资源与产业 ›› 2018, Vol. 20 ›› Issue (2): 41-51.DOI: 10.13776/j.cnki.resourcesindustries.20180507.001

• 资源开发 • 上一篇    下一篇

西藏改则县铁格隆南荣那矿段超大型斑岩—浅成低温热液复合型铜矿床特征及找矿资源潜力分析

李 志,冉启兰    

  1. (西藏自治区地质矿产勘查开发局第五地质大队,青海 格尔木 816099) 
  • 收稿日期:2018-03-19 修回日期:2018-04-18 出版日期:2018-04-20 发布日期:2018-06-24
  • 通讯作者: 李志(E-mail: zbzcs@163.com)
  • 基金资助:
    中国地质调查局地质调查项目(12120114050401) 

CHARACTERISTICS AND RESOURCE POTENTIAL OF RONGNA SUPER LARGE PORPHYRY-EPITHERMAL COMPOUND COPPER DEPOSIT, SOUTHERN TIEGELONG, GAIZE COUNTY, TIBET 

LI Zhi, RAN Qilan    

  1. (No.5 Geobrigade of Tibet Geology and Minerals Exploration and Development, Golmud 816099, China) 
  • Received:2018-03-19 Revised:2018-04-18 Online:2018-04-20 Published:2018-06-24
  • Supported by:
     

摘要: 介绍了西藏改则县多龙矿集区超大型铜矿床铁格隆南荣那矿段的成矿背景、矿床地质、物化探异常特征、蚀变矿物及蚀变分带、矿体地质、矿石质量、矿化期和矿化阶段等矿床特征,并对成矿物质来源做了简单阐述。荣那铜矿床虽是受同一构造—岩浆成矿作用下的系统产物,但由于受两种成矿叠加作用的影响,形成了上部为高硫型浅成低温热液矿床,下部为斑岩型矿床的空间叠置关系,成就该矿床目前是多龙矿集区Cu资源里最大(332+333+334)可达1 100万t,铜平均品位053%最高的铜矿床。通过对矿床类型的精确厘定及成矿地质体、成矿构造和成矿结构面及成矿作用特征标志的研究,构建了铁格隆南荣那矿段找矿预测地质模型,总结和归纳了矿区找矿预测地质模型的结构基本特征,并结合音频大地电磁测深,对矿床下一步找矿方向和资源潜力进行了分析。 

 

关键词: 多龙矿集区;矿床特征;斑岩型铜矿;浅层低温热液;找矿预测地质模型;资源潜力;铁格隆南荣那矿段 

Abstract: This paper introduces the geologic setting, deposit geology, geophysical/geochemical anomalies, alteration, ore body geology, ores quality, mineralization period and stages of Rongna super large porphyry-epithermal compound copper deposit, Gaize county, Tibet, and discusses the source of mineralization elements. Rongna copper deposit is a compound deposit with high-sulfur epithermal deposit on the top and porphyry deposit on the lower part, although it is in the same structure-magma. It is the largest copper deposit in Duolong mineralization concentration district, with 332+333+334 resource up to 11 million tons at a grade of 0.53%. This paper clarifies the deposit types, geology, structure and mineralization, establishes a geological model to predict ore deposit in Rongna deposit, southern Tiegelong, and summarizes its structure, and analyzes the further prospecting and resource potential combined with CSAMT.

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