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模型区定量估算参数确定
引用本文:丁建华,肖克炎,叶天竺,邓刚,娄德波. 模型区定量估算参数确定[J]. 吉林大学学报(地球科学版), 2013, 43(4): 1111-1118
作者姓名:丁建华  肖克炎  叶天竺  邓刚  娄德波
作者单位:1.中国地质科学院矿产资源研究所/ 国土资源部成矿作用与资源评价重点实验室, 北京100037;2.中国地质调查局,北京100037;3.新疆地矿局第六地质大队,新疆 哈密839000
基金项目:中国地质调查局地质大调查项目,科学技术部科技支撑项目,国家自然科学基金项目,中国地质科学院矿产资源研究所基本业务费项目
摘    要:预测模型是将当代成矿理论与现代高新综合勘查技术结合,并将传统的定量数值科学方法与计算机信息技术结合的桥梁。目前全国正在开展的矿产资源潜力评价工作中,资源量估算采用的是矿床模型综合地质信息体积法,该方法基于模型区含矿地质体的体积及其赋含的资源储量来获得模型区含矿系数,再通过类比估算其他预测区潜在资源量。以红石山镍矿为例,详细讲述了模型区的圈定以及含矿地质体定量参数确定的原则及方法。研究认为,国内外目前选用的许多定量预测模型一般都缺少对矿床成因等因素的考虑,该方法则通过对成矿有利的含矿建造的限定来确定成矿系统的范围,从而较好地将矿床成因与定量模型结合起来,提高了预测资源量的可信度。

关 键 词:矿产  定量评价  预测模型  含矿建造  红石山镍矿  
收稿时间:2012-11-07

Determination of Quantitative Parameters in Deposit Model Area
Ding Jianhua,Xiao Keyan,Ye Tianzhu,Deng Gang,Lou Debo. Determination of Quantitative Parameters in Deposit Model Area[J]. Journal of Jilin Unviersity:Earth Science Edition, 2013, 43(4): 1111-1118
Authors:Ding Jianhua  Xiao Keyan  Ye Tianzhu  Deng Gang  Lou Debo
Affiliation:1.Institute of Mineral Resources, Chinese Academy of Geological Sciences/Key Laboratory of Metallogeny 〓and Mineral Assessment, MLR,Beijing100037, China;
2.Chinese Geological Survey, Beijing100037, China;
3.No.6 Teem of Xinjiang Geological Prospecting Bureau, Hami839000, Xinjiang, China
Abstract:“Prognosis model”is considered as bridge to combine metallogenic theories with modern exploration techniques, and to combine exploration techniques with GIS. During the performance of National Mineral Resource Assessment Project, geologists use “Deposit Synthetic Information Modeling Volume Method” to estimate the potential resource. The main principle of this method is to estimate the potential resource of the predicted areas by the ore bearing coefficient of the model area. The authors choose Hongshishan nickel deposit as model to show in detail how to delineate the area and depth of ore-bearing formations. Compared with those quantitative models now used in both domestic and abroad, the method discussed in this paper takes genesis into account by identifying “ore-bearing formation”, which can improve the confidence level of quantitative assessment results.
Keywords:mineral resources  quantitative assessment  prognosis model  ore-bearing formation  Hongshishan nickel deposit
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