Journal of Jilin University(Earth Science Edition) ›› 2017, Vol. 47 ›› Issue (4): 1319-1330.doi: 10.13278/j.cnki.jjuese.201704307

Previous Articles    

Application of PPC Model Combined with RCGA to Identify and Extract Geochemical Anomaly

Xiao Fan1,2, Chen Jianguo3,4   

  1. 1. School of Earth Science and Engineering, Sun Yat-sen University, Guangzhou 510275, China;
    2. Guangdong Key Laboratory of Geological Process and Mineral Resources Exploration, Sun Yat-sen University, Guangzhou 510275, China;
    3. Resources Faculty, China University of Geosciences, Wuhan 430074, China;
    4. State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan 430074, China
  • Received:2016-12-12 Online:2017-07-26 Published:2017-07-26
  • Supported by:
    Supported by the National Natural Science Foundation of China (41502310) and the Guangdong Natural Science Foundation (2015A030310246)

Abstract: In order to identify and extract geochemical anomalies, a novel method, which combines projection pursuit classification (PPC), a dimension-reducing technology on high-dimensional data, with the real coded genetic algorithm (RCGA), has been proposed in this paper. We analyzed and discussed the key technological issues in geochemical anomaly identification and extraction using RCGA-PPC model based on the features of geochemical data. At the same time, an application software package was developed for the RCGA-PPC model on MATLAB. As a case study, stream sediment geochemical data in Gejiu, Yunnan, China, were tested with the RCGA-PPC model and Sn, Cu, Pb, Zn, As, Cd, etc. ore forming or/and mineralization associate elements were selected as the variables to recognize anomalies. The results show that most of the local higher optimal projection values are well coincident with the deposits location. Therefore, it can be concluded that RCGA-PPC model could be a useful method for geochemical anomaly identification and extraction.

Key words: projection pursuit classification, real coded genetic algorithm, geochemical data processing, anomaly identification and extraction, Gejiu, Yunnan

CLC Number: 

  • P631.8
[1] David M, Campiglio C, Darling R. Progress in R- and Q-Mode Analysis: Correspondence Analysis and Its Application to the Study of Geological Processes[J]. Canadian Journal of Earth Sciences, 1974, 13(1): 131-146.
[2] Armour B A, Olesen B L. Condensing Multi-Element Reconnaissance Geochemical Data from South Greenland Using Empirical Discriminant Analysis[J]. Journal of Geochemical Exploration, 1984, 21(1/2/3): 395-404.
[3] Castillo M R, Howarth R J. Application of the Empirical Discriminant Function to Regional Geochemical Data from the United Kingdom[J]. Geological Society of America, 1976, 87(11): 1567-1581.
[4] 黄意信. 相似性判别分析方法[J]. 地质与勘探, 1975, 8: 56-68. Huang Yixin. The Discriminant Analysis Method Based on Similarity[J]. Geology and Prospecting, 1975, 8: 56-68.
[5] 赵鹏大, 胡旺亮, 李紫金. 矿床统计预测[M]. 北京: 地质出版社, 1994. Zhao Pengda, Hu Wangliang, Li Zijin. Statistical Prediction for Mineral Deposits[M]. Beijing: Geological Publishing House, 1994.
[6] 罗长清. 聚类分析在某地化探异常评价中的应用效果[J]. 物化探计算技术, 1984, 6(1): 77-80. Luo Changqing. Application of the Cluster Analysis to the Evaluation of the Geochemical Prospecting Anomalies[J]. Computation Techniques for Geophysical and Geochemical Exploration, 1984, 6(1): 77-80.
[7] Ji H J, Zeng D M, Shi Y X, et al. Semi-Hierarchical Correspondence Cluster Analysis and Regional Geochemical Pattern Recognition[J]. Journal of Geochemical Exploration, 2007, 93(2): 109-119.
[8] 陈永良, 李学斌. 基于核函数理论的系统聚类分析[J]. 吉林大学学报(地球科学版), 2010, 40(5): 1211-1216. Chen Yongliang, Li Xuebin. Kernel-Based Hierarchical Cluster Analysis[J]. Journal of Jilin University (Earth Science Edition), 2010, 40(5): 1211-1216.
[9] 陈永良, 路来君, 李学斌. 多元地球化学异常识别的核马氏距离方法[J]. 吉林大学学报(地球科学版), 2014, 44(1): 396-408. Chen Yongliang, Lu Laijun, Li Xuebin. Kernel Mahalanobis Distance for Multivariate Geochemical Anomaly Recognition[J]. Journal of Jilin University (Earth Science Edition), 2014, 44(1): 396-408.
[10] Gordon A D. A Review of Hierarchical Classification[J]. Journal of the Royal Statistical Society, 1987, 150(2): 119-137.
[11] Cormack R M. A Review of Classification[J]. Journal of the Royal Statistical Society, 1971, 134(3): 321-367.
[12] Hartigan J A, Wong M A. A K-Means Clustering Algorithm[J]. Journal of the Royal Statistical Society, 1979, 28(1): 100-108.
[13] Cheng Q M, Agterberg F P, Ballantyne S B. The Separation of Geochemical Anomalies from Background by Fractal Methods[J]. Journal of Geochemical Exploration, 1994, 51(2): 109-130.
[14] 成秋明. 多维分形理论和地球化学元素分布规律[J]. 地球科学:中国地质大学学报, 2000, 25(3): 311-318. Cheng Qiuming. Multifractal Theory and Geochemical Element Distribution Pattern[J]. Earth Science: Journal of China University of Geosciences, 2000, 25(3): 311-318.
[15] Xiao F, Chen J G. Fractal Projection Pursuit Classification Model Applied to Geochemical Survey Data[J]. Computers & Geosciences, 2012, 45: 75-81.
[16] Zhang L P, Bai G P, Xu Y X. A Wavelet-Analysis-Based New Approach for Interference Elimination in Geochemical Hydrocarbon Exploration[J]. Mathematical Geology, 2003, 35(8): 939-952.
[17] Su S, Mcardle B H, Rodgers K A, et al. Wavelet Analysis of Variations in Geochemical and Microfossil Data Across the Cretaceous/Tertiary Boundary at Flaxbourne River, New Zealand[J]. New Zealand Journal of Geology and Geophysics, 2003, 46(2): 199-208.
[18] Zhang L P, Ruan T J. Application of Wavelet Analysis to Interference Elimination for Geochemical Hydrocarbon Exploration[J]. Journal of China University of Geosciences, 2000, 11(1): 89-91.
[19] 黄厚辉, 郭科, 唐菊兴. 基于小波多尺度分析的异常下限确定方法[J]. 地质找矿论丛, 2007, 22(4): 311-313, 320. Huang Houhui, Guo Ke, Tang Juxing. The Wavelet Theory-Based Multi-Scale Analysis Method to Determine the Lower Limit of Element Geochemical Anomalies[J]. Contributions to Geology and Mineral Resources Research, 2007, 22(4): 311-313, 320.
[20] 陈建国, 夏庆霖. 利用小波分析提取深层次物化探异常信息[J]. 地球科学:中国地质大学学报, 1999, 24(5): 509-512. Chen Jianguo, Xia Qinglin. Wavelet-Based Extraction of Geophysical and Geochemical Anomaly Information[J]. Earth Science: Journal of China University of Geosciences, 1999, 24(5): 509-512.
[21] 李庆谋, 成秋明. 分形奇异(特征)值分解方法与地球物理和地球化学异常重建[J]. 地球科学:中国地质大学学报, 2004, 29(1): 109-118. Li Qingmou, Cheng Qiuming. Fractal Singular-Value (Egin-Value) Decomposition Method for Geophysical and Geochemical Anomaly Reconstruction[J]. Earth Science: Journal of China University of Geosciences, 2004, 29(1): 109-118.
[22] Cheng Q M. Mapping Singularities with Stream Sediment Geochemical Data for Prediction of Undiscovered Mineral Deposits in Gejiu, Yunnan Province, China[J]. Ore Geology Reviews, 2007, 32(1): 314-324.
[23] Cheng Q M, Agterberg F P. Singularity Analysis of Ore-Mineral and Toxic Trace Elements in Stream Sediments[J]. Computers & Geosciences, 2009, 35(2): 234-244.
[24] 成秋明. 多重分形与地质统计学方法用于勘查地球化学异常空间结构和奇异性分析[J]. 地球科学:中国地质大学学报, 2001, 26(2): 161-166. Cheng Qiuming. Multifractal and Geostatistic Methods for Characterizing Local Structure and Singularity Properties of Exploration Geochemical Anomalies[J]. Earth Science: Journal of China University of Geosciences, 2001, 26(2): 161-166.
[25] 陈志军. 多重分形局部奇异性分析方法及其在矿产资源信息提取中的应用[D]. 武汉: 中国地质大学, 2007. Chen Zhijun. Multifractal Theory Based Local Singularity Analysis Method and Its Application in Spatial Information Extraction for Mineral Exploration[D]. Wuhan: China University of Geosciences, 2007.
[26] Xiao F, Chen J G, Zhang Z Y, et al. Singularity Mapping and Spatially Weighted Principal Component Analysis to Identify Geochemical Anomalies Associated with Ag and Pb-Zn Polymetallic Mineralization in Northwest Zhejiang, China[J]. Journal of Geochemical Exploration, 2012, 122: 90-100.
[27] Xiao F, Chen J G, Agterberg F P, et al. Element Behavior Analysis and Its Implications for Geochemical Anomaly Identification: A Case Study for Porphyry Cu-Mo Deposits in Eastern Tianshan, China[J]. Journal of Geochemical Exploration, 2014, 145: 1-11.
[28] Xie S Y, Cheng Q M, Ke X Z, et al. Identification of Geochemical Anomaly by Multifractal Analysis[J]. Journal of China University of Geosciences, 2008, 19(4): 334-342.
[29] 张生元, 黄锐, 徐德义, 等. 非负矩阵分解方法在水系沉积物地球化学数据处理中应用[J]. 地球科学:中国地质大学学报, 2009, 34(2): 347-352. Zhang Shengyuan, Huang Rui, Xu Deyi, et al. Application of Non-Negative Matrix Factorization in Stream Sediment Geochemical Data Processing[J]. Earth Science: Journal of China University of Geosciences, 2009, 34(2): 347-352.
[30] Heslop D, Dobeneck T V, Höcker M. Using Non-Negative Matrix Factorization in The "Unmixing" of Diffuse Reflectance Spectra[J]. Marine Geology, 2007, 241(1): 63-78.
[31] 陈建国, 肖凡, 陈志军, 等. 希尔伯特-黄变换与独立分量分析在深层次找矿信息提取中的应用[C]//地球资源环境定量化理论与应用. 广州: 中山大学, 2009: 195. Chen Jianguo, Xiao Fan, Chen Zhijun, et al. Hilbert-Huang Transformation and Independent Component Analysis Applied in Deep Mineralization Associated Geoinformation Extraction[C]//Quantitative Theory and Applications for Earth Resources and Environment. Guangzhou: Sun Yat-sen University, 2009: 195.
[32] 连盈盈. 盲提取在地球化学异常识别中的应用[D]. 成都: 成都理工大学, 2009. Lian Yingying. BSE Applied to Distinguish Geochemical Anomaly from Background[D]. Chengdu: Chengdu University of Technology, 2009.
[33] Jimenez L O, Landgrebe D A. High Dimensional Feature Reduction Via Projection Pursuit[C]//Geoscience and Remote Sensing Symposium, 1994. California: IEEE, 1995: 1145-1147.
[34] Friedman J H. Exploratory Projection Pursuit[J]. Journal of the American Statistical Association, 1987, 82(1): 249-266.
[35] 付强, 赵小勇. 投影寻踪模型原理及其应用[M]. 北京: 科学出版社, 2006. Fu Qiang, Zhao Xiaoyong. The Principles and Applications of Project Pursuit Model[M]. Beijing: Science Press, 2006.
[36] Friedman J H, Stuetzle W, Schroeder A. Projection Pursuit Density Estimation[J]. Journal of the American Statistical Association, 1984, 79(387): 599-608.
[37] Huber B P. Projection Pursuit[J]. The Annals Statistics, 1985, 13(2): 435-475.
[38] Flick T E, Jones L K, Priest R G, et al. Pattern Classification Using Projection Pursuit[J]. Pattern Recognition, 1990, 23(12): 1367-1376.
[39] Friedman J H, Tukey J W. A Projection Pursuit Algorithm for Exploratory Data Analysis[J]. IEE Transactions on Computers, 1974, 23(9): 881-890.
[40] Friedman J H. A Recursive Partitioning Decision Rule for Nonparametric Classification[J]. IEEE Transactions on Computers, 1977, 26(4): 404-408.
[41] Jimenez L O, Landgrebe D A. Hyperspectral Data Analysis and Supervised Feature Reduction via Projection Pursuit[J]. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(6): 2653-2667.
[42] Jimenez L O, Landgrebe D A. Unsupervised Classification in High Dimensional Space: Geometrical, Statistical, and Asymptotical Properties of Multivariate Data[J]. IEEE Transactions on System Man and Cybernetics: Part C:Applications and Reviews, 1998, 28(1): 39-54.
[43] Lee E, Cook D, Klinke S, et al. Projection Pursuit for Exploratory Supervised Classification[J]. Journal of Computational and Graphical Statistics, 2005, 14(4): 831-846.
[44] Fu Q, Fu H. Application of PPE Model Based on RAGA in the Investment Decision-Making of Water Saving Irrigation Project[J]. Nature and Science, 2003, 1(1): 57-61.
[45] 肖长来, 危润初, 梁秀娟, 等. 基于投影寻踪聚类模型的龙坑水源地地下水水质评价[J]. 吉林大学学报(地球科学版), 2011, 41(增刊1): 248-252. Xiao Changlai, Wei Runchu, Liang Xiujuan, et al. Assessment of Water Quality of Groundwater in Longkeng Based on Projection Pursuit Cluster Model[J]. Journal of Jilin University (Earth Science Edition), 2011, 41(Sup.1): 248-252.
[46] Fu Q, Zu W. Study on PPE Model Based on RAGA to Evaluation the Water Quality[J]. Nature and Science, 2004, 2(4): 8-34.
[47] 王顺久. 水资源开发利用综合研究[D]. 成都: 四川大学, 2003. Wang Shunjiu. Research on the Utilization of Water Resources[D]. Chengdu: Sichuan University, 2003.
[48] Wang S J, Yang Z F, Ding J. Projection Pursuit Cluster Model and Its Application in Water Quality Assessment[J]. Journal of Environmental Sciences, 2004, 16(6): 994-995.
[49] Zhang C, Dong S. A New Water Quality Assessment Model Based on Projection Pursuit Technique[J]. Journal of Environmental Sciences, 2009, 21(Sup.1): S154-S157.
[50] 舒栋才, 樊明兰, 林三益. 基于免疫进化算法的投影寻踪聚类及其在地下水动态分类中的应用[J]. 四川大学学报(工程科学版), 2004, 36(1): 15-18. Shu Dongcai, Fan Minglan, Lin Sanyi. Applying Projection Pursuit Cluster Based on Immune Evolutionary Algorithmin Groundwater Regime Classification[J]. Journal of Sichuan University (Engineering Science Edition), 2004, 36(1): 15-18.
[51] 付强, 金菊良, 梁川. 基于实码加速遗传算法的投影寻踪分类模型在水稻灌溉制度优化中的应用[J]. 水利学报, 2002, 33(10): 39-45. Fu Qiang, Jin Juliang, Liang Chuan. Application of Projection Pursuit Model to Optimize Paddy Irrigation Schedule[J]. Shuili Xuebao, 2002, 33(10): 39-45.
[52] 张军, 梁川, 赵燮京, 等. 基于RAGA的PPC模型在节水灌溉多方案择优中的应用[J]. 中国农村水利水电, 2006, 12: 13-15. Zhang Jun, Liang Chuan, Zhao Xiejing, et al. Application of PPC Model Based on RAGA in the Water-Saving Irrigation Scheme Selection[J]. China Rural Water and Hydropower, 2006, 12: 13-15.
[53] Trizna D B, Bachmann C, Sletten M, et al. Projection Pursuit Classification of Multiband Polarimetric SAR Land Images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(11): 2380-2386.
[54] Chiang S S, Chang C I, Ginsberg I W. Unsupervised Target Detection in Hyperspectral Mages Using Projection Pursuit[J]. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(7): 1380-1391.
[55] Ifarraguerri A, Chang C I. Unsupervised Hyperspe-ctral Image Analysis with Projection Pursuit[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(6): 2529-2538.
[56] 林伟, 田铮. 极化SAR图像的聚类序列投影寻踪模型方法[J]. 电波科学学报, 2006, 21(5): 682-686. Lin Wei, Tian Zheng. Sequential Projection Pursuit Clustering Model for POL-SAR Data Unsupervised Classification[J]. Chinese Journal of Radio Science, 2006, 21(5): 682-686.
[57] 谷复光, 王清, 张晨. 基于投影寻踪与可拓学方法的泥石流危险度评价[J]. 吉林大学学报(地球科学版), 2010, 40(2): 373-377. Gu Fuguang, Wang Qing, Zhang Chen. Debris Flow Risk Assessment by PPC and Extenics[J]. Journal of Jilin University (Earth Science Edition), 2010, 40(2): 373-377.
[58] 倪长健, 王顺久, 丁晶. 边坡稳定性评价的投影寻踪聚类模型[J]. 岩石力学与工程学报, 2004, 23(16): 2687-2689. Ni Changjian, Wang Shunjiu, Ding Jing. Projection Pursuit Cluster Model for Slope Stability Evaluation[J]. Chinese Journal of Rock Mechanics and Engineering, 2004, 23(16): 2687-2689.
[59] 王园, 王沁, 何蕴龙, 等. 西安地裂与地面沉降灾害投影寻踪分析预测[J]. 工程地质学报, 1999, 7(1): 30-34. Wang Yuan, Wang Qin, He Yunlong, et al. Analysis and Prediction of Ground Fractures and Surface Subsidence Hazard in Xi’an City Using Projection Tracing[J]. Journal of Engineering Geology, 1999, 7(1): 30-34.
[60] 王琼, 朱令人. 投影寻踪聚类在新疆地震预报中的应用[J]. 内陆地震, 2005, 19(1): 8-15. Wang Qiong, Zhu Lingren. Application of the Projection Pursuit Cluster on the Earthquake Prediction in Xinjiang[J]. Inland Earthquake, 2005, 19(1): 8-15.
[61] Jiang F Z, Yang X F. The Application of Projection Pursuit Classification in the Process of Strategy Selection and Evaluation Based on the Real Coded Accelerating Genetic Algorithm[J]. Chinese Business Review, 2008, 7(1): 41-45.
[62] 舒栋才. 基于免疫进化算法的投影寻踪聚类在公司债券财务质量评级中的应用[J]. 计算机工程与应用, 2004, 40(15): 226-229. Shu Dongcai. Applying PPC based on IEA in Enterprises Bond Financial Quality Evaluation Grading[J]. Computer Engineering and Applications, 2004, 40(15): 226-229.
[63] Demirci O, Clark V P, Calhoun V D. A Projection Pursuit Algorithm to Classify Individuals Using FMRI Data: Application to Schizophrenia[J]. NeuroImage, 2008, 39(4): 1774-1782.
[64] 周明, 孙树栋. 遗传算法原理及其应用[M]. 北京: 国防工业出版社, 2000. Zhou Ming, Sun Shudong. The Principles and Applications of Genetic Algorithms[M]. Beijing: National Defense Industry Press, 2000.
[65] Munteanu C, Lazarescu V. Improving Mutation Capabilities in a Real-Coded Genetic Algorithm[C]//Proceedings of the First European Workshops on Evolutionary Image Analysis, Signal Processing and Telecommunications. Sweden: Springer-Verlag, 1999: 138-149.
[66] Kaelo P, Ali M M. Integrated Crossover Rules in Real Coded Genetic Algorithms[J]. European Journal of Operational Research, 2007, 176(1): 60-76.
[67] Deep K, Thakur M. A New Crossover Operator for Real Coded Genetic Algorithms[J]. Applied Mathematics and Computation, 2007, 188(1): 895-911.
[68] Blanco A, Delgado M, Pegalajar M C. A Real-Coded Genetic Algorithm for Training Recurrent Neural Networks[J]. Neural Networks, 2001, 14(1): 93-105.
[69] Deep K, Thakur M. A New Mutation Operator for Real Coded Genetic Algorithms[J]. Applied Mathematics and Computation, 2007, 193(1): 211-230.
[70] Ha J, Kung Y, Fung R, et al. A Comparison of Fitness Functions for the Identification of a Piezoelectric Hysteretic Actuator Based on the Real-Coded Genetic Algorithm[J]. Sensors and Actuators A: Physical, 2006, 132(2): 643-650.
[71] Fu Q, Xie Y G, Wei Z M. Application of Projection Pursuit Evaluation Model Based on Real-Code Acceleration Genetic Algorithm in Evaluation Wetland Soil Quality Variations in the Sanjiang, China[J]. Pedosphere, 2003, 13(3): 249-256.
[72] 成秋明, 赵鹏大, 陈建国, 等. 奇异性理论在个旧锡铜矿产资源预测中的应用:成矿弱信息提取和复合信息分解[J]. 地球科学:中国地质大学学报, 2009, 34(2): 232-242. Cheng Qiuming, Zhao Pengda, Chen Jianguo, et al. Application of Singularity Theory in Prediction of Tin and Copper Mineral Deposits in Gejiu District, Yunnan, China: Weak Information Extraction and Mixing Information Decomposition[J]. Earth Science: Journal of China University of Geosciences, 2009, 34(2): 232-242.
[73] 薛传东. 个旧超大型锡铜多金属矿床时空结构模型[D]. 昆明: 昆明理工大学, 2002. Xue Chuandong. The Space-Time Structure Model of the Gejiu Superlarge Tin-Copper-Polymetallic Deposit[D]. Kunming: Kunming University of Science and Technology, 2002.
[74] 陈守余, 赵鹏大, 张寿庭, 等. 个旧超大型锡铜多金属矿床成矿多样性与深部找矿[J]. 地球科学:中国地质大学学报, 2009, 34(2): 319-324. Chen Shouyu, Zhao Pengda, Zhang Shouting, et al. Mineralizing Multiformity and Deep Prospecting of Gejiu Super Sn-Cu Multi-metal Deposit, Yunnan, China[J]. Earth Science: Journal of China University of Geosciences, 2009, 34(2): 319-324.
[75] 徐启东, 夏庆霖, 成秋明. 云南个旧矿集区区域构造-岩浆演化与锡铜多金属成矿系统[J]. 地球科学:中国地质大学学报, 2009, 34(2): 307-313. Xu Qidong, Xia Qinglin, Cheng Qiuming. Tectonic-Magmatic Evolution Related to Metallogenic System in Gejiu Ore-Concentration Area, Southeast Yunnan of China[J]. Earth Science: Journal of China University of Geosciences, 2009, 34(2): 307-313.
[76] 贾润幸. 云南个旧锡矿集中区地质地球化学研究[D]. 西安: 西北大学, 2005. Jia Yunxing. The Geological and Geochemical Research on Gejiu Tin-Polymetallic District, Yunan[D]. Xi'an: Northwest University, 2005.
[77] 秦德先, 黎应书, 范柱国, 等. 个旧锡矿地球化学及成矿作用演化[J]. 中国工程科学, 2006, 8(1): 30-39. Qin Dexian, Li Yingshu, Fan Zhuguo, et al. The Geochemistry and Mineralization Evolvement of Gejiu Tin Ore Deposits[J]. Engineering Science, 2006, 8(1): 30-39.
[78] 肖凡. 基于RAGA的PPC模型在个旧化探资料处理中的应用研究[D]. 武汉: 中国地质大学, 2008. Xiao Fan. Study of PPC Model Based on RAGA and Its Application for Geochemical Data Processing in Gejiu[D]. Wuhan: China University of Geosciences, 2008.
[1] Zhang Bo, Cao Hongkai, Sun Jianmeng, Zhang Pengyun, Yan Weichao. Numerical Simulation of Response Characteristics of Array Induction Logging in Heavy Oil Thermal Recovery Formation [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(4): 1277-1286.
[2] Liao Dongliang, Zeng Yijin. Establishment of Formation Shear Fracture Model by Logging Data [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(4): 1268-1276.
[3] Pan Baozhi, Liu Wenbin, Zhang Lihua, Guo Yuhang, Aruhan. A Method for Improving Accuracy of Reservoir Fracture Identification [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(1): 298-306.
[4] Li Zhenling, Shen Jinsong, Li Xining, Wang Lei, Dan Weining, Guo Sen, Zhu Zhongmin, Yu Renjiang. Estimating Porosity Spectrum of Fracture and Karst Cave from Conductivity Image by Morphological Filtering [J]. Journal of Jilin University(Earth Science Edition), 2017, 47(4): 1295-1307.
[5] Zhang Hengrong, He Shenglin, Wu Jinbo, Wu Yixiong, Liang Yunan. A New Method for Predicting Permeability Based on Modified Kozeny-Carmen Equation [J]. Journal of Jilin University(Earth Science Edition), 2017, 47(3): 899-906.
[6] JiangYanjiao, Sun Jianmeng, Gao Jianshen, Shao Weizhi, Chi Xiurong, Chai Xiyuan. Numerical Simulation of Mud Invasion Around the Borehole in Low Permeability Reservoir and a Method for Array Induction Log Resistivity Correction [J]. Journal of Jilin University(Earth Science Edition), 2017, 47(1): 265-278.
[7] Gao Jianshen, Sun Jianmeng, Jiang Yanjiao, Cui Likai. Effect of Electrode Array Structures in Laterolog and a New Array Measurement Method [J]. Journal of Jilin University(Earth Science Edition), 2016, 46(6): 1874-1883.
[8] Pan Baozhi, Jiang Bici, Liu Wenbin, Fang Chunhui, Zhang Rui. Gas-Bearing Logging Features and Quantitative Evaluation for Tight Sandstone Reservoirs [J]. Journal of Jilin University(Earth Science Edition), 2016, 46(3): 930-937.
[9] Zhang Xinpei, Yu Xuefeng. Using Geophysical Information to Describe Effective Reservoirs of Archean Buried Hill [J]. Journal of Jilin University(Earth Science Edition), 2016, 46(1): 270-278.
[10] Zhao Jun, Dai Xinyun, Gu Li, Qi Xinzhong, Chen Weizhong. Method of Permeability Model Establishment Based on the Complex Reservoir Controlled by Particle-Size [J]. Journal of Jilin University(Earth Science Edition), 2016, 46(1): 279-285.
[11] Zheng Xiangwei, Wu Jian, He Shenglin, Hu Xiangyang, Liang Yunan. Fine Evaluation of Permeability of Conglomerate Reservoir Based on Flow Unit [J]. Journal of Jilin University(Earth Science Edition), 2016, 46(1): 286-294.
[12] Jin Bo, Huang Xianxiong, Chang Guangfa, Zhang Shengbin, Fu Haibo, Li Tiezhu. Types and Distribution of Carboniferous Carbonate Reservoirs in Southern Д Area of Pre-Caspian Basin [J]. Journal of Jilin University(Earth Science Edition), 2014, 44(6): 2042-2050.
[13] Zhang Zhongqing, Pang Bingqiang. A Novel Approach for Electromagnetic Logging While Drilling Data Processing [J]. Journal of Jilin University(Earth Science Edition), 2014, 44(5): 1720-1726.
[14] Song Yanjie, Jiang Yanjiao, Song Yang, Zhang Yini. Experimental on the Influencing Factors of m and n of Low Resistivity Oil Reservoirs in Southern Gulong Area [J]. Journal of Jilin University(Earth Science Edition), 2014, 44(2): 704-714.
[15] Yang Zhen,Yang Jinzhou,Han Laiju. Numerical Simulation and Application of Azimuthal Propagation Resistivity Imaging While Drilling [J]. Journal of Jilin University(Earth Science Edition), 2013, 43(6): 2035-2043.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!