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内蒙古浩布高铅锌矿床闪锌矿微量元素特征及其地质意义
引用本文:曾庆文, 戴香麟, 董国臣, 魏良民, 秦季军, 陈佳德, 肖阳, 舒启海. 2023. 内蒙古浩布高铅锌矿床闪锌矿微量元素特征及其地质意义. 岩石学报, 39(2): 567-582. doi: 10.18654/1000-0569/2023.02.17
作者姓名:曾庆文  戴香麟  董国臣  魏良民  秦季军  陈佳德  肖阳  舒启海
作者单位:1. 中国地质大学(北京)地质过程与矿产资源国家重点实验室, 北京 100083; 2. 赤峰山金红岭有色矿业有限责任公司, 赤峰 025420
基金项目:本文受赤峰山金红岭有色矿业有限责任公司委托项目(QT-QG-T2021204)和中央高校基本科研业务费专项资金(2652019045)联合资助
摘    要:

内蒙古浩布高铅锌矿床位于大兴安岭南段黄岗-甘珠尔庙成矿带, 该带是我国北方重要的铅锌多金属成矿带之一。目前, 浩布高矿床闪锌矿微量元素赋存机制尚不清晰, 矿床成因类型亦存在一定的争议。本研究采用激光剥蚀电感耦合等离子体质谱仪(LA-ICP-MS)原位微量元素分析手段, 结合机器学习方法, 对浩布高闪锌矿微量元素组成特征、赋存机制以及矿床成因类型进行了探讨。LA-ICP-MS分析结果表明, 浩布高矿床中闪锌矿以富集Fe、Mn、Co、Cu、Se、Ag、Cd、In、Sn等元素, 贫Ni、Ga、Ge、As、Mo、Sb、Au、Tl、Pb、Bi等元素为特征。其中, Fe、Mn、In等元素主要以类质同象的方式替代Zn赋存于闪锌矿中, Cu、Ag、Sn等元素含量变化范围较大, 可能部分以微粒包裹体的形式存在。In与Cu含量具有一定的正相关, 推测In在闪锌矿中富集机理可能为Cu++In3+↔2Zn2+。Cd与Fe含量呈一定的正相关性, 而与Zn含量呈负相关性, 这可能暗示在闪锌矿中Cd主要以类质同象的方式置换Zn元素而非Fe元素。通过穷举闪锌矿微量元素图解发现, 即使得分最高的Co/Ag-Mn图解依然存在较大范围的重叠区域, 因此不能简单地用闪锌矿微量元素二元图解来判别矿床类型。通过测试四种机器学习中经典的不同核函数的支持向量机算法, 最终得出准确率为91.5%的高斯内核支持向量机闪锌矿成矿类型分类器, 可以用于多种矿床类型闪锌矿的研究。浩布高矿床中闪锌矿微量元素组成明显不同于密西西比河谷型(MVT)、沉积喷流型(SEDEX)、火山块状硫化物型(VMS)和浅成低温热液型铅锌矿床, 而与矽卡岩型接近。综合已有矿物学、年代学以及本研究获得的闪锌矿地球化学证据表明, 浩布高应是一个典型的矽卡岩型铅锌矿床。



关 键 词:闪锌矿   微量元素组成   机器学习   矽卡岩型矿床   浩布高
收稿时间:2022-09-07
修稿时间:2022-12-20

Trace element characteristics of sphalerite in the Haobugao Zn-Pb deposit,Inner Mongolia,and their geological significance
ZENG QingWen, DAI XiangLin, DONG GuoChen, WEI LiangMin, QING JiJun, CHEN JiaDe, XIAO Yang, SHU QiHai. 2023. Trace element characteristics of sphalerite in the Haobugao Zn-Pb deposit, Inner Mongolia, and their geological significance. Acta Petrologica Sinica, 39(2): 567-582. doi: 10.18654/1000-0569/2023.02.17
Authors:ZENG QingWen  DAI XiangLin  DONG GuoChen  WEI LiangMin  QING JiJun  CHEN JiaDe  XIAO Yang  SHU QiHai
Affiliation:1. State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Beijing 100083, China; 2. Chifeng Hongling Nonferrous Mining Co. Ltd. (Shandong Gold Group), Chifeng 025420, China
Abstract:The Huanggang-Ganzhuermiao metallogenic belt in the south segment of the Great Xing'an Range is one of the important polymetallic belts in northeastern China. It contains several Zn-Pb deposits, among which Haobugao is a representative one. At present, the occurrence mechanism of the trace elements in the Haobugao sphalerite is not clear, and the genetic type of the deposit is controversial. In this study, in situ trace element analysis by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) combined with machine learning method was used to better characterize the sphalerite compositions and explore the mechanism how the trace elements enter into the sphalerite, and furthermore, to reveal the genetic type of the Haobugao deposit. The results show that the Haobugao sphalerite is characterized by enrichment of Fe, Mn, Co, Cu, Se, Ag, Cd, In and Sn, and depletion in Ni, Ga, Ge, As, Mo, Sb, Au, Tl, Pb and Bi. Among these trace elements, Fe, Mn and In are present isomorphously in sphalerite. The concentrations of Cu, Ag and Sn vary widely, indicating that some of them may occur as micro-inclusions. There is a generally positive correlation between the concentrations of In and Cu, suggesting that In substitutes into the sphalerite through substituting for Zn2+ by Cu++In3+↔2Zn2+. Cd is slightly positively correlated with Fe but negatively correlated with Zn, suggesting that Cd mainly replaces Zn rather than Fe. By enumerating the trace element diagrams of sphalerite, it is found that even the Co/Ag vs. Mn diagram with the highest Silhouette Coefficient still has a large part of overlapping areas, so the binary diagram of sphalerite trace elements cannot be simply used to distinguish the deposit types. Through testing the classical support vector machine (SVM) algorithms of four different kernel functions, the best result is a Gaussian kernel SVM classifier with an accuracy of 91.5%, which can be used for the judgment of the genetic types through sphalerite compositions. Using this method, it is demonstrated that the trace elements of the Haobugao sphalerite is significantly different from that of the MVT, SEDEX, VMS and epithermal Zn-Pb deposits, but similar to that of skarn type deposits. Combined with previous mineralogy and geochronology evidence and the present sphalerite geochemical results, the Haobugao deposit could be classified as a typical skarn type Zn-Pb deposit.
Keywords:Sphalerite  Trace elements  Machine learning  Skarn deposit  Haobugao
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