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The Per Geijer iron ore deposits: Characterization based on mineralogical, geochemical and process mineralogical methodsKrolop, Patrick 04 April 2022 (has links)
The Per Geijer iron oxide-apatite deposits are important potential future resources for Luossavaara-Kiirunavaara Aktiebolag (LKAB), which has been continuously mining magnetite/hematite ores in northern Sweden for almost 130 years. The Per Geijer deposits reveal a high phosphorus content and vary from magnetite-dominated to hematite-dominated ores, respectively. The high phosphorus concentration of these ores results from highly elevated content of apatite as gangue mineral. Reliable, robust, and qualitative characterization of the mineralization is required as these ores inherit complex mineralogical and textural features. The precise mineralogical information obtained by optical microscopy, SEM-MLA and Raman improves the characterization of ore types and will benefit future processing strategies for this complex mineralization. The different approaches demonstrate advantages and disadvantages in classification, imaging, discrimination of iron oxides, and time consumption of measurement and processing. A comprehensive mineral-chemical dataset of magnetite, hematite and apatite obtained by electron microprobe analysis (EPMA) and LA-ICP-MS from representative drill core samples is presented. Magnetite, four different types of hematite and five types of apatite constitute the massive orebodies: Primary and pristine magnetite with moderate to high concentrations of Ti (∼61–2180 ppm), Ni (∼11–480 ppm), Co (∼5–300 ppm) and V (∼553–1831 ppm) indicate a magmatic origin for magnetite. The presence of fluorapatite and associated monazite inclusions and disseminated pyrite enclosed by magnetite with high Co:Ni ratios (> 10) in massive magnetite ores are consistent with a high temperature (∼ 800°C) genesis for the deposit. The different and abundant types of hematite, especially hematite type I, state subsequent hydrothermal events.
Chromium, Ni, Co and V in both magnetite and hematite have low concentrations in terms of current product regulations and thus no effect on final products in the future. In terms of a possible future hematite product, titanium seems to be the most critical trace element due to very high concentrations in hematite types I and IV, of which type I is most abundant in zones dominated by hematite. Further interest on other products is generated due to the high variability of hematite and apatite in some of these ores.
Information obtained from comminution test works in the laboratory scale can be utilized to characterize ore types and to predict the behavior of ore during comminution circuit in the industrial scale. Comminution tests with a laboratory rod and ball mill of 13 pre-defined ore types from the Per Geijer iron-oxide apatite deposits were conducted in this study. The highest P80 values were obtained by grinding in the rod mill for 10 minutes only (step A). Grinding steps B (25 min ball mill) and C (35 min ball mill) reveal very narrow P80 values. Ore types dominated by hematite have significantly higher P80 values after the primary grinding step (A), which indicates different hardness of the ore types. P80 values are generally lowest after the secondary grinding step C ranging between 26 µm (ore type M1a) and 80 µm (ore type H2a). Generally, Fe content increases in the finer particle size classes while CaO and P contents decrease. The influence of silica or phosphorus seems to be dependent on the dominant iron oxide. Magnetite-dominated ore types are more likely to be affected in their comminution behavior by the presence of the silicates. Contrary, hematite-dominant ore types are rather influenced by the presence of apatite. The difference in the degree of liberation of magnetite and hematite between ore types depends rather on size fractions than the amount of gangue in the ore. Davis tube data indicates that magnetite can be separated from gangue quite efficiently in the magnetite-dominated ore types. Contrary to magnetite ore, hematite-dominated ore types cannot be processed by DT. It is favored to use strong magnetic separation in order to achieve a desirable hematite concentrate. The magnetic material recovered by DT is most efficiently separated at an intensity current of 0.2 A, whereas above 0.5 A the separation process is neglectable. Based on comminution and magnetic separation tests a consolidation to eight ore types is favored which supports possible future mining of the Per Geijer deposits.:Contents
ABSTRACT ……………………………………………………………………… I
CONTENTS ……………………………………………………………………… II
LIST OF FIGURES AND TABLES ……………………………………………… IV
LIST OF ABBREVIATIONS ……………………………………………… V
1 INTRODUCTION ……………………………………………………… 1
1.1 Background and motivation of study ……………………………… 2
1.2 Previous and current work on the Per Geijer deposits ……………… 3
1.3 The need for mineral processing and in-situ ore description ……………… 4
1.4 General and generic aspects on iron oxide apatite deposits ……………… 5
Chapter A
2 REGIONAL GEOLOGY ………………………………………………. 7
2.1 Local geology of the Kiruna area ……………………………………… 7
2.2 Geology of the Per Geijer deposits ……………………………………… 9
3 METHODOLOGY ……………………………………………………… 12
3.1 Core sampling and preparation ……………………………………… 12
3.2 SEM – MLA in-situ ore ……………………………………………… 14
3.3 Electron Probe Microanalyses (EPMA) ……………………………… 15
3.3.1 Iron oxide measurements ……………………………………… 15
3.3.2 Apatite measurements ……………………………………… 15
3.4 In-situ LA-ICP-MS ……………………………………………………… 16
3.5 Whole-rock geochemistry ……………………………………………… 18
3.5.1 Exploration drill core assays ……………………………… 18
3.5.2 Chemical assays of rock chips ……………………………… 18
4 RESULTS ……………………………………………………………… 19
4.1 Pre-definition of ore types ………………………………...……………. 19
4.2 Mineralogy of in situ ore ……………………………………………… 21
4.2.1 Ore Type M1a ……………………………………………… 21
4.2.2 Ore Type M1b ……………………………………………… 22
4.2.3 Ore Type M2a ……………………………………………… 23
4.2.4 Ore Type M2b ……………………………………………… 25
4.2.5 Ore Type HM1b ……………………………………………… 26
4.2.6 Ore Type HM2a ……………………………………………… 27
4.2.7 Ore Type HM2b ……………………………………………… 28
4.2.8 Ore Type H1a ……………………………………………… 29
4.2.9 Ore Type H1b ……………………………………………… 30
4.2.10 Ore Type H2a ……………………………………………… 31
4.2.11 Ore Type H2b ……………………………………………… 32
4.2.12 Comparison of ore types ……………………………………… 33
4.3 Geochemistry of in situ ore types ……………………………… 36
4.3.1 Whole-rock chemical assays of drill cores ……………………… 36
4.3.2 Whole-rock geochemistry of rock chips ……………………… 39
4.4 Mineral chemistry of iron oxides ……………………………………… 42
4.4.1 Iron oxides and associated minerals ……………………………… 42
4.4.2 Mineral chemistry of magnetite from Per Geijer ……………… 43
4.4.3 Mineral chemistry of hematite from Per Geijer ……………… 47
4.5 Mineral chemistry of apatite ……………………………………… 51
4.5.1 Apatite and associated minerals ……………………………… 51
4.5.2 Mineral chemistry of apatite from Per Geijer ……………… 53
Chapter B
5 COMMINUTION TESTS ……………………………………………… 58
5.1 Methodology of comminution tests ……………………………………… 59
5.1.1 Sampling for comminution tests ……………………………… 59
5.1.2 Comminution circuit ……………………………………………… 61
5.1.3 Energy consumption calculation ……………………………… 62
5.1.4 SEM – MLA ……………………………………………………… 64
6 MAGNETIC SEPARATION TESTS ……………………………… 65
6.1 Methodology of magnetic separation by Davis magnetic tube ……… 66
6.2 Davis magnetic tube tests for characterization of the Per Geijer ore types 66
6.3 Separation analysis based on the Henry-Reinhard charts .……………... 67
7 RESULTS OF COMMINUTION OF ORE TYPES ……………………… 69
7.1 General characteristics of magnetite-dominated ore types ……………… 69
7.2 General characteristics of hematite-dominated ore types ……………… 72
7.3 General characteristics of magnetite/hematite-mixed ore types ……… 75
7.4 General characteristics of low-grade ore types ……………………… 77
7.5 Mineral liberation characteristics of magnetite-dominated ore types 79
7.6 Mineral liberation characteristics of hematite-dominated ore types 83
7.7 Mineral liberation characteristics of magnetite/hematite-mixed ore types 87
7.8 Mineral liberation characteristics of low-grade ore types ……………… 90
7.9 Total energy consumption of ore types from the Per Geijer deposits 94
8 RESULTS OF MAGNETIC SEPARATION OF ORE TYPES ……… 95
8.1 Magnetic separation of magnetite-dominated ore types ……………… 95
8.2 Magnetic separation of hematite-dominated ore types ……………… 96
8.3 Magnetic separation of magnetite/hematite-mixed ore types ……………… 97
8.4 Magnetic separation of low-grade ore types ……………………………… 98
8.5 Henry-Reinhard charts ……………………………………………… 99
9 DISCUSSION ……………………………………………………… 101
9.1 Mineralogy of the in-situ ore types from the Per Geijer deposits ……… 101
9.2 Geochemistry of the in-situ ore types from the Per Geijer deposits ……… 103
9.3 Mineral chemistry of iron oxides from the Per Geijer deposits ……… 105
9.4 Mineral chemistry of apatite from the Per Geijer deposits ……………… 114
9.5 Comminution of ore types from Per Geijer ……………………… 119
9.6 Magnetic separation of ore types from Per Geijer ……………………… 120
9.7 Issues with process mineralogy of in-situ and grinded ore types ……… 121
10 CONCLUSIONS ……………………………………………………… 128
11 IMPLICATIONS FOR FUTURE WORK ……………………………… 131
12 REFERENCES ……………………………………………………………… 134
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Oxygen and iron isotope systematics of the Grängesberg Mining District (GMD), Central SwedenWeis, Franz January 2013 (has links)
Iron is the most important metal for modern industry and Sweden is the number one iron producer in Europe. The main sources for iron ore in Sweden are the apatite-iron oxide deposits of the "Kiruna-type", named after the iconic Kiruna ore deposit in Northern Sweden. The genesis of this ore type is, however, not fully understood and various schools of thought exist, being broadly divided into "ortho-magmatic" versus the "hydrothermal replacement" approaches. This study focuses on the origin of apatite-iron oxide ore of the Grängesberg Mining District (GMD) in Central Sweden, one of the largest iron reserves in Sweden, employing oxygen and iron isotope analyses on massive, vein and disseminated GMD magnetite, quartz and meta-volcanic host rocks. As a reference, oxygen and iron isotopes of magnetites from other Swedish and international iron ores as well as from various international volcanic materials were also analysed. These additional samples included both "ortho-magmatic" and "hydrothermal" magnetites and thus represent a basis for a comparative analysis with the GMD ore. The combined data and the derived temperatures support a scenario that is consistent with the GMD apatite-iron oxides having originated dominantly (ca. 87 %) through ortho-magmatic processes with magnetite crystallisation from oxide-rich intermediate magmas and magmatic fluids at temperatures of 600 °C to 900 °C. A minor portion of the GMD magnetites (ca. 13 %), exclusively made up of vein and disseminated ore types, is in equilibrium with a high-δ18O and low-δ56Fe hydrothermal fluid at temperatures below 400 °C, indicating the existence of a hydrothermal system associated with the GMD volcano.
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Low-temperature thermochronologyStübner, Konstanze 24 November 2009 (has links) (PDF)
Die Spaltspuren-Datierung als wesentliche Methode aus dem Bereich der Niedrigtemperatur-Thermochronologie basiert auf der Zählung und Messung geätzter Spuren unter dem Mikroskop. Für eine akkurate Altersbestimmung ist daher das Verständnis der Ätzung von größter Bedeutung. Ein atomistisches Modell und eine Monte-Carlo Computersimulation erklären Ätzgruben-Formen und deren Größenwachstum. Thermochronologie wird in zwei Fallstudien angewendet: eine umfassende Studie über die tektonische Entwicklung Zentralamerikas seit dem Paläozoikum zeigt, wie Geo- und Thermochronologie, Strukturgeologie und Petrologie zusammenarbeiten können, um >400 Ma einer komplexen tektonischen Geschichte zu enträtseln. Eine thermochronologische Studie im Pamir, Tadschikistan betont vor allem die Möglichkeiten, die sich aus der Anwendung der Thermochronologie auf dem Gebiet der Geomorphologie und Neotektonik eröffnen.
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Doprovodné složky živcové suroviny ložiska Krásno - Vysoký kámen: složení a vztah k hlavní užitkové složce suroviny / Additional components of feldspar deposit of Krásno Krásno - Vysoký Kámen: composition and relation to the feldspar materialVrbický, Tomáš January 2016 (has links)
The Krasno deposit is only one active mine at Slavkovsky les. Mined are feldspars raw materials with high quality, commonly used in ceramic and glass industry. Mined raw material has a lot of additional components, which has influence on quality of raw material. Main additional components are unwanted coloring Fe oxides. Another additional components are apatite and topaz, which dont have influence on quality of raw material. The most interesting additional components of raw material are Ta - Nb, Li - Rb minerals. Currently the processing of raw material is under modernization for maximal separation high quality of feldspar material. The result of semi-processing operation shows the concentrate can be potential source of strategic raw materials as Nb - Ta or Li - Rb mineralization. For separation of these minerals and elements must be realized detailed research of selected processing and properties of these minerals. Powered by TCPDF (www.tcpdf.org)
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Low-temperature thermochronology: methodological studies and application in collisional orogensStübner, Konstanze 04 July 2008 (has links)
Die Spaltspuren-Datierung als wesentliche Methode aus dem Bereich der Niedrigtemperatur-Thermochronologie basiert auf der Zählung und Messung geätzter Spuren unter dem Mikroskop. Für eine akkurate Altersbestimmung ist daher das Verständnis der Ätzung von größter Bedeutung. Ein atomistisches Modell und eine Monte-Carlo Computersimulation erklären Ätzgruben-Formen und deren Größenwachstum. Thermochronologie wird in zwei Fallstudien angewendet: eine umfassende Studie über die tektonische Entwicklung Zentralamerikas seit dem Paläozoikum zeigt, wie Geo- und Thermochronologie, Strukturgeologie und Petrologie zusammenarbeiten können, um >400 Ma einer komplexen tektonischen Geschichte zu enträtseln. Eine thermochronologische Studie im Pamir, Tadschikistan betont vor allem die Möglichkeiten, die sich aus der Anwendung der Thermochronologie auf dem Gebiet der Geomorphologie und Neotektonik eröffnen.
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The Geomorphic Response of the Passive Continental Margin of Northern Namibia to Gondwana Break-Up and Global Scale TectonicsRaab, Matthias Johannes 21 June 2001 (has links)
No description available.
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Mineralogy and microfabric as foundation for a new particle-based modelling approach for industrial mineral separationPereira, Lucas 11 January 2023 (has links)
Mining will remain indispensable for the foreseeable future. For millennia, our society has been exploring and exploiting mineral deposits. Consequently, most of the easily exploitable high-grade deposits, which were of primary interest given their obvious technical and economic advantages, have already been depleted. For the future, the mining sector will have to efficiently produce metals and minerals from low-grade orebodies with complex mineralogical and microstructural properties -- these are generally referred to as complex orebodies. The exploitation of such complex orebodies carries significant technical risks. However, these risks may be reduced by applying modelling tools that are reliable and robust.
In a broad sense, modelling techniques are already applied to estimate the resources and reserves contained in a deposit, and to evaluate the potential recovery (i.e., behaviour in comminution and separation processes) of these materials. This thesis focusses on the modelling of recovery processes, more specifically mineral separation processes, suited to complex ores.
Despite recent developments in the fields of process mineralogy and geometallurgy, current mineral separation modelling methods do not fully incorporate the available information on ore complexity. While it is well known that the mineralogical and microstructural properties of individual particles control their process behaviour, currently widely applied modelling methods consider only distributions of bulk particle properties, which oftentimes require much simplification of the particle data available. Moreover, many of the methods used in industrial plant design and process modelling are based on the chemical composition of the samples, which is only a proxy for the mineralogical composition of the ores.
A modelling method for mineral separation processes suited to complex ores should be particle-based, taking into consideration all quantifiable particle properties, and capable of estimating uncertainties. Moreover, to achieve a method generalizable to diverse mineral separation units (e.g., magnetic separation or flotation) with minimal human bias, strategies to independently weight the importance of different particle properties for the process(es) under investigation should be incorporated.
This dissertation introduces a novel particle-based separation modelling method which fulfills these requirements. The core of the method consists of a least absolute shrinkage and selection operator-regularized (multinomial) logistic regression model trained with a balanced particle dataset. The required particle data are collected with scanning electron microscopy-based automated mineralogy systems. Ultimately, the method can quantify the recovery probability of individual particles, with minimal human input, considering the joint influence of particle shape, size, and modal and surface compositions, for any separation process.
Three different case studies were modelled successfully using this new method, without the need for case-specific modifications: 1) the industrial recovery of pyrochlore from a carbonatite deposit with three froth flotation and one magnetic separation units, 2) the laboratory-scale magnetic separation of a complex skarn ore, and 3) the laboratory-scale separation of apatite from a sedimentary ore rich in carbonate minerals by flotation. Moreover, the generalization potential of the method was tested by predicting the process outcome of samples which had not been used in the model training phase, but came from the same geometallurgical domain of a specific ore deposit. In each of these cases, the method obtained high predictive accuracy.
In addition to its predictive power, the new particle-based separation modelling method provides detailed insights into the influence of specific particle properties on processing behaviour. To name a couple, the influence of size on the recovery of different carbonate minerals by flotation in an industrial operation; and a comparison to traditional methodologies demonstrated the limitation of only considering particle liberation in process mineralogy studies -- the associated minerals should be evaluated, too. Finally, the potential application of the method to minimize the volume of test work required in metallurgical tests was showcased with a complex ore.
The approach developed here provides a foundation for future developments, which can be used to optimize mineral separation processes based on particle properties. The opportunity exists to develop a similar approach to model the comminution of single particles and ultimately allow for the full prediction of the recovery potential of complex ores.:1 Introduction 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.2 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.3 State-of-the-art in particle-based separation models . . . . . . . . . . . 11
1.4 Moving forward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.4.1 Particle data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.4.2 Mathematical tools required for the particle-based separation
model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
1.4.3 Workflow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
1.5 Structure of the thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2 The method and its application to industrial operations 23
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.2.1 Assumptions and limitations . . . . . . . . . . . . . . . . . . . . 26
2.2.2 Data structure and required pre-treatment . . . . . . . . . . . . 27
2.2.3 Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.3 Demonstration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.3.1 Artificial test cases . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.3.2 Real case study . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
2.4 Discussion and final considerations . . . . . . . . . . . . . . . . . . . . 39
3 The robustness of the method towards compositional variations of new
feed samples 45
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
3.2 Generalization potential of current Particle-based Separation Model
(PSM) methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.3 Case study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.3.1 Samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.3.2 Dry magnetic separation tests . . . . . . . . . . . . . . . . . . . 53
3.3.3 Sample characterization . . . . . . . . . . . . . . . . . . . . . . 53
3.3.4 Particle-based separation models . . . . . . . . . . . . . . . . . 54
3.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
3.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
4 Flotation kinetics of individual particles 67
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
4.2 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
4.2.1 Data collection . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
4.2.2 Cumulative recovery probability . . . . . . . . . . . . . . . . . . 72
4.2.3 Particle-based kinetic flotation model . . . . . . . . . . . . . . . 74
4.3 Demonstration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
4.3.1 Materials and methods . . . . . . . . . . . . . . . . . . . . . . . 75
4.3.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
4.4 Discussion and final thoughts . . . . . . . . . . . . . . . . . . . . . . . 80
5 Conclusions and outlook 85
5.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
5.2 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
Bibliography 89
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