fuzzy C-means clustering algorithm in joint inversion comprehensive interpretation
摘要
Abstract
There are differences in the inversion results of different geophysical methods,and the key to obtain ing accurate underground knowledge is a final reasonable interpretation based on the joint inversion results of dif-ferent methods.A guided fuzzy C-means(FCM)clustering algorithm is proposed for this purpose,and based on the fuzzy C-means(FCM)clustering algorithm,this paper includes the existing geologic understanding,in-troduces prior constraint information to guide the determination of the clustering centers,and provides a compre-hensive quantitative interpretation of the results of the geophysical joint inversion,aiming at reducing the subjec-tivity and limitations of traditional manual interpretation.The model test shows that the guided FCM clustering technology is more effective than the traditional FCM clustering technologies,especially its ability to effectively distinguish different geological bodies when processing inversion data of complex geological structures.The re-sults of practical data applications demonstrate the great potential of the guided FCM clustering technology in the comprehensive interpretation of multi-attribute geophysical joint inversion results.This technology not only makes geophysical data interpretation more scientific but also provides a more reliable and accurate tool for un-derground resource exploration.关键词
模糊C均值聚类/联合反演/综合解释/先验约束信息/多属性Key words
fuzzy C-means(FCM)clustering/joint inversion/comprehensive interpretation/prior constraint in-formation/multi-attribute分类
天文与地球科学引用本文复制引用
陈易周,刘江,涂齐催,李炳颖,娄敏..引导模糊C均值聚类算法在联合反演综合解释中的应用[J].石油地球物理勘探,2024,59(4):865-874,10.基金项目
本项研究受中国海洋石油有限公司"十四五"重大科技项目"潜山油气成藏理论与勘探关键技术"(KJGG2022-0302)和"地层岩性油气藏高效识别与精细评价技术"(KJGG2022-0303)联合资助. （KJGG2022-0302）
