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Applications of Industrial Computed Tomography in the Mining Sector

Industrial computed tomography (CT) is a non-destructive X-ray computerized method for studying the three-dimensional (3D) distribution and microtexture of phases within individual solid samples. For geological and mineral product samples, CT allows visualization of phases with significant density contrast as well as the recognition of gas and fluid inclusions. Also, the technique precisely defines the in-situ location of minerals of interest. In this paper, we summarize CT principles and present examples of unique 3D information for selected ore types. For the mining sector, CT scanning of mineral resources and their products provides valuable information throughout the mining value chain, from exploration to mining to metallurgical extraction.

Authors/Autoren: Leonard Krebbers M.Sc., Dr. rer. nat. Ramil Gainov, Univ.-Prof. Bernd G. Lottermoser Ph.D., Dr. rer. nat. Stephanie Lohmeier, Dr.-Ing. Alexander Hennig, Institute of Mineral Resources Engineering (MRE), RWTH Aachen University, Aachen/Germany

1  Introduction

Material characterization is an important and fundamental aspect in the raw materials sector. Throughout the mining value chain, which includes everything from mining the resource to delivering products to customers, processes are monitored by mineralogical, physical and chemical methods to improve the quantity and quality of mineral products or concentrates. Hence, all steps of the value chain are usually accompanied by sampling and measurements in the production sequence. Traditionally, such characterization of mineral resources and their products involves the study of minerals in terms of their size, habit, chemistry, morphology, textural position, association and other phase attributes such as solubility or hardness. Mineralogical tools like the electron microprobe provide valuable information on the quantity, composition and distribution of individual phases and in some cases reveal two-dimensional (2D) information on mineral abundances and their textural arrangements. However, these established techniques require sample preparation and cannot produce three-dimensional (3D) images of phase distributions. Such a lack of geometrical information may lead to incorrect interpretations on mineral sizes and abundances (1), which in turn, may lead to sub-optimal recovery and quality of mineral products and concentrates.

Industrial computed tomography (CT) is a newly established, non-destructive X-ray computerized method for studying multicomponent materials and constructions in a 3D regime. It is currently the only method that allows the observation and analysis of internal and external microstructures of objects without sample preparation and without strong limitations on the size and shape of the objects studied. CT can also reveal volume, shape, grain size distribution and connectivity of pores, present phases and cracks. Unlike 2D imaging, CT 3D imaging can confirm not only the presence of these parameters, but CT can usually quantify them.

Moreover, the technology can be used to study geological samples as well as concrete and construction materials and may be applied to material and damage analysis of manufactured goods, including plastics, wood, building materials, metals, and composite hybrid materials (2, 3). In the last decade, the application of CT 3D imaging to geological and mineral product samples has grown significantly (4, 5, 6, 7).

In this paper, we summarize CT principles and present examples of unique CT 3D imaging for samples of diverse mineral resources. The study describes recent experiences with the innovative method and discusses the perspectives of the technique and possible applications in the raw materials sector. Results of this contribution demonstrate that CT is an additional powerful analytical tool for the mining sector throughout the mining value chain, from exploration to mining, mineral processing, and metallurgical extraction (8, 9, 10, 11).

2  Computed tomography

CT measures the attenuation of an X-ray that passes through a sample object. The X-ray attenuation depends on the material density and atomic number (12). High density materials absorb more X-ray energy than low density materials. The X-ray attenuation is therefore characteristic for each phase of which the sample is composed. A 3D – CT measurement procedure is basically the collection of sample projections. These are taken at a pre-set time interval as the sample object rotates usually stepwise between the X-ray source and the detector. The projections are then reconstructed to create 2D slices. Each slice thereby represents a certain thickness of the scanned sample. The resulting data are considered raw data, which are then processed into a full 3D image via a reconstruction software.

In general, solid samples of any type are suitable for CT analysis. The only sample preparation requirement for scanning is that one has to ensure that the sample material fits between X-ray source and X-ray detector. Sample mounting involves the use of low-density material. This holds the sample on a rotation stage and at the same time separates it from the dense rotation stage hardware. The appropriate scanning parameters are then set up in the measurement software interface of the CT scanner according to the unique properties of the sample material. Before starting the measurement, a calibration is necessary to establish the characteristics of the X-ray signal as read by the detectors under scanning conditions. The measurement or scanning time depends on the chosen parameters and usually takes a few hours. After reconstruction, the 3D image is then further processed depending on the goal of the analysis.

Since January 2020, a newly established CT laboratory is operational at the Institute of Mineral Resources Engineering (MRE), RWTH Aachen University, Aachen/Germany (Figure 1).

Fig. 1. CT equipment consisting of motion system (1), detector (2), measuring PC (3), X-ray tube (4) and sample holder (5). Source: MRE

The acquired CT scanner „ProCon CT-Alpha“ is designed to meet the requirements from various fields of research, including the mining, geological, biological and archaeological sciences and engineering disciplines. The CT scanner has a high level of flexibility due to its large measuring cabinet, strong X-ray tube reaching 240 kV, large panel detector, and five-axes system of X-Y-Z-rotation-tilting. Large samples with a diameter of up to 600 mm can be analysed and resolutions down to 5 µm are possible.

3  Material characterization in the mining sector

3.1  Established techniques

Throughout the mining value chain, processes are monitored by mineralogical, physical and chemical methods to optimize quality and quantity of the mineral products or concentrates. Various mineralogical methods are applied to understand and solve challenges encountered during exploration and mining as well as processing of ores, concentrates, smelter products, and related materials. The applied techniques characterize minerals and materials and the acquired data are then interpreted to provide information relevant for exploration, mineral processing, tailings disposal and treatment, hydrometallurgy, pyrometallurgy, and refining.

To date, various techniques have been developed for mineral characterization, such as optical microscopy (OM), scanning electron microscopy equipped with an energy or wave length dispersive X-ray analyzer (SEM/E-WDX), environmental scanning electron microscopy (E-SEM), electron microprobe analyser (EMPA), proton-induced X-ray analyzer (PIXE), secondary ion mass spectrometer (SIMS), infra-red spectrometry (IR), cathodoluminescence (CL), laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), and X-ray diffraction (XRD) (e. g., 10, 13, 14; Table 1).

Table 1. Common analytical techniques used for the characterisation of mineralogical properties and dimensional geometries of geological ores and their products. Source: MRE

Results of these techniques provide information on the presence and properties of minerals in raw materials and allow an improved understanding of mineral behaviour during resource processing. In some cases, the acquired information cannot be related to any dimensional geometries of the analysed samples, e. g., IR, XRD, whereas others techniques allow 2D visualization of the obtained mineralogical data, e. g., OM, SEM, EMPA (Table 1).

In view of the fact that ores and mineral deposits and their products represent 3D arrays of mineral assemblages, there is a need to acquire information on the 3D distribution of phases within ores, wastes and mineral products to achieve optimal material characterization and manufacturing of mineral products. Hence, in the following, recent experiences with the innovative CT method are documented.

3.2 Industrial computed tomography

3.2.1  Gold ore

There are several different types of gold ore deposits worldwide, however, most common to hard-rock gold deposits is a mineral paragenesis comprising native or invisible gold and different sulfides, especially pyrite, arsenopyrite and diverse base metal sulfides. The invisible gold occurs as gold metal, submicron- to nano-sized particles or as chemically bound gold in sulfide phases. Moreover, gold is obtained as a by-product as from large copper and molybdenum porphyries or originates from the artisanal mining of surficial gold ores. Thus, sulfide minerals, e. g., arsenopyrite, pyrite, chalcopyrite, pyrrhotite, galena, are commonly associated with gold in hard-rock ore deposits. The presence of abundant sulfide minerals in gold ores does not only impact on leaching efficiencies during cyanide extraction, it may also lead to acid rock drainage (ARD) in tailings storage facilities, waste rock dumps or heap leach piles.

To date, a number of investigations have documented the occurrence and distribution of gold in diverse ores using CT imaging (15). Results of these works have demonstrated that gold is of favorable density for CT imaging (e. g., 8, 16, 17, 18). In this study, a representative gold ore sample was obtained from the Porgera gold-silver mine, Papua New Guinea. Disseminated Porgera ore is characterized by fine-grained sulfides, comprising largely pyrite, marcasite, sphalerite, galena, pyrrhotite and freibergite present within a propylitic altered mudstone. In addition, there is a veinlet-related sulfide mineralization with carbonaceous quartz-gold-roscoelite veinlet-infill. CT imaging of these veinlets reveals three different phases of different density ranges, comprising gold, gangue minerals and diverse sulfides (19). High-density gold particles appear as bright objects, whereas less dense sulfide particles are distinctly paler (Figure 2).

Fig. 2. 3D visualisation of a gold ore sample from the Porgera gold-silver mine, Papua New Guinea (sample diameter approximately 7 cm). The yellow phase represents native gold. Note its skeletal texture. The blue coloured phases represent non-differentiated sulfides. Gangue material is shaded in light grey. Source: MRE

The low-density carbonate-mica-quartz gangue infill is reflected by greyish colors. Gold particles can be identified and particles sizes recorded. By contrast, the majority of sulfide particles occur as small grains that are disseminated throughout the ore matrix. These sulfides do not only show on the surfaces of the hand specimen, but a cloud of sulfides occurs in the entire rock volume. Normally this information would require systematic dissection of the specimen and the examination of many polished sections and/or a geochemical assay of the sample. Consequently, CT scanning provides valuable information on gold and sulfide abundances and particle distribution. Such data are of major interest for mineral processing and ARD risk assessment.

3.2.2  Salt ore

Rock salt and potash deposits contain the crystallised minerals derived from the evaporation of sea-water and intracontinental lakes. Rock salt deposits contain halite, ranging in grain size from a few micrometres to some decimetres, with intercalations and impurities of other phases, including gypsum, anhydrite, clay or MgCl2 salts. By contrast, potash ore is composed of different K-bearing minerals such as sylvite, carnallite, bi-schofite and kieserite. Impurities of halite and other evaporate minerals plus clay are common. CT has successfully been applied to salt core samples to visualise the spatial distribution of fluid inclusions and to quantify the sample’s porosity (20). Also, Hammer et al. (2015) successfully used CT to visualize the distribution of hydrocarbons in rock salt samples and, based on these findings, calculated the amount of hydrocarbons within their samples (21). In addition, CT imaging has been performed on rock salt samples to map anhydrite impurities expressed as clusters or layers (22).

To illustrate the application of CT on salt ores, a representative sample was used from the Hessian-Thuringian salt district in Germany. The sample is composed of large subhedral to euhedral intergrown crystals of halite and sylvite. In addition, some portions of anhydrite are present. CT image analysis of the sample reveals three different grey value ranges which can be referred to halite (dark grey), sylvite (medium grey), as well as anhydrite (light gray) (Figure 3).

Fig. 3. Representative tomographic 2D slice image of salt ore from the Hessian-Thuringian salt district in Germany, showing grey-scale differentiation of halite (H), sylvite (S) and anhydrite (A). The red and blue coloured areas indicate the volumetric fraction of sylvite in the specimen in a selected rectangle area. Source: MRE

Cracks and cleavages are also apparent. CT imaging shows that the grain boundaries of the salt minerals are interlocked or irregular, respectively, and are thus not controlled by the minerals’ cleavage. Locally, sylvite is enclosed by halite. Furthermore, anhedral anhydrite appears occasionally as infill between large halite and smaller sylvite crystals and along halite cleavage planes.

CT scanning of hardrock salt samples can be used to calculate the modal salt components and provides valuable information on particle sizes and distributions. Such data are of major interest for salt processing. Moreover, CT imaging may allow to assess the detailed distribution of anhydrite within salt deposits and thus contributes to mine safety as sulfate intercalations are potential zones of mechanical weakness (31).

3.2.3  Graphite ore

Commercial sources of graphite are found in a variety of geological settings and result from the conversion of carbonaceous matter through metamorphic processes into graphite (graphitization). Graphite ore bodies can be quite variable, with graphite occurring as tiny layers, larger seams, lenses, and as veins, locally forming stockworks. Moreover, graphite can occur as part of breccia matrix or forms disseminations within metamorphic host rock. Three types of graphite are known: microcrystalline graphite, flake graphite and vein graphite. Generalized, the metamorphic facies and overprinting fluids dictate the grain size of graphite ore and the bulk mineral assemblage and thus the economic significance of graphite ores (23). To date, mineralogical investigations of graphite ores have been carried out only by a combination of established techniques as outlined above. However, CT is suited to distinguish between less-dense graphite (density of 2.26 g/cm3) and denser minerals forming the groundmass, i. e. quartz with a density of 2.65 g/cm3.

To demonstrate the applicability of CT on graphite ores, a representative example from Tanzania was chosen. Graphite occurs in an altered foliated schist in which foliation is defined by sub-parallel oriented medium-grained graphite flakes. The groundmass is composed of quartz with minor feldspar, kaolinite, zoisite, altered biotite and secondary minerals (clay minerals and iron oxy-hydroxides). CT imaging reveals six different grey colour values which can be assigned to 1) graphite, 2) combined quartz and feldspar, 3) kaolinite, 4) combined zoisite and biotite, 5) limonite, and 6) clay minerals (Figure 4).

Fig. 4. Representative tomographic 2D slice image of graphite ore, showing greyscale differentiation of graphite (C), zoisite (Z), kaolinite (K), combined quartz and feldspar (Qtz + Fs), clay minerals (CM), combined zoisite and biotite (Z+Bt), and limonite (L) in a graphite gneiss sample from Tanzania. The white box shows a selected region of interest with segmented volume of aligned subhedral graphite flakes. Source: MRE

Graphite flakes occur as dark items, whereas denser minerals have brighter colours in CT images. Iron oxy-hydroxides are the brightest phases as they have the highest densities in the present mineral assemblage. In addition, CT imaging illustrates the distribution and orientation of graphite crystals as well as the subhedral, tabular, and flaky shape of graphite which range in volume from 0.04 to 0.95 mm3.

As purity and grain size are the factors that set the graphite price, CT analysis can be used to evaluate quantity and type(s) of impurities in graphite concentrate after crushing and grinding. In addition, CT can be used to measure flake sizes. All these are valuable information for improving mineral liberation and process design for further purification.

3.2.4  Copper ore

Copper minerals are usually found in nature in association with sulfur-bearing minerals. Copper metal is generally produced from mining and processing of low-grade ores containing copper as copper sulfides, oxides, sulfates and rarely as native copper. In calc-alkaline porphyry-Cu deposits, the ore is characterized by disseminated chalcopyrite, chalcocite, bornite and pyrite, whereas iron oxides and pyrrhotite are part of the mineral assemblage in alkaline types. Covellite and copper sulfosalts evolved during supergene or hypogene overprints and can form high-grade ores, which are currently mined, e. g., in the Andean cordillera. Depending on the conditions during formation (invisible) gold, silver and molybdenite are associated with copper minerals or with pyrite.

CT scanning has been conducted to obtain mineralogical and textural data on different copper ores. The technique was applied to differentiate, successfully, between copper minerals, which have relatively similar densities (24). Moreover, CT has been used to assess the liberation characteristics of porphyry copper ore (25, 26). Figure 5 shows the CT image of a porphyry copper ore drill core sample.

Fig. 5. Rendered 3D CT image of a porphyry-copper ore drill core sample from the Grasberg mine, Indonesia (sample diameter approximately 6 cm). The rainbow colour range marks the volumetric distribution of the Cu-mineralisation with minor pyrite. Cu-mineralisation either is disseminated or occurs as veinlet infill (stockworks). The non-coloured parts of the rock model correspond to gangue material. Source: MRE

The sample is composed of fine-grained Cu sulfides (predominantly chalcopyrite) present within a groundmass of quartz and minor feldspar. Moreover, there is a veinlet-infill of Cu sulfides and minor pyrite. CT imaging of the copper ore reveals two different phases of density ranges, comprising sulfides and gangue material. Cu sulfides appear as bright objects. Low-density groundmass (quartz, feldspar) is reflected by greyish colours. CT image analysis reveals a disseminated sulfide assemblage as it is typical for such ore. Also, it exposes the typical veinlet mineralisation, represented by two small quartz veinlets with Cu sulfide infill and minor pyrite. Volumetric image segmentation of Cu sulfides turns it into a simple task to identify these structures as stockwork mineralisation, or truncating veinlets, more specifically, due to the offset of the diagonal veinlet. As stockwork veinlets are pathways and traps for mineralising fluids, recognition of the 3D distribution of stockwork formations and related disseminated mineralisation is critical for exploration and mine design of porphyry deposits.

Porphyry-Cu deposits are generally characterized by large tonnages and low-grade ores, with the copper being hosted by various ore minerals and host rocks. Different alteration assemblages are common and indicative, and such materials have to be treated differently during ore processing and their mechanical instability have to be considered for geotechnical mine planning and assessments. Therefore, CT helps to differentiate between different copper-ore minerals from groundmass phases and allows the recognition of variable altered and overprinted host rocks, some of them with poor mechanical stability.

4  Outlook

CT analysis is a powerful tool for imaging 3D details of natural or synthetic materials on a micron scale. The technique can be applied to any ore where the density contrast between target minerals and gangue material(s) can be resolved. Such CT image based analysis provides quantitative 3D microstructural information, e. g., grain sizes and distributions, mineral orientations, shapes, intergrowth characteristics, porosity and cracks, as shown before that cannot obtained by any other technique. In the mining industry, CT may become part of ore characterisation studies to provide a better understanding of ore mineralogy and parameters required to optimise exploration, mining, comminution and refining of the extracted and processed resources. Moreover, recent developments in CT technology allow the application of small CT scanners at mine sites to scan core samples and to obtain 3D images of mineral distributions in drill cores at mine and exploration sites. Thus, the technology now moves from the laboratory to production sites.

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Authors/Autoren: Leonard Krebbers M.Sc., Dr. rer. nat. Ramil Gainov, Univ.-Prof. Bernd G. Lottermoser Ph.D., Dr. rer. nat. Stephanie Lohmeier, Dr.-Ing. Alexander Hennig, Institute of Mineral Resources Engineering (MRE), RWTH Aachen University, Aachen/Germany