Lithologic Reservoirs ›› 2017, Vol. 29 ›› Issue (5): 127-133.doi: 10.3969/j.issn.1673-8926.2017.05.015

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Lithology identification based on principal component analysis and fuzzy recognition

MAZheng1, ZHANG Chunlei2, GAO Shichen1   

  1. 1. School of Science, China University of Geosciences, Beijing 100083, China;
    2. Beijing Zhongdirunde Petroleum Technology Co. Ltd, Beijing 100083, China
  • Received:2017-04-30 Revised:2017-07-14 Online:2017-09-21 Published:2017-09-21

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Abstract: It is not ideal that characterization the complex lithology is disturbed by logging curves,which are redundancies in high similarity logging parameters. Based on principal component analysis(PCA) and fuzzy recognition, to solve this problem,a method was adopt to identify the complex lithology,and verified by carbonate rocks logging data of from fifth member of Majiagou Formation in Sudong 41-33 blocks of Sulige gasfileld. The complex lithology identification methods chose six logging curves of AC,GR,Pe,CNL,DEN,RLLD firstly,which are sensitive to lithology change,then construct three comprehensive variables Y1,Y2,Y3 by principal component analysis,and finally identify lithology by fuzzy recognition method. Compared with traditional identification methods,the method eliminate the fuzziness and correlation effectively,and the accuracy rate is reached up to 86%. It is a practical and effective method of complex lithology identification,and has certain popularization and application value.

Key words: fuzzy recognition, principal component analysis, lithology identification, well logging curve, Sulige gasfilelds

CLC Number: 

  • P618.13
[1] 佘刚,马丽娟,徐永发,等. 油砂储层特征及测井评价方法研究——以柴达木盆地干柴沟地区为例. 岩性油气藏,2015,27(6):119-124. SHE G,MA L J,XU Y F,et al. Reservoir characteristics of oil sands and logging evaluation methods:a case study from Ganchaigouarea, Qaidam Basin. Lithologic Rservoirs,2015,27(6):119-124.
[2] 包强,张婷,张晓东,等. 岩石相测井识别技术在阿姆河右岸A区的应用.天然气工业,2013,33(11):51-55. BAO Q,ZHANG T,ZHANG X D,et al. Application of logging lithofacies identification technology in block A of the Right Bank of the Amu-Darya River. Natural Gas Industry, 2013,33(11):51-55.
[3] 张大权,邹妞妞,姜杨,等. 火山岩岩性测井识别方法研究——以准噶尔盆地火山岩为例. 岩性油气藏,2015,27(1):108-114. ZHANG D Q,ZOU N N,JIANG Y,et al. Logging identification method of volcanic rock lithology:a case study from volcanic rock in Junggar Basin. Lithologic Rservoirs,2015,27(1):108-114.
[4] 王庆如,李敬功. 碳酸盐岩气藏储量参数测井评价方法. 岩性油气藏,2013,25(6):98-102. WANG Q R,LI J G. Logging evaluation method of reserve parameters of carbonate gas reservoir. Lithologic Rservoirs,2013, 25(6):98-102.
[5] BALDWIN J L,BATEMAN R M,WHEATLEY C L. Application of a neural network to the problem of mineral identification from well logs. Log Analyst,1990,3(5):279-293.
[6] 单敬福,陈欣欣,赵忠军,等. 利用BP神经网络法对致密砂岩气藏储集层复杂岩性的识别. 地球物理学进展,2015,30(3):1257-1263. SHAN J F,CHEN X X,ZHAO Z J,et al. Identification of complex lithology for tight sandstone gas reservoirs sase on BP neural net. Progress in Geophysics,2015,30(3):1257-1263.
[7] 张国英,王娜娜,张润生. 基于主成分分析的BP神经网络在岩性识别中的应用. 北京石油化工学院学报,2008,16(3):43-46. ZHANG G Y,WANG N N,ZHANG R S. Application of principal component analysis and BP neural network in identifying lithology. Journal of Beijing Institute of Petro-chemical Technology, 2008,16(3):43-46.
[8] AL-ANAZI A,GATES I D. On the capability of support vector machines to classify lithology from well logs. Natural Resources Research,2010,19(2):125-139.
[9] 于代国,孙建孟,王焕增,等. 测井识别岩性新方法——支持向量机方法.大庆石油地质与开发,2005,24(5):93-95. YU D G,SUN J M,WANG H Z,et al. A new method for logging lithology identification-SVM. Petroleum Geology & Oilfield Development in Daqing,2005,24(5):93-95.
[10] 胡红,曾恒英,梁海波,等. 基于主成分分析和学习矢量化的神经网络岩性识别方法.测井技术,2015,39(5):586-590. HU H,ZENG H Y,LIANG H B,et al. Lithology identification based on principal component analysis and learning vector quantization neural network. Well Logging Technology,2015, 39(5):586-590.
[11] 杨兆栓,林畅松,尹宏,等. 主成分分析在塔中地区奥陶系鹰山组碳酸盐岩岩性识别中的应用. 天然气地球科学,2015,26(1):54-59. YANG Z S,LIN C S,YIN H,et al. Application of principal component analysis in carbonate lithology identification of the Ordovician Yingshan formation in Tazhong area. Natural Gas Geoscience,2015,26(1):54-59.
[12] 刘璐,吴成茂. 模糊局部均值聚类分割法改进及其应用. 计算机工程与设计,2015,36(12):3365-3369. LIU L,WU C M. Improvement and application of fuzzy local mean clustering segmentation method.Computer Engineering and Design,2015,36(12):3365-3369.
[13] 李洁,高新波,焦李成. 基于特征加权的模糊聚类新算法. 电子学报,2006,34(1):89-92. LI J,GAO X B,JIAO L C. A new feature weighted fuzzy clustering algorithm. Chinese Journal of Electronics,2006,34(1):89-92.
[14] PROVOROVA I,PARSHUTIN S,PROVOROVS S. Usin genetic algorithm to optimize weights in data mining task. Scientific Journal of Riga Technical University,Computer Sciences,2009, 40(1):123-128.
[15] 张涛,莫修文. 基于交会图与模糊聚类算法的复杂岩性识别. 吉林大学学报(地球科学版),2007,37(增刊1):109-113. ZHANG T,MO X W. Complex lithologic identification based on cross plot and fuzzy clustering algorithm. Journal of Jilin University(Earth Science Edition),2007,37(Suppl 1):109-113.
[16] DUBOIS M K,BOHLING G C,CHAKRABARTI S. Comparison of four approaches to a rock facies classification problem. Computers and Geosciences,2007,33(5):599-617.
[17] 王瑞,朱筱敏,王礼常. 用数据挖掘方法识别碳酸盐岩岩性. 测井技术,2012,36(2):197-201. WANG R,ZHU X M,WANG L C. Using data mining to identify carbonate lithology. Well Logging Technology,2012,36(2):197-201.
[18] HSIE B Z,LEWIS C,LIN Z S. Lithology identification of aquifers from geophysical well logs and fuzzy logic analysis:Shuilin area,Taiwan. Computers & Geosciences,2005,31(3):263-275.
[19] DONG S,WANG Z,ZENG L. Lithology identification using kernel Fisher discriminant analysis with well logs. Journal of Petroleum Science and Engineering,2016,143:95-102.
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