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Research in quantitative mineralogy: Examples from diverse applications
Minerals Engineering 22 (2009) 402–408
Contents lists available at ScienceDirect
Minerals Engineering journal homepage: www.elsevier.com/locate/mineng
Research in quantitative mineralogy: Examples from diverse applications K.O. Hoal a,*, J.G. Stammer a, S.K. Appleby a, J. Botha a, J.K. Ross a, P.W. Botha b a b
Advanced Mineralogy Research Center, Colorado School of Mines, 1310 Maple St., Golden, CO 80401, USA Intellection Corporation, 10955 Westmoor Dr., Westminster, CO 80021, USA
a r t i c l e
i n f o
Article history: Received 6 October 2008 Accepted 6 November 2008 Available online 27 December 2008 Keywords: Quantitative mineralogy Research Geology Geomet Ores
a b s t r a c t Developed for the mining industry and applied to oil and gas projects, quantitative mineralogy also has enormous potential as a research tool. The Advanced Mineralogy Research Center at Colorado School of Mines was developed for this purpose, and several representative ongoing research projects using QEMSCANÒ techniques are described herein. Geomet applications relate mineralogy and geology to potential processing attributes such as hardness and grind characteristics. For kimberlite exploration and development, and diamond petrogenesis, quantitative mineralogy reveals the complex secondary silicate mineralogy in volcanic and mantle materials, and provides a means of viewing garnets from exploration samples. In Carlin-type gold deposits, the distribution of arsenian-pyrite can serve as a proxy for the distribution of gold. Monzonites from porphyry copper deposits reveal pervasive potassic alteration and quartz veining, which may impact the behavior of the materials during processing. A new view of feldspar zoning in granites not only has broad implications for understanding the petrogenetic evolution of magmatic systems, but is of relevance in processing feldspar-bearing materials. Environmental and biological applications include soil mineralogy, the effect of soil chemistry on vegetation, and studies of mammalian tissues. These examples illustrate how automated mineralogy allows researchers a means of quantifying mineralogical relationships in a wide variety of materials. Ó 2008 Elsevier Ltd. All rights reserved.
1. Introduction The Advanced Mineralogy Research Center at Colorado School of Mines (Mines) is dedicated to research and new applications development in quantitative mineralogy. Mines is unique among universities in the world, with expertise in a wide variety of resource-related areas as well as in pure science and engineering. In part, a result of this diversity of available technical capabilities, the AMRC opened its doors in April with some 20 research projects already in development. Projects in the resources sector make up the bulk of initial activities and range from geometallurgy and copper and gold mining to oil shales and petroleum reservoir characterization. Developing research projects in geological, environmental, biological, and planetary sciences also are in progress. Interdisciplinary research is important, with emphasis on communication across key areas to provide for new insights into mineral characterization in a wide variety of sciences. In contrast to common departmental research initiatives, the diversity of projects in quantitative mineralogy enables cross-pollination of ideas among mining, energy, and environmental sciences. Individual sample challenges, identification of complex mineral associations, difficult ore horizons or processing development issues that may not be re* Corresponding author. E-mail address: [email protected] (K.O. Hoal). 0892-6875/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.mineng.2008.11.003
solved in an industry setting can be better handled in a dedicated research environment. This interdisciplinary environment presents challenges as well, such as developing training programs on an oncall basis that depend on the level of participation by the researcher. 2. Analytical methods This paper provides an overview of some current research applications in quantitative mineralogy using QEMSCANÒ technology, a scanning electron microscope platform with four energy dispersive X-ray spectrometers, allowing for fast acquisition of X-ray signals to determine mineral abundances in dust- to rock-size samples. Mining applications include examination of the distribution of economic minerals in surrounding materials and the determination of their optimum recovery methods based on mineralogy. Beyond mining, quantitative mineralogy is also being applied to the oil and gas sector in the examination of oil shales and pore throat mineralogy, as well as to coal, environmental, planetary, medical, and other applications where mineralogy is a key factor in material characterization. iDiscoverÒ software accommodate queries and new views of materials. The QEMSCANÒ system combines a fully automated Carl Zeiss EVO5O scanning electron microscope platform with four Bruker silicon-drift energy dispersive (EDS) X-ray detectors, a four-quadrant
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K.O. Hoal et al. / Minerals Engineering 22 (2009) 402–408
J0001
Letšeng Satellite Pipe CQG942
CQG928
0
20
40 60 Mass (%)
80
100
Pyroxene Olivine Chlorite Serpentine 1 Serpentine 2 Amphibole Ca Silicate CaCO3 Boundary Mg-Fe-Si phase Si-Mg-Ca phase Others K-Feldspar Calcite Dolomite
Fig. 1. False-colored images, modal abundances, and mineral list for three samples of Letšeng Satellite Pipe, Lesotho kimberlites. The samples define a distinct population defined by the modal assemblage.
Fig. 2. False-colored digital images of pyrite grains (light, centers) with arsenian rims (darker) from the Chukar Forrwall deposit, Nevada. Sub-micron-sized gold occurs in arsenian-pyrite rims within Carlin-type systems. Identification of arsenian-pyrite can be used as a proxy for gold mineralization.
solid-state backscatter electron detector, and a secondary electron detector (Fig. 2). The system further uses an energy resolution of 133 eV (Mn Ka), peltier cooling (no liquid nitrogen), an accelerating voltage of 25 kV, a specimen current of 5 nA on the Faraday Cup, a working distance of 24 mm, and a stage Z distance of 18 mm. The beam diameter is typically 0.25–0.5 lm. The four EDS-detector array allows for fast acquisition of data (commonly 150 analyses per second) and enables the automated analysis of large sample populations for delivering statistically reliable data sets. iDiscover software automates the stepping of the electron beam across samples at a user-defined pixel resolution, typically 520 lm and down to 12 lm resolution (Fig. 3). At each pixel, the system collects a BSE signal and EDS spectrum and correlates them with predefined mineral definitions developed for the system and for the material. These definitions and correlations are assessed quite closely by the scientist to ensure data quality and accurate representation of the materials. The product is a false-colored image of the material with a large dataset of digital information that can then be queried and displayed in many applications. 3. Research project overviews Three of the studies presented below fall into the area of geomet, examining mineral characterization for potential process
development impacts. The fourth study presented below is a vivid illustration of carefully fine-tuning the technique to provide important compositional variation information. The fifth study illustrates and environmental application in the field of medical geology and environmental science. 3.1. Geomet and diamond deposits Geomet investigations require thorough mineral characterization of geological and ore materials during process development (Hoal, 2008; Hoal et al., 2006). This includes developing an understanding of the field relationships in a deposit and the distribution of ore and gangue minerals throughout domains that are defined on the basis of process attributes. Quantitative mineralogy is increasingly applied in this context to metal deposits, where the improved understanding of the mineralogy has benefits for liberation studies, comminution behavior, and flotation dynamics, among other aspects of a mining operation. Benvie (2007) demonstrated how automated mineralogy analysis can be applied to kimberlites, the most common lithological host of primary diamond deposits. Diamond ores are highly variable in composition, mineralogy, grain and fragment size, and grade within a deposit. In addition, kimberlites are typically porous and friable materials to handle and analyze. Nevertheless, diamond projects are prime examples of the diverse ways
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Fig. 3. Modal mineralogy of monzonite intrusive rocks from a porphyry copper deposit. Pervasive alteration has resulted in a relatively homogenous assemblage of quartz, plagioclase, potassium feldspar, and biotite with kaolinite, chlorite, and illite alteration. Two of the samples are crosscut by quartz–calcite veins and contain larger modal abundances of calcite.
that mineral characterization studies can improve the researcher’s understanding of the nature of materials. Several ongoing diamond projects relate to the variable nature of diamond deposits, from exploration to processing and development. Projects related to diamonds include peridotite xenolith thin sections from Premier (Cullinan) mine, which provide a better understanding of mantle metasomatism and related minerals, and ultimately of diamond-bearing capacity. Current work also is focused on the examination of garnet concentrates that are produced by diamond exploration projects. Thousands of grains typically are analyzed in each project to determine the potential prospectivity of a target. We are reinterpreting the compositions of garnets from some southern African locations in terms of the diamond exploration applications of quantitative mineralogy. In addition to the G10–G9 classification system developed by microprobe techniques (e.g. Gurney and Moore, 1993), it appears that rapid assessment of the full elemental spectrum can add valuable detail to these large sample populations. Thin slabs of kimberlite rocks from Letšeng Satellite Pipe (C. Palmer, pers. comm.) illustrate the variable mineralogical and textural relationships that may impact process development, from the presence of foreign crust- and mantle-derived lithic fragments to the pervasive serpentine–chlorite alteration that accompanies emplacement and post-emplacement events. These quantifiable relationships impact the geotechnical behavior of an ore body, as outlined by Jakubec (2004), and Jakubec et al. (2004). Fig. 1 illustrates how the mineralogy of fine-grained matrix material in kimberlite, typically difficult to distinguish by optical microscopy, was quantified using the technique. The three slabs were polished and analyzed at 20 lm resolution, and the mineral list used is one that is under current refinement for use in kimberlitic materials generally. The modal abundances in Fig. 1 are dominated by high percentages of clinopyroxene and chlorite. The related textural variations represent the presence of magmaclasts and multiple
phases of the kimberlitic magma. Combined, these aspects of the kimberlite are anticipated to impact the hardness of the ore materials and the manner in which they can be predicted to break in the crushing and grinding circuit. The example from Letšeng Satellite Pipe is important as this particular deposit that has produced a number of large diamonds. 3.2. Sediment-hosted Carlin-type deposits Quantitative mineralogy analysis is used in this study to detect micron-sized gold particles in silty carbonate rocks at the Chukar Footwall deposit in northeastern Nevada, USA. This is a new tool applied to understanding hydrothermal mineralization and alteration in Carlin-type gold systems. Gold mineralization in sediment-hosted Carlin-type deposits generally occurs as sub-micronsized particles or in solid solution in rims of arsenian-pyrite and marcasite (Stammer, 2008). Because of this cryptic relationship and the sub-micron grain sizes, it is difficult to characterize the association of arsenian-pyrite and gold in the fine-grained rocks of this deposit type. Three quotations from previous studies on sub-micron gold in Carlin-type systems illustrate the difficulty in understanding this mineralization using traditional analytical methods. Bakken et al. (1989, p. 171) wrote, ‘‘The number of sightings of gold particles within the practical detection limits of most SEMs do not account for the concentration of gold that is present in the ore as determined by fire assay.” Wells and Mullens (1973, p. 192) noted, ‘‘Chemical analyses and thin section petrography of the ore tell little about the actual distribution of gold and associated elements.” Finally, Arehart et al. (1993, p. 178) observed that, ‘‘Arsenic–gold correlations in pyrite in Carlin-type ore is much more difficult to determine because of the presence of gold-free pyrite.” Over the last 40 years, numerous technologies have been used to study sub-micron gold in Carlin-type deposits including transmis-
K.O. Hoal et al. / Minerals Engineering 22 (2009) 402–408
sion electron microscopy (TEM), secondary ion mass spectrometry (SIMS), X-ray absorption near edge structure (XANES) spectroscopy, and high angle annular dark field – scanning transmission electron microscopy (HAADF–STEM). In this study, the quantitative mineralogy system, QEMSCANÒ, was used as a new application to complement these other technologies. It is a quick but rigorous and important step in understanding gold distribution and associated mineralogy. Because gold in the Chukar deposit samples is sub-micron in size, it has not been detected using traditional optical microscopy and scanning electron microscopy techniques. However, because of the known relationship between arsenic and gold in these systems, QEMSCANÒ was employed to detect trace levels of arsenic in various sulfide minerals as a proxy for gold. Ten thin sections were cut and prepared from both core and rib samples. The system initially analyzed the thin sections at a 10 lm resolution to provide mineralogical and textural information. Subsequently, the backscatter threshold was raised to selectively identify sulfides in the sample. Then the system re-scanned and digitally separated the sulfide grains from the gangue minerals. Pyrite and other sulfide minerals were then re-analyzed at a 1 lm resolution to detect minor enrichments in arsenic as a proxy for gold. The maximum resolution of the electron beam used by the instrument is 0.5 lm too low to detect individual gold grains. However, the arsenic-search capability allowed the system to quickly identify and target potential gold-bearing grains that could then be reanalyzed at higher resolution. This technique demonstrates one way in which individual mineral species can be located and analyzed in the context of a solid material and investigated for trace element chemistry. Quantitative mineralogy techniques can be used as a new research tool to rapidly identify arsenic-rims on pyrite as a proxy for gold, which expedites the process of searching for potential gold-bearing grains. 3.3. Mineralogy in a porphyry copper deposit Optical microscopy and quantitative mineralogical analysis are integrated in this study to determine the relationship between mineralogy and rock breakage characteristics of different ore types and lithologic units at a porphyry copper mine. Quantitative mineralogical analysis provides insights into the mineralogical and textural associations in ore materials that may not be apparent in traditional analytical techniques. Modal abundances of ore and gangue mineralogy, the distribution of secondary and alteration phases, and the fracture and vein distribution have important implications for comminution test work. Preliminary measurements of monzonite-dominant geometallurgical domains show that the extensive potassic alteration of the intrusive rocks has resulted in a fairly homogenous mineral assemblage of potassium feldspar, plagioclase, quartz, biotite, and clays (Fig. 3). The relative proportions of quartz, biotite, feldspars, and clays, and the distribution of fractures and veins, are the most likely attributes to impact the comminution behavior. Mineralogical measurements of the surrounding metamorphosed country rocks, including skarn, limestone, and quartzite samples, show that the mineralogy is highly variable and may be more difficult to correlate with breakage tests. Detailed quantitative mineralogical analysis integrated with comminution and metallurgical tests can better highlight sulfide associations, leading to better predictive capabilities. 3.4. Feldspar mineralogy: an example from the Scottish late Caledonian granites Plagioclase feldspar and K-feldspar make up approximately 60 vol% of the continental crust. As they typically crystallize early
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during magma evolution they contain a wealth of information about the rock’s history, beginning at its molten state and ending at its solid-state. Traditionally, feldspar compositions and, in particular, changes in chemical composition with crystal growth have been investigated using optical microscopy, electron probe microanalysis, isotopic analysis, and cathodoluminescence. All these methods have been shown to be powerful tools, but are typically labor intensive as well as expensive. Due to the latter, analyses are commonly conducted on a small number of samples that are considered representative. However, in particular data collected in situ (e.g. electron probe data) can be biased by stereological affects not readily apparent by optical microscopy. In comparison, automated mineral analysis is an inexpensive and fast analytical method that enables assessment of a larger number of samples, but as the technique was originally developed for the mining industry it has not yet established itself in other fields of geology where the detection of minor compositional variations is essential. The aim of this automated mineralogy study is to develop the capability of determining variations in plagioclase composition in the order of approximately 10%, and subsequently, employ the technique to investigate zoning patterns in plagioclase crystals, a typical phenomenon resulting during cooling and crystallization of igneous rocks. Normally, with decreasing temperatures plagioclase changes from anorthite- to albite-rich compositions creating a simple unidirectional zoning pattern (Bowen, 1913). However, an increasing number of studies have demonstrated that zoning is commonly much more complex (e.g. Ginibre et al., 2007). This is generally interpreted to either reflect temperature and/or pressure changes during crystallization (Hattori and Sato, 1996), or as evidence for open-system events (e.g. repeated magma mixing with more mafic magmas) during a magma’s evolution (Luhr and Melson, 1996). For this study two examples (the Lochnagar and Etive plutons) from the Scottish late Caledonian (425–400 Ma) granites were selected. Previous ion microprobe analysis of zircon from these plutons revealed intra- and inter-crystal oxygen isotope heterogeneities that were interpreted to represent magma mixing events (Appleby et al., 2008). Following development of the analytical technique, we are able to demonstrate that the QEMSCANÒ instrument is capable of determining anorthite contents in plagioclase, and may therefore be used to map changes in composition of approximately 10%. With respect to the Scottish Caledonian granites several observations may be made: (1) It is evident that to a limited extent differences in plagioclase composition exist between the Lochnagar and Etive plutons (Fig. 4a and b). (2) Larger differences can be observed within different facies of a single pluton. In both plutons samples of more mafic composition (i.e. diorites, tonalites) comprise the full range of plagioclase compositions and are dominated by anorthite contents of An35–45; albite (An0–10) is only present in low abundances (Fig. 4a and b). This indicates that in mafic phases plagioclase crystallization occurred early in the magma’s evolution and at high temperatures. In contrast, plagioclase crystals in more felsic granite samples typically show anorthite contents between An35–45 and An0–10, and are dominated by albite (An0–10). (3) Differences in anorthite content were also detected within individual plagioclase crystals in a single sample. In some samples zoning appears to be ‘normal’ and unidirectional with the crystal center being anorthite-rich and the rim albite-rich. However, most samples display multidirectional plagioclase zoning indicating a more complex petrogenetic history (Fig. 4c). Interestingly, plagioclase zoning does not appear to correlate with zircon oxygen isotope data as even samples with homogenous zircon oxygen isotopes display complex plagioclase zoning. An explanation for this may be that plagioclase records open-system events that occurred in the very early stages
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a Lochnagar
b Etive
Order of emplacement
granite
granite tonalite
granite granodiorite
granite
granodiorite granodiorite
granite granite granite diorite
granite granite granite
diorite
granodiorite tonalite
diorite
Fig. 4. (a and b) Bar charts display differences in plagioclase compositions between the Lochnagar and Etive plutons, and between phases within the plutons; (c) false-colored image of a plagioclase crystal showing complex oscillatory zoning (Etive pluton, sample St-05).
of the magma’s evolution well before zircon crystallization. However, more detailed work is required to test this hypothesis. 3.5. Biological and environmental applications Quantitative mineral analysis is being used in various biological and environmental applications including: soils and vegetation, teeth and bone, and infectious diseases. Using QEMSCANÒ it was shown that where there is a distinct difference in the mineralogy and chemistry of soils there is also a distinct difference in dominant vegetation species. Doing ICP-AES analysis on the same soil and vegetation samples the same trends were observed. Other studies have also shown that soil chemistry can be reflected in the chemical composition of vegetation (Álvarez et al., 2003). As a preliminary study to examine the use of quantitative mineralogy in biological applications, samples of baboon teeth from southern Africa as well as African lion toe bones were used for experimental analysis. From these studies, it was possible to distinguish between and quantify the dentine and enamel components within the teeth (Fig. 5a) as well as distinguish different types of apatite within the lion bone (Fig. 5b). The enamel and dentine mainly differ with respect to the presence of minor amounts of magnesium and sodium and the results from the lion bone analysis showed at least three types of apatite, which differs mainly with respect to the presence of chlorine, sodium and magnesium.
These results demonstrate that quantitative mineralogical analysis can be used to link vegetation chemistry to the soils it grows in and to identify minor compositional differences in hard biological tissue samples. This leads to an additional application, which involves the investigation of the mineral composition of lesions caused by bovine tuberculosis, present in soft and hard tissue of infected mammals. It has also been shown that elevated levels of certain elements in soil can increase the prevalence of bovine tuberculosis in mammals (Purdey, 2006), therefore quantitative mineral analysis can be used to produce a database of soil mineralogy, which can be related to the prevalence of bovine tuberculosis in mammals over a certain terrain. The goal of these studies is to investigate the relationship between soil mineralogy, local vegetation distribution and composition, and the occurrence and composition of bovine tuberculosis lesions in the hard and soft tissue of southern African large mammals.
4. Conclusions Quantitative mineralogy lends itself to the research environment because it adds the metric: the capability to manipulate and assess datasets derived from mineralogical relationships. There is a huge potential in new applications development to the technique in a research setting. Mineral and mining projects benefit from the additional information gained during geometallurgy
K.O. Hoal et al. / Minerals Engineering 22 (2009) 402–408
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Fig. 5. (a) Digital phase map of lion toe bone showing the compositional differences in apatite and (b) digital phase map of baboon teeth showing the compositional differences between enamel and dentine.
analysis, and also from the interdisciplinary spinoffs that may result from side-by-side projects in geology, energy and environmental research. The challenge is to identify the important project goals, and to refine the mineralogical definitions to each project. For kimberlites, mineralogical characterization means proving key information on modal abundances. As illustrated by the porphyry copper example, such information may ultimately impact predictions of breakage behavior. Where gold is sub-micron-sized, mineralogical characterization enables arsenic-rims on pyrite to be a proxy for the gold. And importantly, research into the nature of mineral compositional variations, as illustrated by plagioclase feldspar, opens new areas for understanding the geological conditions and processes that are the keys to understanding ores and other materials. Research should be a key component of resource-based quantitative mineralogical characterization studies, since each material contains new clues to liberation and extraction. In each of the above examples, primary and secondary mineral assemblages and mineral compositional changes can be related to geological processes that have a direct impact on how a material is anticipated to behave. Taking the time and up-front cost to untie these relationships and to quantify them may mean a smaller environmental footprint, lower operational costs, reduced project risk, and increased project vale down the line.
Acknowledgements We thank Intellection Pty Ltd., and Intellection Corporation for the partnership developed with Colorado School of Mines to develop the Advanced Mineralogy Research Center and to make it a reality. A number of research collaborators have assisted with and made possible the projects described in this paper: C. Palmer (CSIR
Natural Resources and the Environment and Gem Diamond Technical Services), Newmont Mining Corporation, M. Hitzman (Colorado School of Mines), P. Highsmith (NTX), S. Nelson (Kennecott Utah Corp.,), D. Latti (Rio Tinto Technical Services, Pty), N. Kelly (Colorado School of Mines), C. Graham (University of Edinburgh), M. Gillespie (British Geological Survey), C. Skinner (Yale University), and A. Butcher (Intellection Pty Ltd.). References Álvarez, E., Fernándes Marcos, M.L., Vaamonde, C., Fernández-Sanjurjo, M.J., 2003. Heavy metals in the dump of an abandoned mine in Galicia (NW Spain) and in the spontaneously occurring vegetation. The Science of the Total Environment 313, 158–197. Appleby, S.K., Graham, C.M., Gillespie, M.R., Hinton, R.W., Oliver, G.J.H., EIMF, 2008. A cryptic record of magma mixing in diorites revealed by high-precision SIMS oxygen isotope analysis of zircons. Earth and Planetary Science Letters 269, 105–117. Benvie, B., 2007. Mineralogical imaging of kimberlites using SEM-based techniques. Minerals Engineering 20, 435–443. Bowen, N.L., 1913. The melting phenomena of the plagioclase feldspars. American Journal of Science 35, 577–599. Ginibre, C., Wörner, G., Kronz, A., 2007. Crystal zoning as an archive for magma evolution. Elements 3, 261–266. Gurney, J.J., Moore, R.O., 1993. Geochemical correlations between kimberlitic indicator minerals and diamonds. In: Diamonds: Exploration, Sampling, and Evaluation, Proceedings of a Short Course Presented by the Prospectors and Developers Association of Canada, pp. 147–172. Hattori, K., Sato, H., 1996. Magma evolution recorded in plagioclase zoning in 1991 Pinatubo eruption products. American Mineralogist 81, 982–994. Hoal, K.O., 2008. Getting the geo into geomet. SEG Newsletter, Society of Economic Geologists 73 (April). pp. 1, 11–15. Hoal, K.O., McNulty, T.P., Schmidt, R., 2006. Metallurgical Advances and their Impact on Mineral Exploration and Mining. Society of Economic Geologists Special Publication 12. pp. 243–261. Jakubec, J., 2004. Role of geology in diamond project development. Lithos 76, 337– 345. Jakubec, J., Long, L., Nowicki, T., Dyck, D., 2004. Underground geotechnical and geological investigations at Ekati Mines–Koala North: case study. Lithos 76, 347–357.
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Luhr, J.F., Melson, W.G., 1996. Mineral and composition in June 15, 1991 pumices: evidence for dynamic disequilibrium in the Pinatubo dacite. In: Punogbayan, R.S., Newhall, C.G. (Eds.), Fire and Mud Eruptions of Lahars of Mount Pinatubo, Philippines, pp. 733–750. Purdey, M., 2006. Anti-lactoferrin toxicity and elevated iron: the environmental prerequisites which activate susceptibility to tuberculosis infection? Medical Hypotheses 66, 513–517.
Stammer, J., 2008. Geochemical and Mineralogical Analysis of the Chukar Footwall Gold Deposit. Northeastern Nevada, Colorado School of Mines, Master of Science Thesis, 85 pp. 1993.
Contents lists available at ScienceDirect
Minerals Engineering journal homepage: www.elsevier.com/locate/mineng
Research in quantitative mineralogy: Examples from diverse applications K.O. Hoal a,*, J.G. Stammer a, S.K. Appleby a, J. Botha a, J.K. Ross a, P.W. Botha b a b
Advanced Mineralogy Research Center, Colorado School of Mines, 1310 Maple St., Golden, CO 80401, USA Intellection Corporation, 10955 Westmoor Dr., Westminster, CO 80021, USA
a r t i c l e
i n f o
Article history: Received 6 October 2008 Accepted 6 November 2008 Available online 27 December 2008 Keywords: Quantitative mineralogy Research Geology Geomet Ores
a b s t r a c t Developed for the mining industry and applied to oil and gas projects, quantitative mineralogy also has enormous potential as a research tool. The Advanced Mineralogy Research Center at Colorado School of Mines was developed for this purpose, and several representative ongoing research projects using QEMSCANÒ techniques are described herein. Geomet applications relate mineralogy and geology to potential processing attributes such as hardness and grind characteristics. For kimberlite exploration and development, and diamond petrogenesis, quantitative mineralogy reveals the complex secondary silicate mineralogy in volcanic and mantle materials, and provides a means of viewing garnets from exploration samples. In Carlin-type gold deposits, the distribution of arsenian-pyrite can serve as a proxy for the distribution of gold. Monzonites from porphyry copper deposits reveal pervasive potassic alteration and quartz veining, which may impact the behavior of the materials during processing. A new view of feldspar zoning in granites not only has broad implications for understanding the petrogenetic evolution of magmatic systems, but is of relevance in processing feldspar-bearing materials. Environmental and biological applications include soil mineralogy, the effect of soil chemistry on vegetation, and studies of mammalian tissues. These examples illustrate how automated mineralogy allows researchers a means of quantifying mineralogical relationships in a wide variety of materials. Ó 2008 Elsevier Ltd. All rights reserved.
1. Introduction The Advanced Mineralogy Research Center at Colorado School of Mines (Mines) is dedicated to research and new applications development in quantitative mineralogy. Mines is unique among universities in the world, with expertise in a wide variety of resource-related areas as well as in pure science and engineering. In part, a result of this diversity of available technical capabilities, the AMRC opened its doors in April with some 20 research projects already in development. Projects in the resources sector make up the bulk of initial activities and range from geometallurgy and copper and gold mining to oil shales and petroleum reservoir characterization. Developing research projects in geological, environmental, biological, and planetary sciences also are in progress. Interdisciplinary research is important, with emphasis on communication across key areas to provide for new insights into mineral characterization in a wide variety of sciences. In contrast to common departmental research initiatives, the diversity of projects in quantitative mineralogy enables cross-pollination of ideas among mining, energy, and environmental sciences. Individual sample challenges, identification of complex mineral associations, difficult ore horizons or processing development issues that may not be re* Corresponding author. E-mail address: [email protected] (K.O. Hoal). 0892-6875/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.mineng.2008.11.003
solved in an industry setting can be better handled in a dedicated research environment. This interdisciplinary environment presents challenges as well, such as developing training programs on an oncall basis that depend on the level of participation by the researcher. 2. Analytical methods This paper provides an overview of some current research applications in quantitative mineralogy using QEMSCANÒ technology, a scanning electron microscope platform with four energy dispersive X-ray spectrometers, allowing for fast acquisition of X-ray signals to determine mineral abundances in dust- to rock-size samples. Mining applications include examination of the distribution of economic minerals in surrounding materials and the determination of their optimum recovery methods based on mineralogy. Beyond mining, quantitative mineralogy is also being applied to the oil and gas sector in the examination of oil shales and pore throat mineralogy, as well as to coal, environmental, planetary, medical, and other applications where mineralogy is a key factor in material characterization. iDiscoverÒ software accommodate queries and new views of materials. The QEMSCANÒ system combines a fully automated Carl Zeiss EVO5O scanning electron microscope platform with four Bruker silicon-drift energy dispersive (EDS) X-ray detectors, a four-quadrant
403
K.O. Hoal et al. / Minerals Engineering 22 (2009) 402–408
J0001
Letšeng Satellite Pipe CQG942
CQG928
0
20
40 60 Mass (%)
80
100
Pyroxene Olivine Chlorite Serpentine 1 Serpentine 2 Amphibole Ca Silicate CaCO3 Boundary Mg-Fe-Si phase Si-Mg-Ca phase Others K-Feldspar Calcite Dolomite
Fig. 1. False-colored images, modal abundances, and mineral list for three samples of Letšeng Satellite Pipe, Lesotho kimberlites. The samples define a distinct population defined by the modal assemblage.
Fig. 2. False-colored digital images of pyrite grains (light, centers) with arsenian rims (darker) from the Chukar Forrwall deposit, Nevada. Sub-micron-sized gold occurs in arsenian-pyrite rims within Carlin-type systems. Identification of arsenian-pyrite can be used as a proxy for gold mineralization.
solid-state backscatter electron detector, and a secondary electron detector (Fig. 2). The system further uses an energy resolution of 133 eV (Mn Ka), peltier cooling (no liquid nitrogen), an accelerating voltage of 25 kV, a specimen current of 5 nA on the Faraday Cup, a working distance of 24 mm, and a stage Z distance of 18 mm. The beam diameter is typically 0.25–0.5 lm. The four EDS-detector array allows for fast acquisition of data (commonly 150 analyses per second) and enables the automated analysis of large sample populations for delivering statistically reliable data sets. iDiscover software automates the stepping of the electron beam across samples at a user-defined pixel resolution, typically 520 lm and down to 12 lm resolution (Fig. 3). At each pixel, the system collects a BSE signal and EDS spectrum and correlates them with predefined mineral definitions developed for the system and for the material. These definitions and correlations are assessed quite closely by the scientist to ensure data quality and accurate representation of the materials. The product is a false-colored image of the material with a large dataset of digital information that can then be queried and displayed in many applications. 3. Research project overviews Three of the studies presented below fall into the area of geomet, examining mineral characterization for potential process
development impacts. The fourth study presented below is a vivid illustration of carefully fine-tuning the technique to provide important compositional variation information. The fifth study illustrates and environmental application in the field of medical geology and environmental science. 3.1. Geomet and diamond deposits Geomet investigations require thorough mineral characterization of geological and ore materials during process development (Hoal, 2008; Hoal et al., 2006). This includes developing an understanding of the field relationships in a deposit and the distribution of ore and gangue minerals throughout domains that are defined on the basis of process attributes. Quantitative mineralogy is increasingly applied in this context to metal deposits, where the improved understanding of the mineralogy has benefits for liberation studies, comminution behavior, and flotation dynamics, among other aspects of a mining operation. Benvie (2007) demonstrated how automated mineralogy analysis can be applied to kimberlites, the most common lithological host of primary diamond deposits. Diamond ores are highly variable in composition, mineralogy, grain and fragment size, and grade within a deposit. In addition, kimberlites are typically porous and friable materials to handle and analyze. Nevertheless, diamond projects are prime examples of the diverse ways
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Fig. 3. Modal mineralogy of monzonite intrusive rocks from a porphyry copper deposit. Pervasive alteration has resulted in a relatively homogenous assemblage of quartz, plagioclase, potassium feldspar, and biotite with kaolinite, chlorite, and illite alteration. Two of the samples are crosscut by quartz–calcite veins and contain larger modal abundances of calcite.
that mineral characterization studies can improve the researcher’s understanding of the nature of materials. Several ongoing diamond projects relate to the variable nature of diamond deposits, from exploration to processing and development. Projects related to diamonds include peridotite xenolith thin sections from Premier (Cullinan) mine, which provide a better understanding of mantle metasomatism and related minerals, and ultimately of diamond-bearing capacity. Current work also is focused on the examination of garnet concentrates that are produced by diamond exploration projects. Thousands of grains typically are analyzed in each project to determine the potential prospectivity of a target. We are reinterpreting the compositions of garnets from some southern African locations in terms of the diamond exploration applications of quantitative mineralogy. In addition to the G10–G9 classification system developed by microprobe techniques (e.g. Gurney and Moore, 1993), it appears that rapid assessment of the full elemental spectrum can add valuable detail to these large sample populations. Thin slabs of kimberlite rocks from Letšeng Satellite Pipe (C. Palmer, pers. comm.) illustrate the variable mineralogical and textural relationships that may impact process development, from the presence of foreign crust- and mantle-derived lithic fragments to the pervasive serpentine–chlorite alteration that accompanies emplacement and post-emplacement events. These quantifiable relationships impact the geotechnical behavior of an ore body, as outlined by Jakubec (2004), and Jakubec et al. (2004). Fig. 1 illustrates how the mineralogy of fine-grained matrix material in kimberlite, typically difficult to distinguish by optical microscopy, was quantified using the technique. The three slabs were polished and analyzed at 20 lm resolution, and the mineral list used is one that is under current refinement for use in kimberlitic materials generally. The modal abundances in Fig. 1 are dominated by high percentages of clinopyroxene and chlorite. The related textural variations represent the presence of magmaclasts and multiple
phases of the kimberlitic magma. Combined, these aspects of the kimberlite are anticipated to impact the hardness of the ore materials and the manner in which they can be predicted to break in the crushing and grinding circuit. The example from Letšeng Satellite Pipe is important as this particular deposit that has produced a number of large diamonds. 3.2. Sediment-hosted Carlin-type deposits Quantitative mineralogy analysis is used in this study to detect micron-sized gold particles in silty carbonate rocks at the Chukar Footwall deposit in northeastern Nevada, USA. This is a new tool applied to understanding hydrothermal mineralization and alteration in Carlin-type gold systems. Gold mineralization in sediment-hosted Carlin-type deposits generally occurs as sub-micronsized particles or in solid solution in rims of arsenian-pyrite and marcasite (Stammer, 2008). Because of this cryptic relationship and the sub-micron grain sizes, it is difficult to characterize the association of arsenian-pyrite and gold in the fine-grained rocks of this deposit type. Three quotations from previous studies on sub-micron gold in Carlin-type systems illustrate the difficulty in understanding this mineralization using traditional analytical methods. Bakken et al. (1989, p. 171) wrote, ‘‘The number of sightings of gold particles within the practical detection limits of most SEMs do not account for the concentration of gold that is present in the ore as determined by fire assay.” Wells and Mullens (1973, p. 192) noted, ‘‘Chemical analyses and thin section petrography of the ore tell little about the actual distribution of gold and associated elements.” Finally, Arehart et al. (1993, p. 178) observed that, ‘‘Arsenic–gold correlations in pyrite in Carlin-type ore is much more difficult to determine because of the presence of gold-free pyrite.” Over the last 40 years, numerous technologies have been used to study sub-micron gold in Carlin-type deposits including transmis-
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sion electron microscopy (TEM), secondary ion mass spectrometry (SIMS), X-ray absorption near edge structure (XANES) spectroscopy, and high angle annular dark field – scanning transmission electron microscopy (HAADF–STEM). In this study, the quantitative mineralogy system, QEMSCANÒ, was used as a new application to complement these other technologies. It is a quick but rigorous and important step in understanding gold distribution and associated mineralogy. Because gold in the Chukar deposit samples is sub-micron in size, it has not been detected using traditional optical microscopy and scanning electron microscopy techniques. However, because of the known relationship between arsenic and gold in these systems, QEMSCANÒ was employed to detect trace levels of arsenic in various sulfide minerals as a proxy for gold. Ten thin sections were cut and prepared from both core and rib samples. The system initially analyzed the thin sections at a 10 lm resolution to provide mineralogical and textural information. Subsequently, the backscatter threshold was raised to selectively identify sulfides in the sample. Then the system re-scanned and digitally separated the sulfide grains from the gangue minerals. Pyrite and other sulfide minerals were then re-analyzed at a 1 lm resolution to detect minor enrichments in arsenic as a proxy for gold. The maximum resolution of the electron beam used by the instrument is 0.5 lm too low to detect individual gold grains. However, the arsenic-search capability allowed the system to quickly identify and target potential gold-bearing grains that could then be reanalyzed at higher resolution. This technique demonstrates one way in which individual mineral species can be located and analyzed in the context of a solid material and investigated for trace element chemistry. Quantitative mineralogy techniques can be used as a new research tool to rapidly identify arsenic-rims on pyrite as a proxy for gold, which expedites the process of searching for potential gold-bearing grains. 3.3. Mineralogy in a porphyry copper deposit Optical microscopy and quantitative mineralogical analysis are integrated in this study to determine the relationship between mineralogy and rock breakage characteristics of different ore types and lithologic units at a porphyry copper mine. Quantitative mineralogical analysis provides insights into the mineralogical and textural associations in ore materials that may not be apparent in traditional analytical techniques. Modal abundances of ore and gangue mineralogy, the distribution of secondary and alteration phases, and the fracture and vein distribution have important implications for comminution test work. Preliminary measurements of monzonite-dominant geometallurgical domains show that the extensive potassic alteration of the intrusive rocks has resulted in a fairly homogenous mineral assemblage of potassium feldspar, plagioclase, quartz, biotite, and clays (Fig. 3). The relative proportions of quartz, biotite, feldspars, and clays, and the distribution of fractures and veins, are the most likely attributes to impact the comminution behavior. Mineralogical measurements of the surrounding metamorphosed country rocks, including skarn, limestone, and quartzite samples, show that the mineralogy is highly variable and may be more difficult to correlate with breakage tests. Detailed quantitative mineralogical analysis integrated with comminution and metallurgical tests can better highlight sulfide associations, leading to better predictive capabilities. 3.4. Feldspar mineralogy: an example from the Scottish late Caledonian granites Plagioclase feldspar and K-feldspar make up approximately 60 vol% of the continental crust. As they typically crystallize early
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during magma evolution they contain a wealth of information about the rock’s history, beginning at its molten state and ending at its solid-state. Traditionally, feldspar compositions and, in particular, changes in chemical composition with crystal growth have been investigated using optical microscopy, electron probe microanalysis, isotopic analysis, and cathodoluminescence. All these methods have been shown to be powerful tools, but are typically labor intensive as well as expensive. Due to the latter, analyses are commonly conducted on a small number of samples that are considered representative. However, in particular data collected in situ (e.g. electron probe data) can be biased by stereological affects not readily apparent by optical microscopy. In comparison, automated mineral analysis is an inexpensive and fast analytical method that enables assessment of a larger number of samples, but as the technique was originally developed for the mining industry it has not yet established itself in other fields of geology where the detection of minor compositional variations is essential. The aim of this automated mineralogy study is to develop the capability of determining variations in plagioclase composition in the order of approximately 10%, and subsequently, employ the technique to investigate zoning patterns in plagioclase crystals, a typical phenomenon resulting during cooling and crystallization of igneous rocks. Normally, with decreasing temperatures plagioclase changes from anorthite- to albite-rich compositions creating a simple unidirectional zoning pattern (Bowen, 1913). However, an increasing number of studies have demonstrated that zoning is commonly much more complex (e.g. Ginibre et al., 2007). This is generally interpreted to either reflect temperature and/or pressure changes during crystallization (Hattori and Sato, 1996), or as evidence for open-system events (e.g. repeated magma mixing with more mafic magmas) during a magma’s evolution (Luhr and Melson, 1996). For this study two examples (the Lochnagar and Etive plutons) from the Scottish late Caledonian (425–400 Ma) granites were selected. Previous ion microprobe analysis of zircon from these plutons revealed intra- and inter-crystal oxygen isotope heterogeneities that were interpreted to represent magma mixing events (Appleby et al., 2008). Following development of the analytical technique, we are able to demonstrate that the QEMSCANÒ instrument is capable of determining anorthite contents in plagioclase, and may therefore be used to map changes in composition of approximately 10%. With respect to the Scottish Caledonian granites several observations may be made: (1) It is evident that to a limited extent differences in plagioclase composition exist between the Lochnagar and Etive plutons (Fig. 4a and b). (2) Larger differences can be observed within different facies of a single pluton. In both plutons samples of more mafic composition (i.e. diorites, tonalites) comprise the full range of plagioclase compositions and are dominated by anorthite contents of An35–45; albite (An0–10) is only present in low abundances (Fig. 4a and b). This indicates that in mafic phases plagioclase crystallization occurred early in the magma’s evolution and at high temperatures. In contrast, plagioclase crystals in more felsic granite samples typically show anorthite contents between An35–45 and An0–10, and are dominated by albite (An0–10). (3) Differences in anorthite content were also detected within individual plagioclase crystals in a single sample. In some samples zoning appears to be ‘normal’ and unidirectional with the crystal center being anorthite-rich and the rim albite-rich. However, most samples display multidirectional plagioclase zoning indicating a more complex petrogenetic history (Fig. 4c). Interestingly, plagioclase zoning does not appear to correlate with zircon oxygen isotope data as even samples with homogenous zircon oxygen isotopes display complex plagioclase zoning. An explanation for this may be that plagioclase records open-system events that occurred in the very early stages
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a Lochnagar
b Etive
Order of emplacement
granite
granite tonalite
granite granodiorite
granite
granodiorite granodiorite
granite granite granite diorite
granite granite granite
diorite
granodiorite tonalite
diorite
Fig. 4. (a and b) Bar charts display differences in plagioclase compositions between the Lochnagar and Etive plutons, and between phases within the plutons; (c) false-colored image of a plagioclase crystal showing complex oscillatory zoning (Etive pluton, sample St-05).
of the magma’s evolution well before zircon crystallization. However, more detailed work is required to test this hypothesis. 3.5. Biological and environmental applications Quantitative mineral analysis is being used in various biological and environmental applications including: soils and vegetation, teeth and bone, and infectious diseases. Using QEMSCANÒ it was shown that where there is a distinct difference in the mineralogy and chemistry of soils there is also a distinct difference in dominant vegetation species. Doing ICP-AES analysis on the same soil and vegetation samples the same trends were observed. Other studies have also shown that soil chemistry can be reflected in the chemical composition of vegetation (Álvarez et al., 2003). As a preliminary study to examine the use of quantitative mineralogy in biological applications, samples of baboon teeth from southern Africa as well as African lion toe bones were used for experimental analysis. From these studies, it was possible to distinguish between and quantify the dentine and enamel components within the teeth (Fig. 5a) as well as distinguish different types of apatite within the lion bone (Fig. 5b). The enamel and dentine mainly differ with respect to the presence of minor amounts of magnesium and sodium and the results from the lion bone analysis showed at least three types of apatite, which differs mainly with respect to the presence of chlorine, sodium and magnesium.
These results demonstrate that quantitative mineralogical analysis can be used to link vegetation chemistry to the soils it grows in and to identify minor compositional differences in hard biological tissue samples. This leads to an additional application, which involves the investigation of the mineral composition of lesions caused by bovine tuberculosis, present in soft and hard tissue of infected mammals. It has also been shown that elevated levels of certain elements in soil can increase the prevalence of bovine tuberculosis in mammals (Purdey, 2006), therefore quantitative mineral analysis can be used to produce a database of soil mineralogy, which can be related to the prevalence of bovine tuberculosis in mammals over a certain terrain. The goal of these studies is to investigate the relationship between soil mineralogy, local vegetation distribution and composition, and the occurrence and composition of bovine tuberculosis lesions in the hard and soft tissue of southern African large mammals.
4. Conclusions Quantitative mineralogy lends itself to the research environment because it adds the metric: the capability to manipulate and assess datasets derived from mineralogical relationships. There is a huge potential in new applications development to the technique in a research setting. Mineral and mining projects benefit from the additional information gained during geometallurgy
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Fig. 5. (a) Digital phase map of lion toe bone showing the compositional differences in apatite and (b) digital phase map of baboon teeth showing the compositional differences between enamel and dentine.
analysis, and also from the interdisciplinary spinoffs that may result from side-by-side projects in geology, energy and environmental research. The challenge is to identify the important project goals, and to refine the mineralogical definitions to each project. For kimberlites, mineralogical characterization means proving key information on modal abundances. As illustrated by the porphyry copper example, such information may ultimately impact predictions of breakage behavior. Where gold is sub-micron-sized, mineralogical characterization enables arsenic-rims on pyrite to be a proxy for the gold. And importantly, research into the nature of mineral compositional variations, as illustrated by plagioclase feldspar, opens new areas for understanding the geological conditions and processes that are the keys to understanding ores and other materials. Research should be a key component of resource-based quantitative mineralogical characterization studies, since each material contains new clues to liberation and extraction. In each of the above examples, primary and secondary mineral assemblages and mineral compositional changes can be related to geological processes that have a direct impact on how a material is anticipated to behave. Taking the time and up-front cost to untie these relationships and to quantify them may mean a smaller environmental footprint, lower operational costs, reduced project risk, and increased project vale down the line.
Acknowledgements We thank Intellection Pty Ltd., and Intellection Corporation for the partnership developed with Colorado School of Mines to develop the Advanced Mineralogy Research Center and to make it a reality. A number of research collaborators have assisted with and made possible the projects described in this paper: C. Palmer (CSIR
Natural Resources and the Environment and Gem Diamond Technical Services), Newmont Mining Corporation, M. Hitzman (Colorado School of Mines), P. Highsmith (NTX), S. Nelson (Kennecott Utah Corp.,), D. Latti (Rio Tinto Technical Services, Pty), N. Kelly (Colorado School of Mines), C. Graham (University of Edinburgh), M. Gillespie (British Geological Survey), C. Skinner (Yale University), and A. Butcher (Intellection Pty Ltd.). References Álvarez, E., Fernándes Marcos, M.L., Vaamonde, C., Fernández-Sanjurjo, M.J., 2003. Heavy metals in the dump of an abandoned mine in Galicia (NW Spain) and in the spontaneously occurring vegetation. The Science of the Total Environment 313, 158–197. Appleby, S.K., Graham, C.M., Gillespie, M.R., Hinton, R.W., Oliver, G.J.H., EIMF, 2008. A cryptic record of magma mixing in diorites revealed by high-precision SIMS oxygen isotope analysis of zircons. Earth and Planetary Science Letters 269, 105–117. Benvie, B., 2007. Mineralogical imaging of kimberlites using SEM-based techniques. Minerals Engineering 20, 435–443. Bowen, N.L., 1913. The melting phenomena of the plagioclase feldspars. American Journal of Science 35, 577–599. Ginibre, C., Wörner, G., Kronz, A., 2007. Crystal zoning as an archive for magma evolution. Elements 3, 261–266. Gurney, J.J., Moore, R.O., 1993. Geochemical correlations between kimberlitic indicator minerals and diamonds. In: Diamonds: Exploration, Sampling, and Evaluation, Proceedings of a Short Course Presented by the Prospectors and Developers Association of Canada, pp. 147–172. Hattori, K., Sato, H., 1996. Magma evolution recorded in plagioclase zoning in 1991 Pinatubo eruption products. American Mineralogist 81, 982–994. Hoal, K.O., 2008. Getting the geo into geomet. SEG Newsletter, Society of Economic Geologists 73 (April). pp. 1, 11–15. Hoal, K.O., McNulty, T.P., Schmidt, R., 2006. Metallurgical Advances and their Impact on Mineral Exploration and Mining. Society of Economic Geologists Special Publication 12. pp. 243–261. Jakubec, J., 2004. Role of geology in diamond project development. Lithos 76, 337– 345. Jakubec, J., Long, L., Nowicki, T., Dyck, D., 2004. Underground geotechnical and geological investigations at Ekati Mines–Koala North: case study. Lithos 76, 347–357.
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