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首页> 外文会议>The First AusIMM International Geometallurgy Conference 2011. >Estimating Mineralogy in Bulk Samples
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Estimating Mineralogy in Bulk Samples

机译：估计散装样品中的矿物学

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摘要

This paper looks at two ways to estimate the bulk mineralogy of the rocks for assay intervals.rnThe aim is to fi nd an effi cient indicator of the most common minerals in the rock. Phase (modal)rnanalysis has traditionally been done using visual methods such as point counting and imagernanalysis. A modern version of this process is the X-ray point counting routine using the SEM-EDSrnbased software. These methods are too slow and expensive for routine analysis of bulk samplernmineralogy at the normal assay spacing.rnTwo sources of data were considered that provide information that can be used to determinernthe mineral abundance in assay samples. The most widely applied method is (semi-) quantitativernX-ray diffraction (QXRD). The QXRD method is most applicable to major minerals and has limitedrnapplication to minerals at low abundance. The nominal detection limit is 0.5 per cent. Valuesrnbelow fi ve per cent have large errors. A second, less common, method is calculation of mineralogyrnfrom chemical assay data. Conversion of chemical analyses to mineralogical analyses depends onrnthe unique chemical composition of each mineral. Elements only found in one mineral are easilyrnaccounted for, but many compositions are ambiguous. Deciding on the actual mineralogy is notrnsimple. Recalculation of mineral mode from chemical analyses is more accurate than QXRD whenrnthe correct minerals, and mineral compositions, are known.rnWhere only a few QXRD analyses are available they can be used to setup a protocol for calculationrnof mineralogy from assay data. Linear programming works well in this environment. The bestrnresults are obtained when both H_2O and CO_2 are directly measured. Loss-on-ignition (LOI) shouldrnbe included if these are not available.rnWhere both QXRD and chemical analysis are available for all samples, the best results arernobtained using the least squared method to merge the data sets assuming QXRD has much higherrnanalytical errors than chemical assays. The combined method provides more robust results becausernthe high abundance minerals are controlled by the QXRD measurements while the chemical assaysrnimprove the precision for low abundance minerals.
机译：本文研究了两种方法来估算检测间隔内岩石的整体矿物学。目的是找到岩石中最常见矿物的有效指标。相位（模态）分析传统上是使用视觉方法（例如点计数和图像分析）完成的。此过程的现代版本是使用基于SEM-EDSrn的软件进行的X射线点计数例程。这些方法对于常规分析间隔下的大体积样品矿物学的常规分析而言太慢且昂贵。考虑了两个数据源，它们提供了可用于确定分析样品中矿物质丰度的信息。应用最广泛的方法是（半）定量X射线衍射（QXRD）。 QXRD方法最适用于主要矿物，而对低丰度矿物的应用范围有限。名义检出限为0.5％。低于百分之五的值有很大的误差。第二种较不常用的方法是根据化学分析数据计算矿物学。化学分析向矿物学分析的转化取决于每种矿物的独特化学组成。仅在一种矿物中发现的元素很容易被解释，但是许多组成是模棱两可的。确定实际的矿物学并非易事。当已知正确的矿物和矿物成分时，通过化学分析进行矿物模式的重新计算要比QXRD更为准确。在只有少数QXRD分析可用的地方，它们可用于建立从测定数据中计算矿物学的方案。线性编程在这种环境下效果很好。直接测量H_2O和CO_2可获得最佳结果。如果所有样品均不能使用QXRD和化学分析，则应使用点燃损失（LOI）.rn假设QXRD的分析误差比化学分析高得多，则使用最小二乘法合并数据集可获得最佳结果分析。结合的方法提供了更可靠的结果，因为高丰度矿物受QXRD测量控制，而化学分析提高了低丰度矿物的精度。

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  • 来源
  • 会议地点 Brisbane(AU);Brisbane(AU)
  • 作者

    R Berry; J Hunt; S McKnight;

  • 作者单位

    GeMIII Group, CODES – University of Tasmania, Hobart Tas 7005. Email: ron.berry@utas.edu.au;

    GeMIII Group, CODES – University of Tasmania, Hobart Tas 7005. Email: julie.hunt@utas.edu.au;

    Geology and Metallurgy – School of Science and Engineering, University of Ballarat, Mount Helen Vic 3350. Email: s.mcknight@ballarat.edu.au;

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  • 正文语种 eng
  • 中图分类 微生物冶金;微生物冶金;
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