Journal of Jilin University(Earth Science Edition) ›› 2021, Vol. 51 ›› Issue (3): 783-791.doi: 10.13278/j.cnki.jjuese.20200116

Previous Articles     Next Articles

Application of XRF Semi-Quantitative Analysis Technology in Identifying Ore on Polished Section

Fan Pengfei1,2, Deng Shupei3, Zou Yuan4, Liu Chao2, Zhai Hongyu1, Zhou Dongdong5   

  1. 1. School of Earth Science, East China University of Technology, Nanchang 330006, China;
    2. Nuclear Research Institue of No. 230, Changsha 410007, China;
    3. Hunan Nonferrous Metal Exploration and Research Institute Testing Center, Changsha 410000, China;
    4. Hunan Institue of Geology Survey, Changsha 410116, China;
    5. Hunan Branch of China National Geological Exploration Center of Building Materials Industry, Changsha 410000, China
  • Received:2020-05-07 Online:2021-05-26 Published:2021-06-07
  • Supported by:
    Supported by the Project of China Geological Survey (DD20190379-17),the Project of China National Nuclear Corporation (Geology LCEQ-KYWX-01) and the Project of China Nuclear Geology (201918)

PDF (PC)

72

Abstract: The identification of minerals under the reflective polarizing microscope is the most commonly used, quickest, and effective method. However, the identification results are easily affected by personal subjective factors and conditions of the polished section. If we know the elements in the polished section in advance and relative content, we can conjecture the minerals based on geochemical methods and experiences, and the composition data combined with microscope observation can greatly improve the efficiency and accuracy of polished section identification. XRF semi-quantitative analysis technology has the characteristics of fast, non-destructive and simple in sample preparation. In the process of semi-quantitative analysis of the polished section, wedging and shadow effects can be avoided; although the gangue minerals such as silicate minerals cannot be avoided, and there may be even some other influencing factors such as chemical bond drift, the identification of gangue minerals is not very important. Using the results of XRF semi-quantitative analysis to conjecture the minerals, and then identify the minerals under a microscope, the efficiency and accuracy of polished section identification can be improved significantly. In order to illustrate the specific application of XRF semi-quantitative analysis technology in identification of polished section, several examples of polished section identification of polymetallic sulfide ores and uranium-containing polymetallic ores are listed.

Key words: XRF, semi-quantitative analysis, ore polished section, identification

CLC Number: 

  • P588.12
[1] 许乃岑, 沈加林, 张静. X射线衍射-X射线荧光光谱-电子探针等分析测试技术在玄武岩矿物鉴定中的应用[J]. 岩矿测试, 2015, 34(1): 75-81. Xu Naicen, Shen Jialin, Zhang Jing. Application of X-Ray Diffraction, X-Ray Fluorescence Spectrometry and Electron Microprobe in the Identification of Basalt[J]. Rock and Mineral Testing, 2015, 34(1): 75-81.
[2] Rousseau M. Fundamental Algorithm Between Concentration and Intensity in XRF Analysis[J]. X-Ray Spectrometry, 1984, 13(3): 115-120.
[3] Salmon M L. The Effects of Operating Variables in the Application of Multielement Calibration Systems for Fluorescent X-Ray Spectrographic Analyses of Mineral Samples[J]. Advances in X-Ray Analysis, 1960, 4: 433-456.
[4] Salmon M L. A Simple Multielement-Calibration System for Analysis of Minor and Major Elements in Minerals by Fluorescent X-Ray Spectrography[J]. Advances in X-Ray Analysis, 1961, 5: 389-404.
[5] Broll N, Caussin P, Peter M. Matrix Correction in X-Ray Fluorescence Analysis by the Effective Co-Efficient Method[J]. X-Ray Spectrom, 1992, 21(1): 43-49.
[6] Sherman J. The Theoretical Derivation of Fluorescent X-Ray Intensities From Mixture[J]. Spectrochimica Acta, 1955, 7: 283-306.
[7] 朱志秀, 冯健, 李晨, 等. X射线荧光光谱无标样分析技术在出入境矿产品检验中的应用[J]. 理化检验:化学分册, 2009, 45(7): 832-835. Zhu Zhixiu, Feng Jian, Li Chen, et al. Application of X-Aay Fluorescence Spectroscopy Standard-Free Analysis Technology in the Inspection of Entry and Exit Mineral Products[J]. Physical Testing and Chemical Analysis:Chemistry Volume, 2009, 45(7): 832-835.
[8] 张广玉, 赵世煌, 邓晃, 等. 手持式X射线荧光光谱多点测试技术在地质岩心和岩石标本预研究中的应用[J]. 岩矿测试, 2017, 36(5): 501-509. Zhang Guangyu, Zhao Shihuang, Deng Huang, et al. Application of Handheld X-Ray Fluorescence Spectrometry Multi-Point Measurement Mechnology in the Pre-Research of Geological Cores and Rock Specimens[J]. Rock and Mineral Testing, 2017, 36(5): 501-509.
[9] 岩矿鉴定技术规范:第3部分:矿石光片制样:DZ/T 0275.3—2015[S]. 北京: 中国标准出版社, 2015. Specification Identification of Rock and Mineral:Part 3:Ore Polished Section Preparation:DZ/T 0275.3-2015[S]. Beijing: Standards Press of China, 2015.
[10] 高新华, 宋武元, 邓赛文, 等. 实用X射线光谱分析技术[M]. 北京: 化学工业出版社, 2016: 170-171. Gao Xinhua, Song Wuyuan, Deng Saiwen, et al. Practical X-Ray Spectroscopy Analysis Technology[M]. Beijing: Chemical Industry Press, 2016: 170-171.
[11] 韩吟文, 马振东, 张宏飞, 等. 地球化学[M]. 北京: 地质出版社, 2003: 86-91. Han Yinwen, Ma Zhendong, Zhang Hongfei, et al. Geochemistry[M]. Beijing: Geological Publishing House, 2003: 86-91.
[12] 邵帅. 广西河池市大象岭铅锌矿地质特征及认识[J]. 矿产与地质, 2017, 31(4): 695-698. Shao Shuai. Geological Characteristics and Understanding of Daxiangling Lead-Zinc Deposit in Hechi City, Guangxi[J]. Mineral Resources and Geology, 2017, 31(4): 695-698.
[13] 谈树成, 郭翔宇, 何小虎, 等. 云南个旧锡多金属矿床锡石矿物化学特征及其成因意义[J]. 吉林大学学报(地球科学版), 2018, 48(3): 736-753. Tan Shucheng, Guo Xiangyu, He Xiaohu, et al. The Mineral Chemical Characteristics and Genesis of Cassiterite from the Gejiu Tin-Polymetallic Deposit in Yunnan Province[J]. Journal of Jilin University (Earth Science Edition), 2018, 48(3): 736-753.
[14] 彭渤洋, 陈友良, 刘堃, 等. 攀枝花大田505铀矿区混合岩主量元素特征及其意义[J]. 四川冶金, 2017, 39(6): 32-38. Peng Boyang, Chen Youliang, Liu Kun, et al. Characteristics and Significance of Major Elements of Mixed Rocks in Datian 505 Uranium Mining Area, Panzhihua[J]. Sichuan Metallurgy, 2017, 39(6): 32-38.
[15] 张万良. 鹿井铀矿田成矿地质特征及控矿因素[J]. 铀矿地质, 2017, 27(2): 81-87. Zhang Wanliang. Metallogenic Geological Characteristics and Ore-Controlling Factors of Lujing Uranium Ore Field[J]. Uranium Geology, 2017, 27(2): 81-87.
[16] 孙宏伟,王杰,任军平, 等. 中非卢菲里安地区铀矿化特征与资源潜力分析[J]. 吉林大学学报(地球科学版), 2020, 50(6): 1660-1674. Sun Hongwei, Wang Jie, Ren Junping, et al. Analysis of Uranium Mineralization Characteristics and Resource Potential in the Lufirian Region of Central Africa[J]. Journal of Jilin University (Earth Science Edition), 2020, 50(6): 1660-1674.
[17] 张金带. 中国北方中新生代沉积盆地铀矿勘查进展和展望[J]. 铀矿地质, 2012, 28(4): 193-198. Zhang Jindai. Progress and Prospects of Uranium Exploration in Mesozoic and Cenozoic Sedimentary Basins in Northern China[J]. Uranium Geology, 2012, 28(4): 193-198.
[1] Zhu Kaiguang, Jing Chunyang, Fan Tianjiao, Yang Yang, Peng Cong. Identification of Time Domain Airborne Electromagnetic Response with Pseudo-Random Binary Sequence [J]. Journal of Jilin University(Earth Science Edition), 2021, 51(6): 1881-1889.
[2] Xiong Yuehan, Liu Dongyan, Liu Dongsheng, Wang Yanlei, Tang Xiaoshan. Automatic Lithology Classification Method Based on Deep Learning of Rock Sample Meso-Image [J]. Journal of Jilin University(Earth Science Edition), 2021, 51(5): 1597-1604.
[3] Mou Dan, Zhang Lichun, Xu Changling. Comparison of Three Classical Machine Learning Algorithms for Lithology Identification of Volcanic Rocks Using Well Logging Data [J]. Journal of Jilin University(Earth Science Edition), 2021, 51(3): 951-956.
[4] Wang Heng, Jiang Yanan, Zhang Xin, Zhong Hongru, Chen Qingxuan, Gao Shichen. Lithology Identification Method Based on Gradient Boosting Algorithm [J]. Journal of Jilin University(Earth Science Edition), 2021, 51(3): 940-950.
[5] An Yuke, Fan Jiang, Ma Shengwu, Ma Jianquan, Gao Juan, Mao Lijun. Identification of Ancient and Old Landslides in Terraces and Its Application in Linear Engineering Investigation [J]. Journal of Jilin University(Earth Science Edition), 2020, 50(6): 1787-1794.
[6] Ye Tao, Wei Ajuan, Huang Zhi, Zhao Zhiping, Xiao Shuguang. Quantitative Identification of Volcanic Lithology Based on Comprehensive Principal Component Analysis and Bayes Discriminant Method: A Case Study of Mesozoic in Bohai Bay [J]. Journal of Jilin University(Earth Science Edition), 2019, 49(3): 872-879.
[7] Zhang Wenqiang, Yin Changchun, Liu Yunhe, Zhang Bo, Ren Xiuyan. Field Continuation for MCSEM Forward Modeling and Identification of Anisotropic Media [J]. Journal of Jilin University(Earth Science Edition), 2019, 49(2): 578-590.
[8] Zheng Guolei, Xu Xinxue, Li Shibin, Yuan Hang, Ma Wei, Ye Qing. Inversion of Gravity Data in Tianjin [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(4): 1221-1230.
[9] 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.
[10] Zhao Yuyan, Li Bing, Lu Jilong, Hao Libo, Zhao Yu, Wang Dongming. Geochemical and Geophysical Information Integration Technology for Geological Mapping at Shallow Overburden Area in Northeast China [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(1): 318-333.
[11] Yan Baizhong, Qiu Shuwei, Xiao Changlai, Liang Xiujuan. Potential Geothermal Fields Remote Sensing Identification in Changbai Mountain Basalt Area [J]. Journal of Jilin University(Earth Science Edition), 2017, 47(6): 1819-1828.
[12] Liu Haiyan, Liu Cai, Wang Dian, Liu Yang. Seismic Data Discontinuity Identification Using Coherence Based on Facet Model Gradient Operator [J]. Journal of Jilin University(Earth Science Edition), 2017, 47(4): 1286-1294.
[13] Xiao Fan, Chen Jianguo. Application of PPC Model Combined with RCGA to Identify and Extract Geochemical Anomaly [J]. Journal of Jilin University(Earth Science Edition), 2017, 47(4): 1319-1330.
[14] Lan Kai, Liu Xiangfeng. Research Advances in Drillstring Excessive Vibration Identification and Control Techniques [J]. Journal of Jilin University(Earth Science Edition), 2017, 47(1): 203-214.
[15] Song Zhi, Deng Ronggui, Chen Zeshuo, Feng Wei. Physical Simulation and Early Identification of Dadu River Blocking Due to Moxi River Debris Flow [J]. Journal of Jilin University(Earth Science Edition), 2017, 47(1): 163-170.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] GAO Song，SONG Ying，WANG Lin，JIANG Buxin. Study on the Screening and Characterization of Special Effective Bacteria of Degrading Thiuram in the Waterbody[J]. J4, 2006, 36(03): 455 -457 .
[2] LI Xian-zhou,LIU Yan,LIU Li-hua,NING Wei-kun,FAN Hai. The Preparation and Characterization of the Kaolin-Hydrazine Intercalation Complex[J]. J4, 2006, 36(04): 659 -662 .
[3] LU Shuang-fang, LI Ji-jun, XUE Hai-tao, XU Li-heng. Chemical Kinetics of Carbon Isotope Fractionation of Oil-Cracking Methane and Its Initial Application[J]. J4, 2006, 36(05): 825 -829 .
[4] DING Zhi-hong,FENG Ping,MAO Hui-hui. Research and Application of a Method Considering Runoff Distribution Through A Year During Partitioning Runoff into Abundant and Low State[J]. J4, 2009, 39(2): 276 -0280 .
[5] ZHANG Feng-jun, LI Qing, MA Jiu-tong, YU Guang-ju. Experimental Study on Treatment of Furfural Wastewater with Membrane Distillation[J]. J4, 2006, 36(02): 270 -0273 .
[6] ZHANG Yuan-qing, SONG Bing-zhong, WANG Yu-fu, ZHANG Ning. Metallogenetic Rules and Prediction of Gold Deposits Around Tongshi Complex,Western Shandong Province[J]. J4, 2010, 40(6): 1287 -1294 .
[7] AN Le-sheng, LIU Guan-qun, YE Si-yuan, ZHAO Quan-sheng, DING Xi-gui, ZHANG Jian-wei. Health Assessment of Coastal Wetlands in the Yellow River Delta[J]. J4, 2011, 41(4): 1157 -1165 .
[8] LI Song, TANG Da-zhen, WANG Wei, XU Hao, YANG Zi, CHEN Xiao-zhi, CUI Li-wei. Sequence Stratigraphic Framework and Geological Significance for Petroleum of Xishanyao Formation in Shanle Oilfield[J]. J4, 2011, 41(4): 983 -991 .
[9] ZENG Yu-chao, SU Zheng, WU Neng-you, WANG Xiao-xing, HU Jian. Temperature Distribution Characteristics of Bedrock Fracture Groundwater System at Zhangzhou Geothermal Field[J]. J4, 2012, 42(3): 814 -820 .
[10] He Jun, Ye Xueyan. Probability Design of Thickness of Composite Liners Based on Organic Pollutant Diffusion[J]. Journal of Jilin University(Earth Science Edition), 2013, 43(1): 228 -234 .
Copyright © Journal of Jilin University(Earth Science Edition), All Rights Reserved.
Tel: +86-431-88502374；13756165364　E-mail: xuebao1956@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd