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利用测井资料自动识别藻灰岩
引用本文:张振城,孙建孟,马建海,张炜,苏远大. 利用测井资料自动识别藻灰岩[J]. 吉林大学学报(地球科学版), 2005, 35(3): 382-388
作者姓名:张振城  孙建孟  马建海  张炜  苏远大
作者单位:1.中国石油大学(华东) 地球资源与信息学院, 山东 东营 257061; 2.青海油田分公司, 甘肃 兰州 736202
基金项目:中国石油天然气集团公司资助项目
摘    要:藻灰岩在测井曲线图上具有不同于其它岩性的特征,据此确定了7种测井参数(自然伽玛、自然电位、井径、声波时差、补偿中子、补偿密度及深电阻率),将测井数据归一化后得到了相应的岩性判别样本参数。利用F-Means中速度较快的聚类迭代(LBG)算法对研究样本进行分类,优选了一组数据用于判别分析。在进行Q因子分析的基础上建立了用于岩性判别的3个判别函数,并对花土沟油田某井段进行了岩性识别预测分析。

关 键 词:藻灰岩  归一化  聚类迭代  岩性判别  
文章编号:1671-5888(2005)03-0382-07
收稿时间:2004-08-02
修稿时间:2004-08-02

Automatic Identification of Algae Limestone with Well Logging Data
ZHANG Zhen-cheng,SUN Jian-meng,MA Jian-hai,ZHANG Wei,SU Yuan-da. Automatic Identification of Algae Limestone with Well Logging Data[J]. Journal of Jilin Unviersity:Earth Science Edition, 2005, 35(3): 382-388
Authors:ZHANG Zhen-cheng  SUN Jian-meng  MA Jian-hai  ZHANG Wei  SU Yuan-da
Affiliation:1.Faculty of Geo Resource and Information,University of Petroleum, China, Dongying 257061,China;2.Qinghai Oilfield,Lanzhou 736202,China
Abstract:Algae limestone represents different characteristics in the plot of well logging. Accordingly seven parameters(GR,SP,CAL,AC,CNL,DEN,RT) selected from well logging data are standardized to form sample parameters for lithologic identification. The LBG(Linde-Buzo-Gray) algorithms in F-means cluster is used to classify the samples, a set of data is then selected for the identification and analysis. Based on Q gene analysis, three identification functions have been obtained and used in lithologic identification and prediction in terms of well logging data of Huatugou oilfield. The method is fast and efficient in identifying algae limestone based on well logging data.
Keywords:algae limestone  digitalized  LBG algorithms  lithologic identification
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