Crustal architecture of the Kiruna mining district : Structural framework, geological modeling, and physical rock property distribution

Sammanfattning: 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.