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Towards Automated Logging of Ore: Positive Identification of Sulphides in the Ores of Agnico Eagle Kittilä and New Boliden Mines
2015 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Drill core logging in the mining industry has traditionally been done by geologists and technicians using basic tools such as a loupe, knife, and magnet, amongst others. The descriptions are usually time-consuming, qualitative, subjective and require the use of expensive complementary techniques, i.e. chemical assays, for acquisition of precise information. Mineralogical and textural relations valuable for the beneficiation stages in a geometallurgical approach are usually not considered; therefore, techniques that allow automated logging and a more detailed characterisation of the ores are necessary for a mineralogical-oriented logging system. Hyperspectral imaging has been recently used in the iron ore industry since the main iron minerals (i.e. hematite, goethite, jarosite) are easily distinguished with this technique. Hyperspectral imaging in the sulphide and gold ore industry is not as extended and is focused on an exploration level, as alteration minerals indicators of the mineralized areas are easily traceable. However, no direct detection of sulphide minerals is at the moment possible with the available commercial techniques. Possible sulphide discrimination and characterisation of their textural relations during logging would allow better knowledge of the ore and a better behaviour forecasting in the beneficiation process. Tests for sulphide detection have only been performed with microwave heating under infra-red thermography for ore gradation and sulphide detection purposes.This Master Thesis presents the results of a mineralogical and textural characterisation of three different sulphide-bearing ores of both orogenic gold and polymetallic VMS deposits from the northern Fennoscandian Shield. A detailed mineralogical and textural characterisation using optical microscopy, SEM-EDS and XRD is included for the evaluation of newly tested techniques. Hyperspectral imaging in different bandwidths and resolutions is evaluated for mineral detection. For the orogenic gold ores, hyperspectral imaging could be used for exploration purposes as the proximal areas to the mineralization presented different mineral responses than the distal ones. For the polymetallic VMS ores, not all alteration minerals of interest for the characterisation of the main lithologies within the deposit were detectable in hyperspectral imaging. Moreover, the high-resolution hyperspectral scans did not provide additional mineralogical information for the technique to be implemented at a mine production scale.The development of new techniques using IR thermography are promising and indicated the potential to detect and characterize sulphide minerals using illuminating sources, and the possibility to discriminate between sulphides using heat sources, i.e. laser heating. Sulphide minerals reflected slightly higher thermal radiation than the non-sulphide mineralogy in the blowtorch technique and the presented well defined contours for the medium- to coarse-sulphide grains. The finest sulphide grains were also detected as higher thermal responses were observed in within the fine silicate-matrix. In the laser technique, galena and pyrite grains could be differentiated from sphalerite and non-sulphide minerals. However, no distinct responses between pyrite and arsenopyrite could be obtained.The tests performed indicate that the use of combined techniques is required for full automation of drill core logging in the mineralogically complex ores from orogenic and polymetallic VMS gold. Additionally, more research needs to be performed for reduction of the subjectivity, easiness of the techniques setups, and possibility to achieve quantitative mineralogy for early forecasting in a geometallurgical context.

Place, publisher, year, edition, pages
Keyword [en]
Technology, logging, sulphide minerals, hyperspectral imaging, SWIR, LWIR, IR thermography
Keyword [sv]
URN: urn:nbn:se:ltu:diva-56842Local ID: d95d3ae7-49b9-40f4-a40b-40623fad416fOAI: diva2:1030229
Subject / course
Student thesis, at least 30 credits
Educational program
Natural Resources Engineering, master's
Validerat; 20150807 (global_studentproject_submitter)Available from: 2016-10-04 Created: 2016-10-04Bibliographically approved

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