首页|西湖凹陷N构造花港组厚层砂泥岩地层测井岩性识别方法

西湖凹陷N构造花港组厚层砂泥岩地层测井岩性识别方法

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西湖凹陷位于东海,钻井取心比较困难,取心资料比较少,岩屑录井资料比较粗略,为了得到比较精细的地层岩性,在无监督机器学习的基础上,采用有监督机器学习的方法进行岩性识别.结果表明:该方法对研究区地层的岩性识别率可达 95%以上,能够快速准确地对目的层的岩性进行识别.
Lithology identification method of thick sand mudstone formation logging in Huagang Formation,N Structure,Xihu Sag
The West Lake Depression is located in the East China Sea,where drilling and coring are relatively difficult,with limited coring data and rough cuttings logging data.In order to obtain more precise formation lithology,a supervised machine learning method based on unsupervised machine learning is adopted for lithology identification.The results show that the method has a lithology recognition rate of over 95%for the strata in the study area,and can quickly and accurately identify the lithology of the target layer.

Xihu DepressionHuagang GroupLithological identificationMRGC clusteringSupport Vector Machine

靳九龙、杨斌、唐生寿、刘洪瑞、代兴宇、蒲金成

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成都理工大学 四川 成都 610059

西湖凹陷 花港组 岩性识别 多分辨率图形聚类 支持向量机

2024

石化技术
中国石化集团资产经营管理有限公司北京燕山石化工分公司

石化技术

影响因子:0.261
ISSN:1006-0235
年,卷(期):2024.31(8)