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鄂东矿集区矽卡岩型铁矿的叠加富集机制:来自磁铁矿结构和矿石品位数据的制约
引用本文:朱乔乔,谢桂青,李伟.鄂东矿集区矽卡岩型铁矿的叠加富集机制:来自磁铁矿结构和矿石品位数据的制约[J].岩石学报,2019,35(12):3703-3720.
作者姓名:朱乔乔  谢桂青  李伟
作者单位:中国地质科学院矿产资源研究所, 自然资源部成矿作用与资源评价重点实验室, 北京 100037,中国地质科学院矿产资源研究所, 自然资源部成矿作用与资源评价重点实验室, 北京 100037,中国地质科学院矿产资源研究所, 自然资源部成矿作用与资源评价重点实验室, 北京 100037
基金项目:本文受国家重点研发计划专题项目(2016YFC06002006)、中央级公益性科研院所基本科研业务费专项资金(KK1702)和国家自然科学基金项目(41702093、41925011)联合资助.
摘    要:矽卡岩型铁矿是我国重要的铁矿类型之一,但该类型铁矿床的品位存在两极分化的现象。本文对鄂东矿集区内典型的矽卡岩型铁矿:大冶铁铜矿、程潮铁矿和金山店铁矿开展详细的磁铁矿显微结构对比,并利用概率图解法对这三个矿床的矿石品位数据进行了筛分。发现在大冶铁铜矿和程潮铁矿中的磁铁矿至少有两个世代,发育明显的叠加结构,且叠加结构在光学显微镜和背散射电子照片中可以识别出来;金山店铁矿中局部矿石也发育叠加结构。这些矿床中代表性勘探线的钻孔品位数据的累积频率曲线具有由低值(TFe 18. 04%~33. 03%)和高值(TFe 48. 97%~55. 63%)两个非相交总体所形成的混合分布模式,剔除低品位数据(TFe 20%)再次筛分其分布模式不变,但单一总体的参数有所改变。磁铁矿结构和品位数据筛分结果表明,这些矿床可能是两个或多个期次/阶段成矿作用叠加的结果,但不同矿床的叠加程度略有区别,大冶和程潮铁矿叠加程度较高,而金山店则相对较弱,这可能是导致大冶和程潮矿床整体为富铁矿而金山店铁矿只有局部是富铁矿的重要原因。因此,叠加富集可能是矽卡岩型铁矿中铁高效富集的一种重要机制,多世代磁铁矿的发育范围和叠加程度可以在一定程度上反映高品位矿石的分布状况,其叠加程度可以作为矽卡岩型富铁矿的找矿线索。

关 键 词:鄂东矿集区  矽卡岩型铁矿  叠加富集  结构  矿石品位  筛分  概率图
收稿时间:2019/1/1 0:00:00
修稿时间:2019/3/10 0:00:00

Superposition mechanism of Fe enrichment in skarn deposits of Edong district: Constrains from magnetite texture and ore grade data
ZHU QiaoQiao,XIE GuiQing and LI Wei.Superposition mechanism of Fe enrichment in skarn deposits of Edong district: Constrains from magnetite texture and ore grade data[J].Acta Petrologica Sinica,2019,35(12):3703-3720.
Authors:ZHU QiaoQiao  XIE GuiQing and LI Wei
Institution:MNR Key Laboratory of Metallogeny and Mineral Assessment, Institute of Mineral Resources, CAGS, Beijing 100037, China,MNR Key Laboratory of Metallogeny and Mineral Assessment, Institute of Mineral Resources, CAGS, Beijing 100037, China and MNR Key Laboratory of Metallogeny and Mineral Assessment, Institute of Mineral Resources, CAGS, Beijing 100037, China
Abstract:Fe skarn deposit is one of the most important Fe types in China, but the grade of this deposit type is polarized. The genesis of high grade Fe skarn deposit in China, especially in the Edong district, eastern China, has been the subject of controversy for decades. Three possible working hypotheses have been proposed, including ore magma, magmatic-hydrothermal replacement and magma-hydrothermal transitional precipitation. In this paper, detailed comparisons on texture of magnetite were carried out on typical Daye-type Fe skarn deposits in the Edong district, including Daye Fe-Cu deposit, Chengchao and Jinshandian Fe deposit, then ore grade data from drill cores of these deposit are analyzed by using probability graphs to separate threshold values. At least two generations of magnetite were recognized in Daye and Chengchao deposit, they formed superposition texture (dissolution and reprecipitation texture included) and can be identified by optical microscope under reflected light and back-scattered electron (BSE) images, which corresponding to different geochemical components. Part of the magnetite from Jinshandian deposit also developed superposition texture. Ore grade data of these deposits showed bimodal distribution which contains a lower group (TFe 18.04%~33.03%) and a high group (TFe 48.97%~55.63%). Excluding the low grade data (TFe < 20%) would not impact the trend of distribution, but could change the parameters of both single group. The above features indicate that these Fe skarn deposits of Edong district might be the result of superposition of two or more ore-forming episodes/stages. The degrees of superposition are different from deposit to deposit. The Daye and Chengchao deposits had a much higher extent of superposition than that of Jinshandian did, this is probably the reason why Daye and Chengchao are high grade deposits while part of Jinshandian deposit is high grade ore. Therefore, superposition might be an important mechanism for highly effective enrichment of Fe in skarn system. The range of multiple generations of magnetite and the extent of superposition can reflect the distribution of high grade ores and extent of superposition could be used as a prospecting clue for high grade Fe skarn deposit.
Keywords:Edong district  Fe skarn deposit  Superposition mechanism  Texture  Ore grade  Threshold separation  Probability graph
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