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Unravelling the Factors Impacting on Concentrate Quality by Geometallurgical Data Analysis at Fortescue Metals Group's Iron Bridge Magnetite Mine

机译:Fortescue金属集团铁桥磁铁矿地质冶金数据分析对影响浓缩质量影响的因素

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The Iron Bridge magnetite mine and infrastructure project is currently in development as a joint venture between Fortescue Metals Group, Formosa and BaosteeL It is supported by an extensive database of reverse circulation drill hole samples analysed by X-ray fluorescence (XRF), with a large subset tested for concentrate mass recovery, concentrate and tail grades by Davis tube recovery (DTR) testing. A limited number of rock physical testing results, including unconfined/ uniaxial compressive strength and crushing work index, completes the database. By combining all available information - assays, DTR results, geology, stratigraphy, mineralogy and rock physical results - and using multivariate statistical analysis techniques, the impact of the critical factors that control concentrate quality, mass recovery and grindability characteristics have been outlined. A set of geochemical groups was created by using a cluster analysis technique from the combined XRF-DTR data. These groups allow optimal separation of material with consistently high concentrate Fe grades and mass recovery. This approach is superior to domaining based on stratigraphic logging or mass recovery as it is commonly used in standard magnetite estimation models. Using the results of a normative mineralogy study, the main geochemical groups were given a mineralogical profile fitting their geochemical characteristics. These findings further refined the understanding of the link between the process characteristics of the samples and their geochemical signature and mineralogy. The geochemical grouping defined on head grades and DTR concentrate mass recovery was generalised into a 'geomet' code based solely on the routinely assayed head grades, thus bypassing the need for systematic DTR testing. The geomet code identifies spatial domains with homogeneous geochemistry, mineralogy and process characteristics in both oxide and fresh material that form the basis of the current Iron Bridge resource model. The allocation of geometallurgical characteristics in terms of concentration amenability and concentrate characteristics on a block-by-block basis over the whole project allows for an optimum mine schedule and plant feed. This ensures that the desired concentrate characteristics and mass recovery can be better predicted over the life-of-mine, thereby improving the mine's economics and stability by derisking the mine schedule and optimising the performance of the concentrators. A key benefit of the geomet code devised for the Iron Bridge mine is that it can be attributed in an automated manner to all samples analysed for a routine XRF analytical suite, from exploration to blasthole drilling. This allows each sample to be allocated to a geometallurgical material type with predictable process response in terms of concentrate mass recovery and concentrate quality without the need to complete systematic DTR testing. A standard multivariate analysis coupled with a cluster analysis has allowed the linking of interdisciplinary results between geology, mineralogy, geochemistry, process and metallurgy to better understand, predict and ultimately mine and process the Iron Bridge deposits. This allows plant operations and product quality to be optimised through each stage thanks to the predictable ore characteristics embedded in the mining model.
机译:铁桥磁铁矿矿山和基础设施项目目前正在开发作为强幻金属集团,Formosa和Baosteel之间的合资企业,它由X射线荧光(XRF)分析的反向循环钻孔样品的广泛数据库支持,具有大通过Davis管回收(DTR)测试测试浓缩质量回收,浓缩和尾等级的亚级测试。有限数量的岩石物理测试结果,包括无束缚/单轴抗压强度和破碎工作指数,完成了数据库。通过组合所有可用的信息 - 测定,DTR结果,地质,地层,矿物学和岩石物理结果 - 以及使用多元统计分析技术,概述了控制浓缩质量,质量回收和磨削特性的关键因素的影响。通过使用组合的XRF-DTR数据使用集群分析技术来创建一组地球化学组。这些组允许用始终如一的高浓缩Fe等级和质量恢复最佳地分离材料。这种方法优于基于地层测井或质量恢复的统计,因为它通常用于标准磁铁矿估计模型。利用规范性矿物学研究的结果,主要地球化学基团被赋予其地球化学特性的矿物质简介。这些发现进一步完善了对样品的过程特征与地球化学签名和矿物学之间的联系的理解。在头部等级和DTR集中质量恢复上定义的地球化学分组是基于常规测定的头部等级的“几何”代码之一,从而绕过了对系统DTR测试的需求。几何代码识别具有均匀地球化学,矿物质的空间域,氧化物和新材料中的矿物质和工艺特征,形成当前铁桥资源模型的基础。在整个项目中逐块基础的浓缩扫抚性和浓缩特性的几何特征分配允许最佳的矿井时间表和植物饲料。这确保了所需的浓缩特性和质量恢复可以更好地预测到矿山的寿命,从而通过驾驶矿山时间表提高矿山的经济学和稳定性,并优化集中器的性能。设计为铁桥矿设计的几何代码的一个关键益处是它可以以自动化的方式归因于分析的所有样本,从勘探到普拉斯敦钻钻探。这允许每个样品分配给几何材料类型,以可预测的过程响应在浓缩质量恢复和浓缩质量方面,无需完成系统的DTR测试。与集群分析相结合的标准多变量分析允许在地质,矿物学,地球化学,过程和冶金之间连接跨学科结果,以更好地了解,预测和最终挖掘和处理铁桥沉积物。这允许通过在矿业模型中嵌入的可预测的矿石特性来通过每个阶段进行植物操作和产品质量。

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    《Iron Ore Conference》|2015年||共12页
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    A Manfrino;

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