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中国典型钴矿床地质特征及重点地区矿产资源预测
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. DOI: 10.13278/j.cnki.jjuese.20220209
作者姓名:于晓飞  公凡影  李永胜  张家瑞
作者单位:1.中国地质地质调查局发展研究中心, 北京1000372.自然资源部矿产勘查技术指导中心,北京1000833.甘肃省地质调查院,兰州730030
基金项目:中国地质调查局项目(DD20190159)~~;
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...

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#
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. DOI: 10.13278/j.cnki.jjuese.20220209
Authors:Yu Xiaofei  Gong Fanying  Li Yongsheng  Zhang Jiarui
Affiliation:1.China Geological Survey Development Research Center, Beijing 100037, China2.Mineral Exploration Technical Guidance Center of Ministry of Natural Resources,Beijing 100083, China3.Geological Survey of Gansu Province,Lanzhou 730030,China
Abstract:China is not only a major consumer of cobaltresources but also a big importer of cobalt resources. Influenced by the newenergy electric vehicle industry, cobalt ore resources have attracted more andmore attention in recent years. In order to scientifically evaluate thepotential of cobalt resources, guide the deployment of prospecting andexploration, and improve the guarantee capacity of cobalt resources in China,we carried out cobalt resource potential evaluation of cobalt resources in 9key provinces (regions) from 2019 to 2021. Based on the perspective of thedistribution and geological characteristics of cobalt deposits, the types ofcobalt deposits predicted for prospecting in China are determined, including: weatheringtype, chemical deposit type, sandstone type and submarinehydrothermal-sedimentary type, all of which related to the sedimentarygeological processes; marine and continental volcanic rock type that related tothe volcanic geological processes; magmatic type, skarn type (contactmetasomatic type), hydrothermal vein type and porphyry type, all of which associatedwith intrusive magmatism; sedimentary metamorphic type and a small number ofmetamorphic core complexes type that related to the metamorphism. And the metallogenicgeological bodies related to various types of cobalt deposits are also sortedout and summarized. By analyzing the geological characteristics andspatio-temporal distribution of cobalt deposits in China, and synthesizingprediction elements such as geological, geophysical, geochemical, and remotesensing information, a prospecting prediction model was established,prospecting potential areas were delineated, and resource reserves wereestimated. The results show that the cobalt deposits in China include six mainprospecting prediction types: weathering crust nickel-cobalt deposit,hydrothermal-sedimentary copper-cobalt deposit, marine volcanic rockcopper-cobalt deposit, marine volcanic rock massive sulfide copper-zinc cobaltdeposit, magmatic copper-nickel cobalt deposit and hydrothermal veined cobaltdeposit; 416 cobalt ores were delineated,  64 prospecting potential areas were delineated,99 prospecting targets were optimized, and further exploration suggestions wereput forward. A total of 453 000 t of cobalt resources havebeen identified in 9 key provinces (regions), and the estimated cobaltresources are about 420 million t.
Keywords:cobalt deposit,geological characteristics,metallogenic regularity,prospecting predictionmodel  resourcepotentialevaluation  keyareas
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