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中南大学学报(自然科学版)

Journal of Central South University

第46卷    第6期    总第250期    2015年6月

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文章编号:1672-7207(2015)06-2227-09
基于信息熵-模糊谱聚类的非均质碎屑岩储层孔隙结构分类
葛新民1, 2,范宜仁1, 2,唐利民3,陈义国4,齐林海5,邢帅6

(1. 中国石油大学 地球科学与技术学院,山东 青岛,266580;
2. 中国石油大学CNPC测井重点实验室,山东 青岛,266580;
3. 中国石油大庆油田井下作业分公司,黑龙江 大庆,163000;
4. 陕西延长石油(集团)有限责任公司研究院,陕西 西安,710075;
5. 中国石油大庆油田海拉尔石油勘探开发指挥部,黑龙江 大庆,163000;
6. 中国石油集团测井有限公司长庆事业部,陕西 西安,710201
)

摘 要: 提出基于信息熵-模糊谱聚类算法的孔隙结构自动分类技术,应用谱聚类算法解决凸分布聚类问题,实现全局收敛,有效避免“维数灾难”。根据信息熵理论对谱聚类算法中的尺度参数进行优化,得到孔隙结构类型。在此基础上,结合模糊数学算法得到每个样本对孔隙结构类型的隶属度,根据隶属度最优法则(样品对某一类孔隙结构的隶属度大于70%)确定不同样本所属孔隙结构类别。研究结果表明:该算法所得孔隙结构分类结果与试油、试采等生产测试结果十分吻合,工程应用效果十分明显。

 

关键字: 非均质碎屑岩;孔隙结构分类;模糊谱聚类算法;信息熵;尺度参数优化

Pore structure typing of heterogeneous clastic reservoir using information entropy-fuzzy spectral clustering algorithm
GE Xinmin1, 2, FAN Yiren1, 2, TANG Limin3, CHEN Yiguo4, QI Linhai5, XING Shuai6

1. School of Geosciences in China University of Petroleum, Qingdao 266580, China;
2. CNPC Key Well Logging Laboratory in China University of Petroleum, Qingdao 266580, China;
3. Down Hole Service Sub-Company of Daqing Oilfield Company, Daqing 163000, China;
4. Research Institute of Shanxi Yanchang Petroleum (Group) Co. Ltd., Xi’an 710075, China;
5. Hailar Headquaters of Petroleum Exploration and Development of Daqing Oil field Company, Daqing 163000, China;
6. Changqing Division, China Petroleum Logging Co. Ltd., Xi’an 710201, China

Abstract:A method of automatic typing was proposed by using information entropy-fuzzy spectral clustering algorithm. Complete convergence was obtained by using spectral clustering algorithm to solve the convex distribution clustering problem, thus the ‘dimension disaster’ was avoided effectively. In the light of information entropy theory, the scale parameters of spectral clustering algorithm were optimized and then the types of pore structures were presented. On this basis, in combination with each sample of the pore structure types of membership from fuzzy mathematics algorithm, various types of pore structure of different samples can be obtained according to the membership degree of optimal rule (membership degree of samples for one pore structure is greater than 70%). The results show that the results of pore structure typing obtained from the algorithm are in good agreement with well test and production test results, and its engineering application effect is very obvious.

 

Key words: heterogeneous clastic reservoir; pore structure typing; fuzzy spectral clustering algorithm; information entropy; scale parameter optimizing

中南大学学报(自然科学版)
  ISSN 1672-7207
CN 43-1426/N
ZDXZAC
中南大学学报(英文版)
  ISSN 2095-2899
CN 43-1516/TB
JCSTFT
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