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作 者:陶金涛 张楠楠[1,2] 常金雨 李艳荣 Tao Jintao;Zhang Nannan;Chang Jinyu;Li Yanrong(Xinjiang Research Center for Mineral Resources,Xinjiang Institute of Ecology and Geography,Chinese Academy of Sciences,Urumqi,Xinjiang,830011,China;University of Chinese Academy of Sciences,Beijing,100049,China)
机构地区:[1]中国科学院新疆生态与地理研究所新疆矿产资源研究中心,新疆乌鲁木齐830011 [2]中国科学院大学,北京100049
出 处:《新疆地质》2022年第1期27-32,共6页Xinjiang Geology
基 金:国家重点研发计划(2018YFC0604006-4);中国科学院战略性先导研究项目(XDA19030204)联合资助
摘 要:结合新疆东天山卡拉塔格地区红海VMS铜锌矿床成矿地质背景,基于矿区积累的地质和物探数据,构建了三维地质模型。利用三维距离分析和地球物理反演方法,定量提取了多种控矿因素;采用逻辑回归模型进行了深部成矿预测并圈定了找矿有利单元。预测结果表明,逻辑回归模型能够较好地识别红海矿床深部隐伏矿体,圈定的找矿有利单元约占研究区所有块体单元的3.95%,包含了红海已知矿体块体单元的96.43%。找矿有利单元主要沿红海矿区NE向和NW向两条主断裂分布,在已知矿体的南部存在较高成矿概率的区域,体积约为86×10^(6)m^(3),主要埋藏深度为地表下250~600 m,可作为下一步找矿勘探的重点区域。Combined with the geological background of the Honghai volcanogenic massive sulfide Cu–Zn deposit in Kalatage district, eastern Tianshan, northwestern China, a 3D geological model was constructed based on the accumulated geological data and geophysical data. A variety of ore-controlling factors were quantitatively extracted by using 3D distance analysis and geophysical inversion. The logistic regression model was used for deep prospectivity mapping and to delineate favorable units. The result shows that the logistic regression model can identify the concealed and deep-seated Honghai deposit well. The delineated favorable units occupied about 3.95% of the study area, but contain 96.43% of the known orebody. The favorable units are mainly distributed along the NE-and NW-trending faults. The high favorable areas, located in the south of the known orebody of the Honghai deposit, have great potential. Their volume is about 86×10^(6)m^(3) and their buried depth is 250 m to 600 m underground. They should be considered as high-priority targets for future mineral exploration.
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