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    娄德波, 肖克炎, 孙艳, 李楠. 成矿概率面金属量法在东天山铜镍矿预测中的应用[J]. 中国地质, 2010, 37(1): 183-190.
    引用本文: 娄德波, 肖克炎, 孙艳, 李楠. 成矿概率面金属量法在东天山铜镍矿预测中的应用[J]. 中国地质, 2010, 37(1): 183-190.
    LOU De-bo, XIAO Ke-yan, SUN Yan, LI Nan. The application of areal productivity based on the probability of mineral occurrence: A case study of copper-nickel sulfide deposits in the East Tianshan Mountains[J]. GEOLOGY IN CHINA, 2010, 37(1): 183-190.
    Citation: LOU De-bo, XIAO Ke-yan, SUN Yan, LI Nan. The application of areal productivity based on the probability of mineral occurrence: A case study of copper-nickel sulfide deposits in the East Tianshan Mountains[J]. GEOLOGY IN CHINA, 2010, 37(1): 183-190.

    成矿概率面金属量法在东天山铜镍矿预测中的应用

    The application of areal productivity based on the probability of mineral occurrence: A case study of copper-nickel sulfide deposits in the East Tianshan Mountains

    • 摘要: 提要:地球化学方法被普遍应用于矿产资源定量预测, 但多数方法都只是基于地球化学数据本身而进行的, 较少考虑除成矿物质来源之外的诸如构造、地层等地质环境的影响,结果使估算的资源量不能够很好符合客观实际。在充分研究地质因素的基础上, 认为物质基础和富集强度是矿床形成的重要条件,并据此对传统面金属量法进行了修正,建立了成矿概率面金属量法。该法可在一定程度上屏蔽虚假资源量。笔者采用成矿概率面金属量法对东天山地区铜镍矿的铜资源量进行了定量评价,效果较好。预测结果表明, 东天山地区该类型铜矿资源潜力较大。

       

      Abstract: Abstract:Geochemical methods have been commonly used in the quantification of mineral resources. Most of these methods, however, are based merely on geochemical data, with less attention paid to geological factors such as tectonics and strata. In consequence, the estimation of mineral resources frequently fails to conform to the reality. Based on a study of geological factors, the authors consider material basis and enrichment intensity as important metallogenic conditions and have thus established a new areal productivity based on the probability of mineral occurrence by modifying the traditional areal productivity. To some extent, this method wipes off pseudo-estimation. The authors calculated the copper potential resources of copper-nickel sulfide deposits in East Tianshan Mountains and obtained satisfactory result. It is shown that the potential of copper resources in the East Tianshan Mountains is very great.

       

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