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中国铁矿资源潜力定量分析
引用本文:肖克炎,娄德波,阴江宁,王全明,李景朝,杨毅衡,孙 莉,丁建华,叶天竺.中国铁矿资源潜力定量分析[J].地质通报,2011,30(5):650-660.
作者姓名:肖克炎  娄德波  阴江宁  王全明  李景朝  杨毅衡  孙 莉  丁建华  叶天竺
作者单位:1. 中国地质科学院矿产资源研究所,北京100037;长江大学,湖北荆州434023
2. 中国地质科学院矿产资源研究所,北京,100037
3. 中国地质调查局,北京,100037
4. 中国地质调查局发展研究中心,北京,100037
5. 北京信息工程大学,北京,100101
6. 国土资源部高咨中心,北京,100812
摘    要:按照矿床模型综合地质信息矿产预测方法,在中大比例尺勘探数据的基础上,全国分省分预测工作区,不同矿产预测类型分预测深度和可利用性,对全疆域铁矿圈定成矿远景区,使用地质参数体积法估算铁矿潜在资源量。以此为基础,按照单位面积查明资源量和预测资源量定量统计,分析中国重要的铁矿矿集区,为铁矿整装勘查提出部署参考建议。

关 键 词:铁矿  资源  评价  矿集区  定量  模型

Quantified research on iron potential of China
XIAO Ke-yan,LOU De-bo,YIN Jiang-ning,WANG Quan-ming,LI Jing-chao,YANG Yi-heng,SUN Li,DING Jian-hu,YE Tian-zhu.Quantified research on iron potential of China[J].Geologcal Bulletin OF China,2011,30(5):650-660.
Authors:XIAO Ke-yan  LOU De-bo  YIN Jiang-ning  WANG Quan-ming  LI Jing-chao  YANG Yi-heng  SUN Li  DING Jian-hu  YE Tian-zhu
Institution:1. Institute of Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China;2. Yangtze University, Jingzhou 434023, Hubei, China;3. China Geological Survey, Beijing 100037, China;4. Development and Research Center, China Geological Survey, Beijing 100037, China;5. Beijing Information Engineering College, Beijing 100101, China;6. Consultation Center of Ministry of Land and Resource, Beijing 100812, China
Abstract:According to the integrated geo-information modeling reserve estimation method and on the basis of the exploration data at the middle and large scales, the authors delineated the national iron tracts under the conditions of different depths, different applications and different assessment mineral styles in the assessment working area of every province in China, whose reserve quantity was estimated with the geological parameter volume method. Based on the discovered and potential iron quantity data in each unit area, the authors studied iron concentration areas in China, and the result will give suggestions for decision makers to make iron exploration decisions.
Keywords:iron minerals  resource  assessment  concentration area    quantity    model
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