The Leveäniemi iron oxide apatite (IOA) deposit, mined by LKAB, is located in Norrbotten, northern Sweden. The deposit has a partially more complex mineralogy than the neighbouring and more famous IOA deposits of Kiirunavaara and Malmberget. The Leveäniemi deposit contains comparatively more ore containing both magnetite and hematite but also maghemite and with slightly different trace element chemistry of the iron oxide minerals. Hematite is currently not considered a valuable mineral in the Svappavaara mineral processing and in the magnetite concentrate titanium and vanadium are considered to be penalty elements. Ore samples were collected from selected drill cores and from these polished thin sections were prepared that were investigated by optical microscopy, EPMA, and FE-SEM-EDS. Investigations focused on iron oxide mineralogy and mineral chemistry with special consideration to titanium and vanadium as those elements are considered deleterious in subsequent blast furnace or direct reduction processes. Investigations revealed that magnetite is the predominant mineral with secondary hematite being the second most abundant iron oxide mineral. In the investigated samples vanadium concentration in magnetite ranges from 0.12 to 0.32% V2O3 with higher concentrations in the southern part of the deposit. No such conclusions regarding spatial distribution could be done for titanium. Furthermore, the investigations indicated that alteration from primary magnetite to secondary hematite does not significantly affect the trace element chemistry of the minerals. Titanium in iron oxides occurs as either inclusions or lamellae of titanium oxide minerals. Vanadium in iron oxides occur as a substitution element and does not occur in stochiometric vanadium minerals. It is considered unfeasible to lower the content of these deleterious elements by physical separation methods. / Leveäniemi är en järnoxid-apatitfyndighet (IOA) i Norrbotten som bryts av LKAB. Fyndigheten har en delvis mer komplex mineralogi än de närliggande och mer kända IOA-fyndigheterna Kiirunavaara och Malmberget. Leveäniemifyndigheten innehåller jämförelsevis mer malm innehållande både magnetit och hematit men även maghemit samt med något annorlunda spårämneskemi i järnoxidmineralen. Hematit anses inte i nuläget vara ett värdemineral i Svappavaaras malmförädling och i magnetitekoncentratet anses titan och vanadin utgöra straffelement. Malmprov togs från utvalda borrkärnor och från dessa tillverkades polerade tunnslip som undersöktes med optisk mikroskopering, EPMA och FE-SEM-EDS. Undersökningarna var fokuserade på järnoxidernas mineralogi och mineralkemi med speciellt fokus på titan och vanadin då grundämnena anses vara skadliga i efterföljande masugns- eller direktreduktionsprocesser. Undersökningarna visade att magnetit är det dominerade mineralet med sekundär hematit som det näst vanligaste förekommande järnoxidsmineralet. I de undersökta proven varierade vanadinhalten från 0,12% till 0,32% V2O3 med högre halter i fyndigheten södra delar. Inga liknande slutsatser angående rumsliga fördelningen av titan kunde göras. Vidare så indikerade undersökningarna att omvandling från primär magnetit till sekundär hematit inte nämnvärt påverkar spårämneskemin i mineralen. Titan i järnoxider förekommer antingen som inneslutning eller lameller av titanoxidsmineral. Vanadin i järnoxider förekommer som ett substitutionselement och förekommer inte som stökiometriska vanadinmineral. Det anses inte vara tekniskt eller ekonomiskt möjligt att sänka halterna av dessa skadliga grundämnen med hjälp av fysiska separationsmetoder.

Rapid technological advancements and growing environmental consciousness created a shifting dynamic of metal demand within the context of contemporary global challenges. The metals play a pivotal role in this transformation and remarkable surge in demand is expected. Mining districts such as the Kiruna area in northern Sweden, provide access to raw materials, assuring supply chain security, sustainability, and an environmentally friendly future. The district is part of the northern Norrbotten ore province, Sweden and is known for hosting the Kiruna-type iron oxide-apatite (IOA) deposits with associated magnetite-hematite-REE ores such as the Per Geijer deposits, and a range of other deposits, including the Viscaria Cu-(Fe-Zn), Pahtohavare Cu-Au and the Rakkurijärvi iron oxide-copper-gold (IOCG) deposits.  As the discoveries of significant near-surface deposits are declining, mining companies face a pivotal choice between pursuing resource extraction from lower-grade reserves or to focus on deeper exploration targets. The geological understanding of the subsurface decreases with increasing depth, and the reliance on geophysical techniques becomes more important in reducing the search space. Using geophysics to locate and understand elements of a mineral system requires a good understanding of the physical and chemical properties of the rocks that can be translated into geological implications. Mineral system knowledge and geological concepts can be translated into geological models that can be further used in geophysical inversions with the aim of improving targeting by iterative modeling. A geophysical inversion is in fact a realization of a physical property model, therefore the value added by the geophysical model is dependent of how well the relationship between the geology and its petrophysical signature is understood. The petrophysical characterization of geological environments offers the possibility to improve the understanding of geophysical responses, serving as a link in iterative geological-geophysical modeling.  The approach presented in the current study includes the building of three-dimensional lithological and structural framework models, and investigating the petrophysical footprint in connection with lithology, alteration, and rock fabric from the Kiruna mining district. Geological modeling and petrophysical characterization are important components within the comprehensive mineral system modeling framework and enhance geophysical investigations aimed at detecting and assessing iron oxide mineral systems. A rule-based hybrid implicit-explicit geological modeling technique proved to be useful in the integration of surface and subsurface data of the Kiruna mining district, and a structural framework and geological model was produced that provides insights into the relationship between lithological units and structures. Drill core observations indicate a competency contrast between lithological units confirming previous surface-based observations. Deposit scale structural analysis in connection with the geological models indicated the proximity of NW-SE to SW-NE trending brittle conjugate fault networks with iron-oxide apatite ore lenses, revealing juxtaposition of individual ore lenses. Complementing structural analysis and geological modeling, petrophysical characterization in connection with lithogeochemical, mineralogical, and textural investigations revealed that density and p-wave seismic velocity can be used as a general lithological indicator, while magnetic susceptibility is influenced by secondary processes. Heterogeneous strain accommodation by lithological units indicates a strong influence on density, seismic properties, and the ferromagnetic properties of the samples. Metasomatic processes alter the intrinsic properties of the samples by increasing or decreasing the physical properties of the rocks from the Kiruna area, by controlling the feldspar, mica, magnetite, and ferromagnesian mineral content. Nevertheless, an extensive sample population must be investigated to understand the large-scale effects. The present work serves as a foundation for quantitatively integrated exploration models that use geological models and petrophysical characterization as calibration tools to model mineral systems.

The Northern Norrbotten ore district hosts a multitude of Sweden’s mineral deposits including world class deposits such as the Malmberget and Kirunavaara Iron oxide apatite deposits, the Aitik Iron oxide copper gold deposit, and a multitude of smaller deposits. Northern Norrbotten has been shaped by tectonothermal events related to the evolution of the Fennoscandian Shield and is a geologically complex environment. Without extensive rock outcropping and with most drilling localized to known deposits the regional to local scale of mineralization is not fully understood. To better understand the evolution and extent of the mineralization’s cross-disciplinary geosciences must be applied, where geophysical methods allow for interpretations of the deep and non-outcropping subsurface. Common earth modelling is a term describing a joint model derived from all available geoscientific data in an area, where geophysical models provide the framework.This study describes the geophysical modeling of two IOA deposits in Norrbotten, the Malmberget deposit in Gällivare and the Per-Geijer deposit in Kiruna. To better put these two deposits into a semi-regional setting magnetotelluric (MT) measurements have been conducted together with LKAB. LTU and LKAB have measured more than 200 MT stations in the two areas from 2016-2023. These measurements have then been robustly processed into magnetic transfer functions (impedances) for the broadband MT frequency spectrum (1000Hz,1000s). Then, all processed data judged to be of sufficient quality have been used for 3D inversion modelling using the ModEM code. The resulting conductivity/resistivity models reveals the local conductivity structure of the area, believed to be closely tied to the mineralization due to the conductive properties of the iron bearing minerals. Both areas yielded believable models which pinpointed known mineralization’s at surface as conductive anomalies and their connections to deeper regional anomalies.During modelling a robust iteratively re-weighted least square (IRLS) scheme has been implemented in the inversion algorithms. This scheme allows for objective re-weighting of data errors based on the ability for a given model discretization to predict individual datums. This, to better identify measurements which have been contaminated by local electromagnetic noise due to anthropogenic sources (mainly the power grid and railway). Due to the mathematical properties of the scheme, it allows for models which minimizes the L1 data error-norm instead of usual L2 minimization. This has yielded models whit sharper contrasts in resistivity and successfully emphasizes data believed to be reliable. Results indicate that the scheme was implemented successfully and the tradeoffs in data-fit are deemed acceptable.In addition, in the Kiruna study potential field data (magnetic total field and gravimetry) have been 3D modelled for the same area. These data sets have been inversion modelled in 3D using the MR3D-code developed at LTU with partners. Resulting 3D models have then been interpreted collectively both traditionally and with the use of machine learning methods. To guide interpretations more than 100 rock samples have been collected in the area and their petrophysical properties (density, magnetic susceptibility, electrical resistivity) have been measured at LTU. These petrophysical properties have been used to guide the machine learning methods for the 3D models by first using K-mean clustering on normalized petrophysical data and then using the resulting centroid vectors as input for a Gaussian mixture model of the similarly normalized 3D models. Resulting clusters show potential in being able to pick up sharp geological boundaries but expectedly is unable to fully capture geological structures one to one.

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