| 中国典型钴矿床地质特征及重点地区矿产资源预测 |
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| 引用本文： | 于晓飞,公凡影,李永胜,张家瑞.中国典型钴矿床地质特征及重点地区矿产资源预测[J].吉林大学学报(地球科学版),2022,52(5):1377-1418. |
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| 作者姓名： | 于晓飞 公凡影 李永胜 张家瑞 |
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| 作者单位： | 1.中国地质地质调查局发展研究中心, 北京
100037
2.自然资源部矿产勘查技术指导中心，北京
100083
3.甘肃省地质调查院，兰州
730030 |
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| 摘 要： | 我国既是钴矿资源消费大国,又是钴矿资源进口大国,受新能源电动汽车工业的影响,近年来钴矿资源得到越来越多的关注.为了科学地评估我国钴矿资源潜力,指导找矿勘查部署工作,立足国内,提高我国钴矿资源的保障能力,笔者２０１９—２０２１年开展了９个重点省(自治区)的钴矿资源潜力评价工作.本文从我国钴矿床分布和地质特征角度,先以成矿地质作用为主线,厘定我国找矿预测矿床类型,包括与沉积地质作用有关的风化型、化学沉积型、砂岩型和海底喷流沉积型,与火山地质作用有关的海相火山岩型、陆相火山岩型,与侵入岩浆地质作用有关的岩浆型、矽卡岩型(接触交代型)、热液脉型和斑岩型,与变质地质作用有关的沉积变质型,以及少量与大型变形地质作用有关的变质核杂岩型;进而梳理并总结了各类型钴矿有关的成矿地质体.通过分析我国钴矿的矿床地质特征和时空分布规律,综合地质、物探、化探和遥感信息等预测要素,建立找矿预测模型,并在此基础上圈定找矿远景区,估算资源量.结果表明:我国钴矿包括风化型镍钴矿、海底喷流沉积型铜钴矿、海相火山岩型铁铜钴矿、海相火山岩型块状硫化物铜锌钴矿、岩浆型铜镍钴矿和热液脉型钴矿６种主要找矿预测类型;圈定416个钴矿最小预测区,圈定64个找矿远景区,优选99个找矿靶区,提出下一步勘查建议;９个重点省(自治区)累计查明钴资源储量45.3万t,预测钴资源量约420万t.
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| 关 键 词： | 钴矿床 地质特征 成矿规律 找矿预测模型 资源潜力评价 重点地区 |
| 收稿时间： | 2022-07-14 |
Geological Characteristics of Typical Cobalt Deposits in China andPrediction of Mineral Resources in the Key Areas#br# |
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| Yu Xiaofei,Gong Fanying,Li Yongsheng,Zhang Jiarui.Geological Characteristics of Typical Cobalt Deposits in China andPrediction of Mineral Resources in the Key Areas#br#[J].Journal of Jilin Unviersity:Earth Science Edition,2022,52(5):1377-1418. |
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| Authors: | Yu Xiaofei Gong Fanying Li Yongsheng Zhang Jiarui |
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| Institution: | 1.
China Geological Survey Development Research Center, Beijing 100037, China
2.
Mineral Exploration Technical Guidance Center of Ministry of Natural Resources,
Beijing 100083, China
3.
Geological Survey of Gansu Province,Lanzhou 730030,China |
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| Abstract: | China is not only a major consumer of cobalt
resources but also a big importer of cobalt resources. Influenced by the new
energy electric vehicle industry, cobalt ore resources have attracted more and
more attention in recent years. In order to scientifically evaluate the
potential of cobalt resources, guide the deployment of prospecting and
exploration, and improve the guarantee capacity of cobalt resources in China,
we carried out cobalt resource potential evaluation of cobalt resources in 9
key provinces (regions) from 2019 to 2021. Based on the perspective of the
distribution and geological characteristics of cobalt deposits, the types of
cobalt deposits predicted for prospecting in China are determined, including: weathering
type, chemical deposit type, sandstone type and submarine
hydrothermal-sedimentary type, all of which related to the sedimentary
geological processes; marine and continental volcanic rock type that related to
the volcanic geological processes; magmatic type, skarn type (contact
metasomatic type), hydrothermal vein type and porphyry type, all of which associated
with intrusive magmatism; sedimentary metamorphic type and a small number of
metamorphic core complexes type that related to the metamorphism. And the metallogenic
geological bodies related to various types of cobalt deposits are also sorted
out and summarized. By analyzing the geological characteristics and
spatio-temporal distribution of cobalt deposits in China, and synthesizing
prediction elements such as geological, geophysical, geochemical, and remote
sensing information, a prospecting prediction model was established,
prospecting potential areas were delineated, and resource reserves were
estimated. The results show that the cobalt deposits in China include six main
prospecting prediction types: weathering crust nickel-cobalt deposit,
hydrothermal-sedimentary copper-cobalt deposit, marine volcanic rock
copper-cobalt deposit, marine volcanic rock massive sulfide copper-zinc cobalt
deposit, magmatic copper-nickel cobalt deposit and hydrothermal veined cobalt
deposit; 416 cobalt ores were delineated, 64 prospecting potential areas were delineated,
99 prospecting targets were optimized, and further exploration suggestions were
put forward. A total of 453 000 t of cobalt resources have
been identified in 9 key provinces (regions), and the estimated cobalt
resources are about 420 million t. |
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| Keywords: | cobalt deposit geological characteristics metallogenic regularity prospecting predictionmodel resourcepotentialevaluation keyareas
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