The Mineral System Approach is a concept in which the formation of ore deposits is viewed as a series of source, pathway, and sink processes. In the context of magmatic sulfide deposits, the main source of metals is in the mantle, the pathway is a translithospheric network of intrusions and dykes, and the sink is a physicochemically suitable crustal segment, where the metals are ultimately concentrated and deposited. The ability to decipher the signs of these processes in rocks is useful for identifying prospective areas for mineral exploration. With petrological experiments, we can simulate many of the processes occurring within the mineral system in a controlled laboratory environment. Experiments conducted in mantle conditions reveal how different mantle lithologies melt and what is the role of each phase in releasing the metals. Sulfide saturation state of the melt is one of the main variables in controlling the faith of the chalcophile metals and hence it has been intensively studied experimentally. The presence of dense sulfides in the mantle source or their precipitation along the translithospheric pathway tends to inhibit effective metal transportation to the upper crustal levels. However, experiments have shown that sulfides have a strong tendency in attaching to low-density fluid bubbles and carbonate melts, which may aid in their transport within the silicate melt in certain situations. Finally, observations from many ore deposits indicate that magmatic assimilation of sedimentary sulfur is important in triggering early sulfide saturation, which favors efficient metal enrichment to the sink. Experiments enable us to characterize the physicochemically complex magma-sediment interactions in detail and identifying the reaction pathways, which promote sulfide saturation. From source to sink, the key processes affecting the metal budget leave geochemical and mineralogical fingerprints to rocks, which we can detect with the experiments and use to evaluate the exploration potential of magmatic suites. An application to the magmatic Cu-Ni-PGE sulfide deposits of the Central Lapland Greenstone Belt will be presented.
How to cite: Virtanen, V., Iacono-Marziano, G., Yang, S., and Guo, F.: The mineral system of magmatic sulfide deposits: an experimental approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11246, https://doi.org/10.5194/egusphere-egu25-11246, 2025.
The Beja Igneous Complex (BIC) is a major geological feature of the SW Iberian Variscides, extending for over 100 km along the southern border of the Ossa-Morena Zone. The formation of the BIC occurred during the main collisional stages of the Variscan Orogeny. The Layered Gabbroic Sequence (LGS) corresponds to the most primitive member of the BIC, hosting various occurrences of Fe-Ti(-V) oxide mineralization within olivine leucogabbros. The early stages of LGS crystallization are recorded by the Soberanas troctolites (SB I) and gabbronorites (SB II; εNd350 = +6.75; 87Sr/86Sr350 = 0.7043), Odivelas ferro-gabbros (ODV I; εNd350 = +1.81; 87Sr/86Sr350 = 0.7049) and Torrão ferro-diorites (TOR; εNd350 = +2.42; 87Sr/86Sr350 = 0.7045). The formation of ODV I ferro-gabbros and massive oxide accumulations has been envisaged as a consequence of extensive differentiation (Fo88-54; An89-41) from oxidized (ΔFMQ = +1.7) primitive basaltic parental magmas, derived from SB I, to more reduced conditions (ΔFMQ = +0.5). Pressure estimates for the emplacement and main fractionation events are 4.5 kbar. The nearby exposed TOR ferro-diorites share many geochemical similarities with the most isotopically primitive SB II gabbronorites, namely sub-parallel REE and trace element patterns. Geochemical modeling shows that 20-30% fractionation of a typical mafic mineral assemblage comprising cpx + ol (± amp) + spn from magmas represented by the SB II gabbronorites can plausibly generate the TOR ferro-diorites. Although median amp-plg pressure estimates for the TOR ferro-diorites are comparable with those obtained for SB II and ODV I gabbroic rocks, the amp-only pressure estimates provided by amphibole phenocrysts in TOR ferro-diorites yield pressure values of 6 to 7 kbar. These “high-pressure amphiboles” suggest that the parental SB II magmas should already have significant amounts of dissolved H2O (> 3.5 wt%). Under such high-pressure conditions, fractionation of plagioclase is inhibited, explaining the lack of negative Eu and Sr anomalies in these rocks. Estimation of fO2 conditions for ferro-diorites is precluded by late, sub-solidus re-equilibration of coexisting magnetite and ilmenite, possibly related to free O2 liberation during amphibole crystallization.
While deriving from similar parental magmas, the ODV I ferro-gabbros and TOR ferro-diorites record distinct differentiation conditions. High-pressure fractionation of primary basaltic magmas promotes the enrichment of dissolved H2O due to increased solubility, deviating the composition of residual melts towards the stability field of amphibole. Conversely, lower-pressure evolution of similar magmas generates a typical “dry” tholeiitic differentiation path, resulting in stronger Fe and Ti enrichment and so the potential to generate massive oxide accumulations, as recorded in ODV I ferro-gabbros. These findings highlight the role of pressure in generating significantly different products from the same primary basaltic magma.
Co-funded by the EU SEMACRET GA#101057741 and FCT I.P./MCTES through national funds (PIDDAC): UID/50019/2025 and LA/P/0068/2020 https://doi.org/10.54499/LA/P/0068/2020).
How to cite: Antunes Dias, M., Jesus, A., Mateus, A., Oliveira, A., and Bartolomeu, B.: Pressure effects on the differentiation of basaltic magmas: insights from the synorogenic Beja Layered Gabbroic Sequence (Portugal) and implications for oxide-ore forming processes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20726, https://doi.org/10.5194/egusphere-egu25-20726, 2025.
Mafic layered intrusions are well-known hosts of base- and precious metal deposits throughout the world. The formation of Fe-Ti-V deposits in layered mafic intrusions remains a subject of interest to petrology and to the extractive industries. The 2.44 Ga magmatism in the Fennoscandian shield was caused by a mantle plume event and the initiation of rifting of the Archean craton, causing the emplacement of several mafic-ultramafic intrusions, mafic dykes and volcanic rocks. Many of these 2.44 Ga intrusions host significant mineralizations, including occurrences of Cr, PGE and V. The Koillismaa intrusion belongs to this group of intrusions, and hosts significant contact-, and reef-type PGE mineralization in the lower and middle portions of the intrusion, respectively, and an Fe-Ti-V oxide deposit in the upper part. The Mustavaara Fe-Ti-V deposit is a historically important source of V, having accounted for a significant portion of global V production from 1976-1985. The deposit contains an estimated 64 Mt of proven reserves, and 35 Mt of probable reserves, grading 14 wt. % ilmenomagnetite of 0.91 wt% V (Karinen et al., 2022, and references therein). The oxide ore zone is dominated by magnetite gabbro with disseminated vanadium oxide of about 30%, without significant massive ores, which is different from the Bushveld complex, but similar to some other Finnish intrusions (e.g., Akvanvaara). The clinopyroxene grains are intensely altered, but fresh plagioclase domains are normally present. In this study, systematic in situ analysis of trace elements and Rb-Sr isotope of plagioclase from samples taken across the whole stratigraphy of the Koillismaa intrusion has been conducted. These new data, together with published bulk rock geochemical and mineralogical data will be used for constraining the parental magma composition, and elucidating the fractionation of magma, magma replenishment and oxygen fugacity, and thus a better understanding of the genesis of the Fe-Ti-V deposit in Mustavaara.
Karinen, T., Moilanen, M., Kuva, J., Lahaye, Y., Datar, B. and Yang, S., 2022. Mustavaara revisited: A revised genetic model for orthomagmatic Fe–Ti–V mineralisation in the Koillismaa intrusion. p414. ERE4.3
How to cite: Datar, B., Karinen, T., O’Brien, H., Kurhila, M., Myllyperkiö, M., Chernonozhkin, S. M., Moilanen, M., and Yang, S.: In-situ trace elements and Sr isotopes in plagioclase in the Koillismaa intrusion, Finland, and implications for the formation of Fe-Ti-V oxide ores, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21666, https://doi.org/10.5194/egusphere-egu25-21666, 2025.
Sediment-hosted deposits are a major global source of copper. This study presents 3D reactive transport simulations to identify critical controls on copper leaching, transport, and deposition. Numerical experiments are performed using the open-source IC-FERST code (http://multifluids.github.io/), integrating buoyancy-driven groundwater flow, heat and salt transport, and copper leaching, transport, and deposition. The code implements dynamic mesh optimisation to improve computational efficiency.
The 3D geological model is based on the pre-orogenic stratigraphy of the Katangan basin, noting that many aspects of this stratigraphy are common to other sedimentary basins hosting copper deposits. We model flow in two snapshots of basin geometry at different times: early during evaporite formation and later when the basin has opened further, the evaporites have been buried, and there is a thicker basin fill. Modelling flow in these different snapshots allows us to test (i) the conditions for mineralisation at early and late diagenetic stages of basin evolution, (ii) the impact on flow of changing hydrogeological basin architecture, and (iii) the impact of heating during burial. Copper leaching from potential red-bed and basement source rocks is governed by a partition coefficient, while deposition is assumed to occur at a constant rate within an interval overlying the red beds representing a redox boundary.
Results demonstrate convective cells are established at two scales. Large (km) - scale convection occurs within permeable faults, allowing dense, saline groundwater to percolate downwards from the accumulating basin fill into the basement, where heating drives upwards flow back into the basin. Initially, convective cells form within individual faults, emphasizing the flow's three-dimensional nature. Later, some faults become dominated by downwards flow, others by upwards flow. These large-scale, fault-controlled convective cells are a major driver of copper transport: hot, saline brines leach copper from red-bed and basement source rocks and transport it upwards for deposition. Stratabound, lateral flow of copper-rich brine creates deposits near faults dominated by upwards groundwater flow. Additionally, small (10s–100s m) - scale convection occurs within red-beds, provided they have sufficient permeability. These small-scale convection cells drive local copper leaching, allowing upward migration and deposition. Vertical flow of copper-rich brine creates patchy deposits not spatially associated with faults.
Key controls on mineralisation are the efficiency of leaching from red-beds and basement source rocks, fault permeability controlling large-scale convective flow, red-bed source rock permeability, and the presence of a salt source in the basin. Early mineralisation can occur only if cool, low-salinity brines effectively leach copper from source rocks, because hot, saline brines do not reach the source rocks until later in basin evolution. Moreover, mineralisation can only occur without a salt source if low-salinity brines can effectively leach copper. Mineralisation does not occur in a single pass of copper-enriched brine but gradually, as convection supplies enriched brine that deposits its copper, removes the depleted brine, and circulates this to the source rocks to be enriched again over numerous cycles.
How to cite: Bahlali, M., Jacquemyn, C., Purkiss, M., and Jackson, M.: 3D numerical modelling of copper leaching, transport and deposition by convective groundwater flow in sedimentary basins, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9524, https://doi.org/10.5194/egusphere-egu25-9524, 2025.
Many conceptual models of layered intrusions are based on the idea of a long-lived, melt-dominated magma chamber, within which chemical differentiation occurs through fractional crystallisation and assimilation of the surrounding crust. These models typically assume magma is delivered in a single large batch or a few large pulses. However, recent studies have suggested that melt-dominated chambers are transient. Intrusions are constructed incrementally from smaller magma batches. Melt-dominated layers may form in response to new intrusions or melt-solid separation, but most of the intrusion comprises crystal-rich mush or solid rock. Chemical differentiation occurs by assimilation and fractional crystallisation, as well as reactive percolative melt flow within the mush.
The origin of layering is closely linked to fluid-dynamical processes occurring in intrusions: conceptual models ubiquitously invoke flow, whether of low crystallinity magma driven by thermal or compositional convection, or of melt or fluids percolating through high crystallinity mush. Yet, despite the importance of these processes, few models have attempted to model them using well-established physical conservation laws, constitutive equations and numerical methods. Our aim is to explore the coupled processes of heat and mass transfer in layered intrusions. We develop a two-phase (melt and crystals) numerical model that is applicable to layered intrusions constructed incrementally or by a single large batch of magma. The numerical model captures (i) separation of melt and crystals by crystal settling at high melt fraction and percolative flow at low melt fraction, (ii) transfer of heat by conduction and advection and (iii) solid-melt mass exchange and chemical differentiation. We report a chemical model, used to track chemical differentiation, which is built for layered intrusions. The chemical model can match the end-members of equilibrium and fractional crystallisation, depending upon the efficiency of melt-solid separation calculated by the numerical model. The chemical model also calculates the proportion of four major rock-forming minerals in layered intrusions: olivine, orthopyroxene, clinopyroxene and feldspar.
Preliminary results suggest layering in these intrusions can form by melt-crystal separation at high and low melt fraction, coupled with reactive percolative flow at low melt fraction. Reversals in the characteristic upwards decrease in MgO can also arise by these processes. Incrementally built complexes may contain multiple magma chambers at different depths, separated by crystal-rich mush or solid rock, rather than a single chamber. Although the chemical model is the same, we observe differences in layering style and composition depending on the cooling time and intrusion style. Ongoing research continues to investigate the parameter space.
Current work is focussed on coupling the chemical model reported here with a three-dimensional code for simulating heat and mass transport and chemical reaction. This will allow us to test determine the style of convection, and the impact of convection on layering. Second, our model assumes local thermal and chemical equilibrium. It does not allow crystal zonation or undercooling of a pure melt prior to crystallisation. Current research is focussed on extending the chemical model to allow undercooling, so we can test the prevalence of pervasive versus in-situ nucleation and growth of crystals.
How to cite: Booth, C., Hu, H., and Jackson, M.: Numerical modelling of melt-solid separation in layered intrusions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7393, https://doi.org/10.5194/egusphere-egu25-7393, 2025.
The central Norwegian Dragset and Høydal deposits are small-scale Cyprus-type volcanogenic massive sulphide (VMS) deposits hosted within oceanic back-arc affinity metavolcanic rocks of the Early Ordovician Løkken ophiolite. During the Caledonian orogeny, the Dragset deposit was deformed and metamorphosed in lower-mid greenschist facies, while Høydal is one of the very few VMS deposits in the Caledonides that experienced only minimal effects of deformation and metamorphosis. Despite their proximity to the world-known Løkken, the formation process as well as critical metal content is poorly understood. Hence, the present study aims to contribute to these aspects through field observations, optical and electron microscopical petrography, in situ mineral chemistry (EPMA and LA-ICP-MS) and whole-rock geochemical analyses.
Massive sulphide as well as stockwork mineralisation in altered greenstone are observable at both study locations. Pyrite is abundant in both deposits and in each ore type, while chalcopyrite is more common in the stockwork zones. Traces of sphalerite occur at each location and mineralisation type, as well as local sphalerite enrichment in some massive sulphide samples. These mineralogical observations support well the observed differences in whole rock geochemistry data where Cu/Zn ratios decrease towards more distal ore types.
The widespread appearance of pyrite combined with its resistance to later processes make it a perfect tool to reconstruct the formation environments. Higher formation temperatures (up to >320°C) in Dragset facilitated Co incorporation in pyrite as well as occurrence of cobaltite, resulting in overall higher Co content of the ore, compared to Høydal (up to 277 ppm vs. up to 37 ppm). Also, in both deposits the trace element content (As, Te) in pyrite indicates a change in redox conditions, i.e., that fluids became progressively more oxidised towards the seafloor due to mixing with oxygenated seawater.
Sphalerite, unlike pyrite, was affected by metamorphism in Dragset, leading to Zn remobilisation and high temperature (320-480°C) sphalerite precipitation in more permeable zones. As a contrary, submarine hydrothermal sphalerite was found in Høydal, formed at lower temperature (below 200-250°C), enriched in the distal massive sulphide samples. It formed during the waning stage of the hydrothermal process, together with late pyrite and quartz precipitation; the preliminary fluid inclusion study of quartz proves the <200°C formation temperature from an enriched, seawater originated fluid.
Besides the Cu and Zn content, the high temperature formation conditions at Dragset were favourable for the enrichment of a few critical metals (in addition to the above-mentioned Co, Se and Te also). Though some distal samples of Høydal are enriched in lower temperature sphalerite, their Ga content remain below economic grade.
This still ongoing study draws the attention to the effects of formation temperature differences as well as metamorphic overprint on the metal occurrence and distribution in the VMS deposits.
How to cite: B. Kiss, G., M. M. Mina, M., Paulsen, H.-K., R. Miranda, A. C., and T. Mansur, E.: Study of the Dragset and Høydal VMS deposits (Central Norwegian Caledonides): genesis, effects of metamorphic overprint, critical raw material potential, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12838, https://doi.org/10.5194/egusphere-egu25-12838, 2025.
The Bergslagen ore province, part of the Swedish Fennoscandian Shield, hosts the largest rare earth element (REE) reserve in the EU and significant base metal deposits, highlighting its critical raw material potential. The EU-funded Marie Skłodowska-Curie project "CRITTER: Strengthening the Critical Raw Material Independence of the EU through Thermochronology" (ID: 101154535) aims to reconstruct the thermal history of Bergslagen, focusing on cooling, reheating, and ore mobilization over the past 1.8 Ga.
We apply high-temperature Rb-Sr thermochronology on mica at the University of Gothenburg and low-temperature U-Th-He thermochronology on zircon and rutile at the University of Göttingen. This interdisciplinary approach targets minimally altered granites and pegmatites near key mineral deposits, including Bastnäs (REE) and Håkansboda (Cu-Co).
Preliminary Rb-Sr results reveal two distinct age groups (~1700–1500 Ma and ~1050–1350 Ma), suggesting episodic thermal activity linked to regional tectonics. Results from Blötberget (Grängesberg) and I-Edda (Örebro) cores reveal biotite Rb-Sr ages around 1.6-1.5 Ga.
These findings suggest that far-field tectonic events, even within stable cratons, can influence thermal evolution and ore remobilization, advancing our understanding of mineral systems. This study contributes to refining exploration criteria by integrating thermochronology and geochemical techniques for efficient mineral exploration.
How to cite: Kelemen, P., Zack, T., Rösel, D., Dunkl, I., and Lynch, E. P.: Thermal Histories and Critical Mineral Systems in the Bergslagen Ore Province, Fennoscandian Shield, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19683, https://doi.org/10.5194/egusphere-egu25-19683, 2025.
The exponential growth of the high-tech industry, and the current environmental challenges affecting the agricultural sector result in a global demand for critical raw materials, such as rare earth elements (REE) and P. REEs are prioritized given their use for green-energy technologies, whereas P is key for the fertilizer industry.
Southern Norway is host to several magmatic REE occurrences where Fen, Europe’s largest REE deposit, is the most relevant of all. East of the Fen deposit, the southern Oslo Rift area contains several magmatic P-REE occurrences (e.g., Kodal deposit). The P-REE mineralization is mainly contained in small (cm to <1 m) titanomagnetite–apatite–ilmenite-rich pockets irregularly distributed within narrow areas (<1 km2) hosted by monzonite. A recent multidisciplinary project lead by the Geological Survey of Norway has re-defined the ore genesis model of the area and assessed its regional mineral potential.
The restricted size and erratic occurrence of the P-REE mineralization along with the glaciated nature of the terrane pose significant challenges for mineral exploration in the area. If not properly assessed, mineralized areas can be overlooked. In this contribution, we test the performance of field and laboratory measurements of till geochemical and physical properties in the Siljan occurrence as means to detect P-REE mineralization in the broader Southern Oslo Rift area.
The Siljan occurrence is one of the most prospective areas for P-REE mineralization indicated by the regional prospectivity study. Here, we carried out a targeted till sampling transect (1 km long; 50 m x 50 m grid, n = 110) and drone magnetic survey (8 km2; 5 m x 5m resolution). Till material was analyzed in the field using a portable XRF and magnetic susceptibility meter. The samples were sieved to a size of <2 mm, analyzed for major and trace elements using ICP-MS, and subjected to magnetic susceptibility measurements at the Geological Survey of Norway laboratory. First, several geochemical vectors were selected separately for the field and laboratory datasets using raw data and multivariate statistics. Then, geochemical and magnetic susceptibility anomalies from both datasets were decoupled from background using fractal analysis. Our results show that geochemical vectors involving Ca, Fe and P, and magnetic susceptibility measurements from both datasets can efficiently detect the Siljan anomaly and spatially correlate with a magnetic high indicated by the drone survey. Notably, REE-driven anomalies are less well-defined in the field dataset, nonetheless, these remain useful to detect the mineralized zone. The survey results also indicate that till transport is minimal in Siljan, which makes this media a very robust vector for mineral exploration surveys.
Overall, this study shows that characterization of soil geochemistry and -magnetic susceptibility combined with an appropriate exploration grid design, can efficiently trace the fingerprint of magmatic P-REE mineralization in southern Norway, and likely, in similar glaciated terranes elsewhere. Moreover, our results indicate that field measurements can provide equally reliable results when compared to the more costly and time-consuming laboratory analyses.
How to cite: Acosta-Gongora, P., Andersson, M., Coint, N., Henderson, I., Texeira Mansur, E., Szitkar, F., Miranda Rodrigues, A. C., and Wang, Y.: Tracing P-REE mineralization in till from the southern Oslo Rift, Norway, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7381, https://doi.org/10.5194/egusphere-egu25-7381, 2025.
Modelling Induced polarization effects in airborne electromagnetic (AEM) data is becoming a standard tool in mineral exploration, but the industry standard is still based on one-dimensional (1D) forward and Jacobian modelling. We have developed a three-dimensional (3D) vector finite element electromagnetic forward and inversion method considering IP effects within the EEMverter modelling platform. The computations are carried out in frequency domain, and then time- transformed in time domain through a Hankel transform. This allows to model any parameterization of the IP phenomenon, from the simple constant phase angle model to a full debye decomposition. We present AEM survey data from Semacret project, which contain significant IP anomaly responses. Our test results show that the anomaly distribution of the 3D EM-IP inversion agrees well with the known geological drill hole data.
Airborne electromagnetic (AEM) exploration technology, recognized for its efficiency, flexibility, and indifference to complex terrains, has been extensively applied in hydrogeological mapping geothermal exploration, and energy resource surveys. Due to the typically large-scale datasets collected via AEM, employing inversion methods based on one-dimensional (1D) forward operators remains a conventional and mainstream strategy for data interpretation. In geological settings where the terrain is flat and the subsurface media are approximately layered, 1D inversion can provide relatively accurate interpretations. However, in regions where the terrain is rugged and the distribution of subsurface media varies significantly in different directions, such as mineral deposits, 1D forward modeling is no longer applicable and three-dimensional (3D) inversion is required for proper interpretation.
To meet the demand for detailed interpretation of airborne electromagnetic data for mineral resources, this study employs the vector finie element method, which is known for its high flexibility and computational accuracy, to perform 3D EM forward modelling and inversion. The main
features include: 1) the use of Octree meshes to accelerate the meshing process and allow further mesh refinement during inversion iterations, 2) calculation of complex resistivity responses in the frequency domain, enabling easy simulation of any parameterized model of IP, and 3) the independence of the forward modeling mesh from the inversion model mesh, requiring the calculation of the Jacobian matrix only in the footprint area of the forward modeling mesh during inversion iterations.
How to cite: Chen, J., Zhang, B., Dauti, F., and Fiandaca, G.: 3D AEM inversion considering IP effect for mineral exploration in Semacret project, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20819, https://doi.org/10.5194/egusphere-egu25-20819, 2025.
In the Akaanvara area in Northern Finland, during the SEMACRET project, several geophysical campaigns have been carried out, which together with the information provided by the campaigns previously carried out in the area have been used to define procedures for the choice of methodologies, processing and modelling suitable for the exploration of the mineralisations in the study area.
AEM and Flight Magnetometry, AMT and Passive Seismic campaigns have completed the existing information consisting of gravimetric and magnetic data. The different methodologies have been analysed in detail, applying in each case the most resolute and precise processing and modelling techniques, as well as novel in some cases, which although they have been applied in other areas of the world have not been tested in geological environments of the characteristics of Akaanvara, with the challenges of working in an area with very high resistivities.
This paper aims to analyse in detail how the different methodologies and the different processes and modelling applied to the measured and collected data, and their integration, can be applied to the geological environment of Akaanvara. The results of the analysis of the different methods, as well as the treatment that has been applied to them, together with the integration of all the layers of information have provided very interesting conclusions.
How to cite: Fernandez, I., Viezzoli, A., Fiandaca, G., Moisio, K., kozlovskaya, E., and Yang, S.: Geophysical exploration in orthomagmatic mineral deposits: multimethod approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21095, https://doi.org/10.5194/egusphere-egu25-21095, 2025.
The critical raw materials (CRMs) exploration and supply is crucial to achieve the objectives defined by the European Critical Raw Materials Act to reach the green energy transition. In order to reduce the social and environmental impact of the exploration, innovative indirect techniques have to be adopted for the mineral targeting. Among the various geophysical methods, two of the most common techniques for exploration are the Induced Polarization (DCIP) and the Electromagnetic (EM) to map, respectively, chargeable and conductive bodies in depth. Although these techniques have been considered sensitive to different physical properties for a long time, it has been recognized that the effects of a polarizable ground can be measurable by inductive EM measurements (Smith et al., 1996), both airborne and ground. It has then been shown that is possible to model the inductive IP (Viezzoli et al., 2013) to retrieve the ground chargeability distribution and how novel modelling approaches (Dauti et al., 2024) can increase the inductive chargeability sensitivity in depth with good relationships with known mineralized bodies. In this context, with this contribute we propose a case study for which the retrieved inductive chargeability models have been actively used to define the next steps of the exploration workflow for a real green-field exploration research project in Portugal (within the HORIZON SEMACRET European project) with chargeable and resistive targets.
First, two Airborne EM surveys have been flown with different base frequencies (12.5 Hz and 25 Hz) to increase the data sensitivity to IP effects and to improve the near surface resolution. Then, a modelling approach that pointed to reduce the equivalencies among the parameters of the “IP-expanded” model-space has been applied to the data. These have been both independently and jointly modelled (between 12.5 and 25Hz), to better define where to follow-up on the ground. The inversions defined different chargeable targets that, integrated with the ancillary information, had allowed to define where to follow-up on the ground with the DCIP survey. The ground data have been acquired over the AEM lines and the chargeable anomalies have been confirmed by the
galvanic measurement. To conclude, a joint inversion between all the methodologies have been carried and the IP effects from a methodological multi-frequency prospective have been investigated, merging the sensitivities of different methodologies to resolve the ground chargeability within a unified IP bandwidth.
With this contribute we thus worked in a twofold direction: from an applied standpoint, we used the AIP method as a tool to define targets for a large-scale greenfield project and we successfully downscaled the exploration defining where to follow-up on the ground using the airborne result. Then, from a methodological standpoint, we resolved the ground chargeability merging the sensitivities to IP effects of the galvanic and of two inductive methodologies.
How to cite: Dauti, F., Viezzoli, A., Chen, J., Jesus, A. P., Fernandez, I., and Fiandaca, G.: Airborne IP driven exploration for greenfield exploration: an application in the SEMACRET project , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20829, https://doi.org/10.5194/egusphere-egu25-20829, 2025.
The Strzegomiany-Kunów Fe-Ti±V prospect is located within the eastern edge of Ślęża ophiolite which belongs to the Central-Sudetic ophiolites (CSO), forming part of the Variscan suture zone. The Ślęża ophiolite is the largest exposed section of the Central Sudetic Ophiolite and retains a nearly complete, typical ophiolite pseudo-stratigraphic sequence. The Kunów-Strzegomiany prospect marks the north-eastern part of the Ślęża ophiolite, covered by the Cenozoic sediments.
The conducted geophysical and geochemical exploration aimed to identify previously unrecognized deep-seated potential for Fe-Ti±V mineralization within the Ślęża area and the Strzegomiany-Kunów Fe-Ti±V prospect. A set of Electric Resistivity Tomography and Induced Polarization profiles was conducted as well as magnetic measurements (ground and airborne). Chemical composition analysis of the samples was conducted using portable X-ray fluorescence, WD-XRF and the ICP-MS.
On Ślęża Mountain, four elongated lenses oriented SW-NE and W-E were delineated, exhibiting enrichment in iron, titanium, and vanadium. These zones are characterized by elevated titanium concentrations, with a maximum of 5.59 wt.% and a median of 4.19 wt.%. High titanium and iron contents show a strong positive correlation with vanadium, which is generally abundant in Ślęża gabbros, reaching up to 1446 ppm (median 993 ppm). The analyzed samples also display slightly elevated scandium concentrations, a critical element as classified by the European Commission. Scandium in Ślęża gabbros ranges from 8.4 to 72.5 ppm, with an average of 55.6 ppm and a median of 57.5 ppm. Elevated scandium levels generally correlate positively with TiO₂ but show no correlation with iron or vanadium.
In the Kunów area, samples were collected from several small outcrops on and around Kunów Hill, as well as from two boreholes, Kunów-B1 and Kunów-B2, which document the subsurface extent of the Kunów gabbro body to a depth of 89 m below ground level (b.g.l.). The gabbros from Kunów Hill exhibit a chemical composition similar to those from the Ślęża area. Titanium concentrations in the Kunów samples are locally elevated, with a maximum of 5.17 wt.% and a median of 3.74 wt.%, slightly lower than the values observed in the Ślęża gabbros. Vanadium levels in Kunów samples are generally high, with individual samples showing enrichment relative to Ślęża, ranging from 141 ppm to 1603 ppm (median: 509 ppm).
In the two studied boreholes, several oxide-bearing intervals of variable thickness (0.2 to 2.0 meters) were identified. The highest concentrations of Fe, Ti, and V occur within semi-massive to massive oxide ore hosted in ophitic gabbro. These Fe-Ti-V-enriched intervals are interpreted as south- or southwest-dipping lenses or dikes of oxide gabbros/ferrogabbros. The lateral extent of these, previously unknown, bodies remains poorly constrained and will require additional exploratory boreholes for detailed characterization.
Funded by the European Union (SEMACRET, Grant Agreement no. 101057741)
How to cite: Rosowiecka, O., Bienko, T., Mikulski, S., and Weekes, R.: New data on Fe-Ti±V mineralization from Ślęża and Strzegomiany-Kunów prospect, SW Poland: insights from geophysical surveys and geochemical exploration, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16664, https://doi.org/10.5194/egusphere-egu25-16664, 2025.
The development of cost-effective and environmentally friendly methods for the exploration of critical raw materials (CRM) is important in the modern world as such platinum-group metals (PGM) as nickel (Ni), cobalt (Co), vanadium (V), copper (Cu) are irreplaceable in a wide set of EU strategic sectors such as aerospace, digital industry, and defense sectors. Orthomagmatic mineral systems include mafic layered intrusions and conduit-type sulphide deposits, which host many of the above-mentioned CRMs. In the EU, there is currently only one orthomagmatic sulphide deposit (Kevitsa Ni-Cu-PGE-Co, Finland) and one orthomagmatic oxide deposit (Kemi Cr, Finland) in production. However, there are potential deposits in different countries, among which is the Akanvaara Cr-V-PGE deposit, which was extensively studied by the Geological Survey of Finland (GTK) during the 1990s. Within these studies, more than 100 diamond drill holes were drilled with comprehensive geochemical analyses across the whole stratigraphy. The layered rocks and occurrence of thick magnetite gabbro motivated the selection of Akanvaara as one of the sites in the SEMACRET project (“Sustainable exploration for orthomagmatic (critical) raw materials in the EU: Charting the road to the green energy transition”) for testing of advanced geophysical techniques for orthomagmatic mineral deposits exploration. Within this project, an innovative passive seismic method based on coda wave passive seismic interferometry has been developed. To test this method, we recorded continuous three-component seismic data along two profiles, crossing the mineralized zones of the deposit. In total, we used 746 three-component seismometers provided by the FINNSIP (Finnish Seismic Instrument Pool www.finnsip.fi). The instruments were installed in two profiles and recorded continuous seismic data from 2.11.2023 to 9.12.2023 (606 instruments) and from 28.08.2024 to 2.10.2024 (140 instruments), respectively. Results of passive seismic data processing by the developed method show converted arrivals originated at mineralization zones and other structural features of the deposit. To interpret these arrivals, we used the gravity data measured by the GTK during the 1990’s. This data was measured with 20 m point separation, whereas line separation was 200 m. Data has been reduced to Bouguer anomaly by the GTK. We removed the regional field from the Bouguer anomaly data with upward continuation and applied a high-pass filter to remove the high-frequency part. Three-dimensional unconstrained inversion was done with the UBC-GIF Mag3d inversion software. Joint interpretation of obtained density models and seismic sections shows a good correlation between structures with different densities and converted arrivals, which makes the results interpretable. In this study, we describe details of data acquisition and processing as well as the interpretation of Akanvaara Cr-V-PGE deposit models obtained by passive seismic coda wave interferometry and gravimetry. The joint application of these methods looks promising for brownfield exploration of massive orebodies.
How to cite: Afonin, N., Moisio, K., Kozlovskaya, E., and Yang, S.: Structure of Akanvaara Cr-V-PGE deposit in Northern Finland, obtained by passive seismic coda wave interferometry and gravimetry, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9884, https://doi.org/10.5194/egusphere-egu25-9884, 2025.
Airborne Full Tensor Magnetic Gradient (FTMG) data was acquired by SUPRACON AG in Ransko gabbro-peridotite massif of Czech Republic as a part of SEMACRET project activities. The area is known for numerous mineral deposits that have been intensively studied by Geological Survey of Czech Republic in the past. According to these studies, the known Ni-Cu and Cu-Zn mineralized zones occur as relatively narrow sub-vertical bodies inside mafic and ultramafic rocks. That is why direct detection of these zones by traditional total magnetic intensity (TMI) mapping is challenging due to high values of magnetic susceptibility of surrounding rocks. However, petrophysical studies show that mineralized zones in Ransko have generally the higher values of magnetic susceptibility than the mafic and ultramafic rocks there, which means that the high-resolution FTMG technology could be capable to map these mineralization zones directly. Therefore, demonstration of possibilities of the FTMG airborne technology to map directly mineralized zones in orthomagmatic mineral deposits was one of the purposes of airborne FTMG measurements in Ransko. The measured area was 3,8 km x 5,6 km large, with flight line spacing of 100 m. After raw data reprocessing that included data correction, synchronization, balancing, coordinate transforms and tensor build, the resulting data was low-passed filtered and resampled into a regular grid. The FTMG data included six magnetic gradient tensor components (Bxx, Bxy, Bxz, Byy, Byz, Bzz). In addition, the TMI map was calculated based on the mentioned data set and resampled for proper use after an adapted filtering. A comparison between TMI map, different FTMG component maps and the geological map showed that anomalies associated with outcropped mineralization zones are either weakly visible or not visible in the TMI data whereas anomalies that are spatially coincident with the outcropped mineralized zones are clearly visible in the FTMG components data. For more detailed data processing and inversion we selected an area that contains the known outcropped deposits. In order to obtain the 3D distribution of mafic and ultramafic rocks inside the Ransko massif we inverted the FTMG data using the UBC-GIF (University of British Columbia-Geophysical Inversion Facility) MAG3D-software. The model demonstrates large amounts of mafic and ultramafic rocks with high magnetic susceptibility inside the Ransko massif. To detect anomalies in FTMG data that could be related to compact inversion source structures (mineralized areas) we applied the Helbig’s transform. Based on these results we selected several areas with compact sources for more detailed modeling and inversion of FTMG data. We used a parameterization of compact sources represented by magnetic ellipsoids of arbitrary orientation and different main axes. The FTMG data was then inverted using ideal point method of multi-objective optimization. The parameters of magnetized bodies obtained were verified with the known geological and petrophysical information. Generally, our study demonstrated that the airborne FTMG surveys can be used to directly map the mineralized zones inside mafic and ultramafic complexes.
How to cite: Kozlovskaya, E., Sarala, J., Moisio, K., Nevalainen, J., Schneiderer, M., and Kobow, J.: Modelling and inversion of FTMG airborne data acquired in Ransko gabbro-peridotite massif (Czech Republic), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21419, https://doi.org/10.5194/egusphere-egu25-21419, 2025.
The global push for sustainable energy and critical mineral resources is driving remarkable advancements in geoscience, including the widespread adoption of machine learning, numerical simulations and data fusion techniques, as well as the acquisition of large geophysical and geochemical datasets worldwide. These developments, coupled with recent advances in ultra-fast computational solvers, are unlocking the potential for large data-driven simulations and joint inversions for the complete physical state of the Earth's lithosphere that were traditionally considered impractical. These developments are blurring the traditional boundaries between geodynamics, geochemistry, and inverse geophysical theory, steering in a new generation of multi-scale and multi-observable exploration tools.
In this presentation, we will discuss the concept of Multi-Observable Thermochemical Tomography (MTT), a powerful technique that integrates multi-scale joint inversion of multiple datasets, machine learning, and numerical modeling to obtain probabilistic models of the lithosphere's thermochemical structure with unprecedented resolution and confidence. MTT serves as a unifying data-fusion platform, providing critical proxies that enable the application of the mineral systems approach in exploration. These two methodologies are inherently complementary, reinforcing each other to enhance predictive targeting and resource discovery. We will showcase recent advances in MTT and related techniques that illustrate the potential of integrating MTT with the concept of mineral systems to enhance predictive targeting and resource discovery during greenfield and brownfield exploration of critical minerals.
How to cite: Afonso, J. C., Jamasb, A., Navir, M., and Aranguren, D.: Imaging Mineral Systems in Space and Time: New Data-Fusion Methods and Their Potential for Exploration, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9066, https://doi.org/10.5194/egusphere-egu25-9066, 2025.
The Bolnisi mining district in Southern Georgia belongs to the central segment of the Tethyan orogenic and metallogenic Belt. It is located in the eastern extremity of the Turkish Eastern Pontides and the northern part of the Jurassic-Cretaceous sedimentary-volcanic Somkheto-Karabagh belt of the Lesser Caucasus. The Late Cretaceous (~87–71 Ma) bimodal explosive volcanism in this region resulted in mafic and felsic rock types, the latter being a major host of the ore deposits and prospects, and being defined locally as the felsic Mashavera and Gasandami suites. The Late Cretaceous Sakdrisi gold-copper epithermal deposit is a major deposit in the Bolnisi district where different projects are going on. The Late Cretaceous sequences in this region are subdivided into six volcanogenic suites and corresponds to Cenomanian and Maastrichtian in age.
To better understand what controls the mineralization and the distribution of ores in the deposit, a 3D geological model have been built (in the Leapfrog Geo program) considering the distribution of lithological unit boundaries and structures at the Sakdrisi (Sakdrisi 4 and 5) epithermal deposit, based on outcrop observations, detailed mappings, and interpretations of drill core data. The ore types and their distribution in different levels between the Sak4 and Sak5 have always been a matter of question. Our new lithological approach, which included genetic naming of rocks, allowed us to perform correct paleovolcanological reconstructions together with structure in context and obtain a complete representation in the 3D model of the displacement of these stratigraphic units and the distribution of mineralization within them. The following lithological units were identified on Sakdrisi deposit: the upper non-mineralized volcano-sedimentary complex (UVSC) - Ignimbrite (IGN) and cross-cutting andesite-basaltic (AN_BA), and rhyodacite (RHD) dikes and lower mineralized (LVSC) volcano-sedimentary complex – pumice tuff (PT), massive fine-grained tuff (MFT), pumice tuff with the transition to fine-grained intervals (PTTI), layerd tuff (LT), ignimbrite like tuff (IGNT). The upper (UVSC) and lower (LVSC) complexes are separated by the thrust fault zone (central fault) including the sedimentary formation (SF) which is also non-mineralized. The central fault represents the upper limit of the mineralized zone. The lower base of the mineralization zone in Sak.4 is observed in some drill holes in layered tuff where the gypsum veins occur and also in ignimbrite-like tuffs. The explosive breccia pipes cross-cut all these lower mineralized lithological units on Sak.4 and Sak.5.
The high-grade ore zones are mainly localized in massive fine-grained tuffs, which are brittle and strongly silicified and of course connecting with the explosive breccia in matrix and also in the clasts. These tuffs easily succumbed to fractures developed by faults and fractures together with the explosive breccias, creating a favorable environment for the movement of ore-forming fluids and, consequently, the precipitation of metals. Two major trends of faults are recognized in the Sakdrisi deposit where dominant in the SE and NE directions. Both lithological and structural control on mineralization was convinced in the Sakdrisi deposit.
How to cite: Popkhadze, N., Gogia, B., Natsvlishvili, M., Shubitidze, J., Ananiashvili, G., Sonmez, S., and Moritz, R.: New lithological approach for the 3D Geological modeling of the Upper Cretaceous Sakdrisi Gold Copper Epithermal deposit in Bolnisi District, Lesser Caucasus, Georgia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15150, https://doi.org/10.5194/egusphere-egu25-15150, 2025.
Most sediment-hosted mineral deposits occur in marine sedimentary rocks along intracratonic or epicratonic rift basins at the edges of the thick continental lithosphere. Craton thickness, typically 150–200 km, was analysed using the Full-Waveform Seismic Tomography (REVEAL model) to extract horizontal shear wave velocity (Vsh), vertical shear wave velocity (Vsv), and isotropic P-wave velocity (Vp). Principal component analysis and k-means clustering revealed that Vsh effectively defines craton boundaries and similarly thick lithospheric features, aligning well with mineral deposits. IOCG and sediment-hosted deposits are found within ~125 km of these boundaries (based on total metal content) and ~100 km (based on ore tonnage). These deposits form along internal and external craton boundaries, separating Archean nuclei from Proterozoic terranes and along Phanerozoic orogens and accreted passive margins. Thermal and lithospheric models were used to differentiate cratons from other thick lithospheric features, isolating ~85% of all deposits related to the edge of cratons. Additionally, we found that more than ~85% of craton edge deposits are formed within 90 km of craton boundaries. A consistent gradient of increasing metal content with proximity to craton boundaries underscores the significance of these craton boundaries. In fact, more than 85% of known target craton edge deposits are concentrated within just 16% of continental areas, significantly enhancing exploration efficiency and resource discovery by reducing exploration areas.
Building on this foundation, we conducted a temporal analysis to explore why some craton boundaries are fertile while others are not, aiming to reduce exploration areas more. By analysing over 20 kinematic features using the latest reconstruction model spanning 1,800 Ma for craton deposits and uniformly generated random points within 180 km of craton boundaries, we reconstructed craton boundaries, deposits, and random points to identify key patterns. Lower craton velocities (<5 cm/year) emerged as a critical factor in mineralisation compared to random points, which can reach velocities up to 20 cm/year. This is likely driven by prolonged hydrothermal fluid circulation, enhanced fluid-rock interactions, sustained structural pathways, and extended thermal anomalies that support mineralisation. Similarly, lower Convergence rates (<4 cm/year) were associated with deposits, in contrast to random points with velocities up to 30 cm/year. The interplay between slower rifting and Convergence rates reflects the interconnected dynamics of tectonic and mantle processes, where reduced rifting rates weaken ridge push and slab pull forces, slowing subduction. In turn, slower subduction impacts mantle convection and lithospheric recycling, further reducing rifting rates in a complex feedback system. Additionally, we found that most deposits cluster within 400–1,800 km of subduction trenches at the time of formation, indicating a spatial relationship between tectonic activity and deposit formation. Deposits also tend to cluster around specific subduction lengths (~2,500 km and ~5,000 km), suggesting these tectonic settings provide more favourable conditions for mineralisation in contrast to the broader distribution of random points.
How to cite: Shirmard, H., Mather, B., Farahbakhsh, E., Czarnota, K., and Müller, R. D.: Spatio-Temporal Data Mining of Craton Edge-Related Mineralisation: Unveiling the Dynamics of Sediment-Hosted and IOCG Deposits, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3017, https://doi.org/10.5194/egusphere-egu25-3017, 2025.
The targeting till geochemical data set of Finland was collected during 1970s by the Geological Survey of Finland (GTK). It covers central Lapland, some areas in Ostrobothnia and eastern Finland. Targeting till geochemistry survey samples comprise soil samples collected by GTK along sampling lines in 1971–1983 and the point density of soil sampling varies between 6–12 samples/km2. The line interval is 500–2000 metres, and the point interval 100–400 metres. In total, there are 385 000 samples and from those samples, 191 559 locate in the Central Lapland. The samples were collected using percussion drilling with a flow-through bit and the sampling depth varies greatly, having on average 2 metres, where the maximum depth is 25.3 metres, and the minimum depth is 0.1 metres. A size fraction < 0.063 mm was sieved from the samples, and the concentrations of 17 chemical elements were analysed with an emission quantometer (EKV). As this data set contains elemental concentration for different depths, the aim of this study was to find the best suitable depth interval for finding orthomagmatic deposits. Thus, specific area from central Lapland was selected to study the depth profile of the samples. After data pre-processing, elements with acceptable quality were selected for further analysis emphasising on the elements those associate with orthomagmatic deposits. Then two methods for choosing the appropriate depth intervals were used. First, by detecting changes in both variance and/or mean. Second, choosing one metre intervals. These were then compared to see which method results in better outcome. For this comparison fuzzy logic was first used. Selected elements for fuzzy logic and their membership function were based on the detected correlation between elements by preforming principal component analysis (PCA). Furthermore, PCA determined elements groups. Three groups were recognised, these were 1) Mg-Cr-Ni, 2) Fe-Cu-Co with inverse Na-K values, and 3) Mn-V-Ti. Based on predicted maps generated in ArcGIS 10.8.1 for identified depth intervals, the depth range 1.7m to 3.6m demonstrated the highest potential to detect orthomagmatic mineral deposits. Compared to one metre interval approach where 2 m interval demonstrates the highest potential for deposits. Receiver operating characteristics (ROC) and area under the curve (AUC) were ultimately used to determine which of these approaches had the highest potential for exploration.
How to cite: Kalubowila, C., Raatikainen, M., and Sarala, P.: Identification of appropriate depth interval of high resolution targeting till data in Finland for mineral exploration , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18205, https://doi.org/10.5194/egusphere-egu25-18205, 2025.
Plant material can be used in mineral exploration as indicators of subsurface deposits based on their chemical composition. While the classic approach has been geobotany, this approach is severely hampered in areas where humans have completely altered the plant species occurrence, for example by using the landscape for forestry or agricultural purposes. The solution is to use the chemical composition of the plant material instead.
Within the EU project SEMACRET plant material had been tested to serve for mineral exploration on ultramafic host rocks in ultra-intensive agriculture. In intensive agriculture, it is clear that extensive use of fertilizers or heavy tillage of the soil disturbs the natural signals coming from the host rock and ultimately obscures the signal from the target mineral. To test this hypothesis, plant material was sampled from almond and olive farms in Portugal covering several ultramafic units and known mineralized outcrops. The orientation study data show that the chemical composition of the plant material discriminates between different mafic and ultra-mafic host rocks, even despite the intensive agricultural practices, and that elemental values of certain target elements are indicative of mineralization. It also shows that not all target elements work equally well on the mineralization tested, but that some target elements are likely to be too strongly altered by natural uptake of the plant and/or airborne dust contamination.
How to cite: Pospiech, S. and Dujmovic, L.: Using Plant Ionome for Mineral Exploration in Altered Landscapes: Insights from Intensive Agriculture in Portugal, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17751, https://doi.org/10.5194/egusphere-egu25-17751, 2025.
Mineral prospectivity modelling is a geospatial technique used to predict the likelihood of discovering economically viable mineral deposits in unexplored areas. This method integrates various geoscientific data, such as geological, geophysical, geochemical, and remote sensing data, using simple mathematical, statistical or artificial intelligence algorithms to identify regions with high mineral potential. By expert knowledge or by analysing spatial patterns and correlations between known mineral occurrences and various geological features, prospectivity modelling aids in reducing exploration risks and costs. It typically involves developing a mineral systems model for the mineral system of interest, feature selection and extraction through data processing, and applying predictive models. Newer methods involve unsupervised data-driven methods to eliminate bias from lack of knowledge. The output is a prospectivity map highlighting areas with varying probabilities of mineralisation. This approach is increasingly vital for sustainable mineral exploration, enabling more efficient targeting of resources while minimising environmental impact. Besides providing a brief overview of prospectivity modelling, this talk presents a case study from southern Portugal.
The layered gabbros of Beja are valuable sources of critical raw materials (CRMs) such as Titanium (Ti) and vanadium (V), which are considered critical by the European Union due to their high demand for modern industries and supply risk.
This study describes computer-based exploration targeting of evolved gabbros enriched in oxide ores using two approaches: (1) a first-pass data-driven unsupervised analysis and (2) a knowledge-driven analysis utilising Fuzzy Inference Systems (FIS), a knowledge-based artificial intelligence technique.
The first pass data-driven analysis employed self-organising maps, a machine learning-based clustering algorithm that generated clusters of features from geophysical data such as magnetic, gravity and topography. Clusters representing differentiated gabbros were isolated based on a geological review of the clusters. This led to identifying new targets in the northwestern part of the study area, where new outcrops were found during a subsequent field visit. The analysis also helped generate more robust datasets for the knowledge-driven study.
The FIS model relies on a generalised mineral systems model to identify targeting criteria and the FIS's structure. The mineral system model includes (1) Primitive, mantle-derived, metal-rich magmas emplaced in a syn-post collisional setting, serving as metal sources; (2) trans-lithospheric faults and suture zones acting as magma pathways; and (3) dilatational zones of high, fracture-related permeability and localised structures that physically trap the mineralising fluids, allowing fractional crystallisation to generate evolved, oxide rich gabbros.
Spatial proxies representing critical processes of the mineral system were mapped from various geoscientific datasets in the form of GIS predictor maps. This study also included singularity maps detecting geochemical anomalies based on the methods described by Gonçalves et al. (2024). All predictor maps were incorporated into the FIS model to generate the prospectivity map highlighting promising areas for further exploration.
The two approaches utilising different inputs form a complimentary workflow, enhancing exploration targeting.
How to cite: Aranha, M., Bartolomeu, B., Gonçalves, M. A., Jesus, A. P., Oliveira, A., and Dias, M.: Uncovering hidden resources: Geospatial techniques in mineral prospectivity modelling and their application to Beja's layered gabbros, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16308, https://doi.org/10.5194/egusphere-egu25-16308, 2025.
How to cite: Puchhammer, P. and Filzmoser, P.: Leveraging spatial anomaly detection for mineral exploration, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11314, https://doi.org/10.5194/egusphere-egu25-11314, 2025.
Porphyry systems host most of the mineable copper reserves globally, a metal experiencing unprecedented demand due to global electrification and decarbonisation trends. While porphyry systems are known to form in magmatic arcs along subduction zones, the precise roles of factors within the subducting and overriding plates remain poorly constrained, complicating prospectivity mapping. In this study, we develop a machine learning-based mineral prospectivity model for porphyry mineralisation, trained on known occurrences and spatio-temporal features derived from a modified plate motion model for the western Tethyan region, incorporating reconstructions of ocean basins spanning 90 Ma to the present. This segment of the Tethyan convergence zones represents a complex tectonic environment shaped by the diachronous collision of the Arabian and Eurasian continents, and our plate motion model reconstructs the spatio-temporal evolution of subduction and collision processes in this region. The initial soft collision, where the thinned Arabian passive margin collided with southern Eurasia, began ~42 Ma along the eastern Bitlis suture zone, transmitting strain into eastern Anatolia, the Caucasus, and northwestern Iran. Collision propagated westward into central Anatolia and southeastward into the northwestern Zagros by the late Eocene (40–35 Ma), followed by central Zagros (35–25 Ma) and southeastern Zagros (25–15 Ma). We defined a segmented passive margin line representing collisional boundaries and timings to capture this diachronous process, integrating collision propagation, strain transmission, and crustal deformation across the western Tethyan region in our reconstruction model.
Our time-dependent mineral prospectivity model illustrates the temporal evolution of porphyry mineralisation across the western Tethyan Belt, highlighting several high-prospectivity zones that lack known deposits and thus represent promising exploration targets. Feature importance analysis reveals the complex mechanisms driving porphyry mineralisation, identifying key predictors: arc segment length, distance to the nearest trench edge, and the orthogonal component of the relative motion vector. The length and curvature of arcs emerge as critical features, with tightly curved arcs linked to enhanced compressional stress and fracturing, promoting magma ascent and porphyry formation. The median distance to the nearest trench edge for known deposits is about six degrees, which exceeds the typical arc distance from the plate boundary, suggesting a distinctive feature of porphyry processes in this region. The orthogonal convergence rate is also pivotal, with higher magnitudes correlated to mineralisation. This indicates rapid convergence enhances metasomatism and partial melting processes in the overriding plate, facilitating porphyry formation. Our results demonstrate the effectiveness of combining plate motion models and machine learning to advance mineral exploration along subduction zones in the western Tethyan Arabia-Eurasia convergence zone. This approach is adaptable to data-poor regions and other time periods globally, offering significant potential for identifying new porphyry targets.
How to cite: Farahbakhsh, E., Heidari, E., Zahirovic, S., McInnes, B. I. A., Kohlmann, F., Seton, M., and Müller, R. D.: Machine learning and tectonic reconstructions: Unlocking porphyry copper exploration in the western Tethyan region, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1730, https://doi.org/10.5194/egusphere-egu25-1730, 2025.
Exploration drilling is a crucial yet expensive process for gaining insights into subsurface environments. With the rising demand for critical minerals needed for the green energy transition, the number of exploration projects has significantly increased. Traditional geostatistical methods are commonly used for mineral resource estimation, but they often depend on dense and extensive datasets, making them challenging for small-scale explorations and environmentally sensitive areas. This study explores the use of machine learning (ML) techniques, specifically Extreme Gradient Boosting and Random Forest, to improve mineral resource estimation in the Ransko region. ML methods present a groundbreaking approach by predicting target variables in unsampled locations using minimal and distant data, effectively reducing environmental impact and exploration costs. Additionally, ML can incorporate geological interpretations and account for spatial continuity, enhancing the quality of estimates and leading to more efficient and sustainable mineral exploration practices.
How to cite: Lindi, O., Aladejare, A., Wertich, V., Ranta, J.-P., and Yang, S.: Advancing Mineral Resource Estimation with Machine Learning: A Case Study from Ransko., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18166, https://doi.org/10.5194/egusphere-egu25-18166, 2025.
The Exploration Information Systems (EIS) ( https://eis-he.eu; Horizon Europe grant No. 101057357) project aims to create mineral prospectivity tools and a user-friendly GIS-wizard and to conduct real world testing of those tools on selected study sites containing known mineralisation. Geological Survey of Sweden (SGU) initiated several multidisciplinary mapping projects in Sweden on thematic mapping of energy, battery and innovation critical mineral and metals. The new data on geology, geophysics and geochemistry as well as new age dating from rocks are carried out within a framework of SGU’s mapping projects in conjunction with the EIS project. A mineral system for lithium mineralisation has been defined which is presented partly in Sadeghi et al., (2024) and Lynch et al, (2024).
In Västernorrland, LCT pegmatites are dated to 1.8 Ga and may be linked to S-type granites formed around 1.84-1.85 Ga. Updated geological maps, incorporating geological fieldwork and geophysical data, show that lithium mineralisation often occurs in association with the contact between granites and preserved sedimentary rocks, and indicate these granites formed by partial melting of magmatic intrusions. Lithium bearing pegmatites typically align with preexisting planar structures in meta-supracrustal rocks, suggesting that earlier structures acted as pathways or traps for volatile-rich melts. Localised ductile deformation may have influenced pegmatite emplacement, as evidence by folded pegmatite forms. This structural information combined with fault kernel density maps, highlight the pathways critical for lithium mineralization. According to field observations, lithium pegmatite mineralisation in Västernorrland is linked to older mafic rocks (e.g., amphibolite, gabbro, andesite) that act as physical traps, and graphite schists that occur in the area interlayered with metasedimentary rocks that may act as chemical traps due to higher content of S and C. A detailed study on till geochemical dataset carried out by Sadeghi et al., (2024) concluded that the Principal Component-4 of a selected trace elements dataset (La-Mn-Li) can represent a proxy for such a chemical trap.
Using this mineral system approach and the EIS toolkit, a new prospectivity map has been generated using “fuzzy method”. Fuzzy operators were used to create fuzzy memberships for each dataset input into the model and then overlain using fuzzy modifiers. The model was validated using known LCT pegmatite occurrences and locations of exploration concessions for LCT pegmatites. The results are validated by the existing known mineralization, claim areas for prospecting and the distribution of know LCT-pegmatite dykes. The model is well correlated to the validations area but there is space for improvement using more detailed data in the northwestern part of study area where a geological mapping project is ongoing.
Sadeghi, M., Casey, P., Carranza, E.J.M., Lynch, E.P (2024) . Principal components analysis and K-means clustering of till geochemical data: Mapping and targeting of prospective areas for lithium exploration in Västernorrland Region, Sweden. Ore Geology Reviews 167, 106002.
Lynch, E.P., Andersson, J.B.H., Sadeghi, M., Bauer, T., & Bečelytė, I. (2024). Stepwise magmatism and structural reactivation facilitates LCT pegmatite formation: Insights from central Sweden. 36th Nordic geological winter meeting, January 10–12 2024, Abstract volume. Geologiska Föreningen Specialpublikation 5, p. 131.
How to cite: Sadeghi, M., Casey, P., and Lynch, E. P.: Mineral systems anatomy linked to computational techniques for lithium mineral exploration targeting in Västernorrland region in Sweden, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6697, https://doi.org/10.5194/egusphere-egu25-6697, 2025.
Posters on site: Wed, 30 Apr, 16:15–18:00 | Hall X4
In geophysical exploration, combining magnetotelluric (MT) and ambient noise tomography (ANT) has proven to be an effective approach for investigating subsurface structures and detecting crustal anomalies. MT gives invaluable insights into variations in electrical conductivity, which can be a sign of fluid pathways, differences in rock types, and thermal anomalies. On the other hand, ANT provides versatile shear-wave velocity models that help map out structural differences and changes in crustal composition. The Curnamona Province, known for having one of the most electrically conductive crusts globally holds significant potential as a target for the MT and ANT methods. This area is particularly intriguing because of its series of conductivity anomalies that reach mid-crustal depths, with a notable eastern boundary located beneath the Mundi Mundi region. In this research, we combine 3D seismic and MT models through statistical clustering. Our goal is to connect these models in a way that allows us to identify regions with similar physical property groupings. Statistical clustering aids in organizing geophysical data, improving the clarity of crustal differences, and uncovering hidden structures like mineralized zones, fault systems, and geothermal reservoirs. The combination of MT and ANT via statistical clustering has provided valuable insights into the subsurface layout of the Curnamona-Mundi Mundi area. The findings highlight important subsurface characteristics, allowing us to distinguish rock types beneath sediment layers and pinpoint potential mineralized areas. This method effectively addresses the limitations of using individual geophysical methods, tackling resolution issues and minimizing interpretational uncertainties. By modeling structural features such as faults and lithological boundaries, this approach enhances the identification of key targets for mineral exploration.
Additionally, a 2D k-means clustering analysis is utilized on the post-inversion resistivity, gravity, and magnetic datasets to map out geological units and rock types. This method combines geophysical signatures to overcome the drawbacks of interpreting individual datasets by using a data-driven approach. The clusters match up well with existing geological maps offering more detailed insights and spotting underground geological formations and their links to possible mineralization areas.
How to cite: Bizhani, H., Heinson, G., Yeats, C., and DeTata, D.: Clustering-Based Integration of Magnetotelluric (MT) and Ambient Noise Tomography (ANT) for High-Resolution Imaging of Crustal Anomalies in the Curnamona-Mundi Mundi Region, Australia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7493, https://doi.org/10.5194/egusphere-egu25-7493, 2025.
The ongoing green transition and growing need for European raw material independence requires the development of innovative exploration methods, including mineral prospectivity mapping using machine learning (ML) based methods. The Exploration Information Systems project (Horizon Europe grant No. 101057357) has developed an open-source GIS plugin to enable user-friendly generation of mineral potential maps using ML using a mineral systems modelidentifying key evidentiary factors for mineralisation such as source, trap, modification and transport (McCuaig et al, 2010). Using a mineral systems model developed through studies of the REE-Line in Sweden, a prospectivity map has been generated using the random forest modelling tool within the EIS toolkit to test the toolkit and to identify potential new prospective areas for REE mineralisation.
REE mineralisation in Bergslagen, Sweden occurs primarily within skarn type polymetallic deposits formed within supracrustal carbonate layers, intercalated in metasupracrustal rhyolitic units dating from between 1.92-1.88 Ga. Key factors found to be favourable for REE mineralisation used as evidentiary layers in the RF model were: proximity to magnetic anomalies (source), principal components of geochemical signatures from glacial till (modifying processes), distance to linear structures and kernel density of linear structures (transport), evidence of K-Mg-Ca-Fe-Na alteration in bedrock and presence of carbonate/skarn horizons (trap) (Andersson et al., 2024).
RF models learning models require training data: i.e. points containing a deposit (1), or no deposit (0) to evaluate the probability any given pixel is to have a deposit. Due to the numerous occurrences of polymetallic deposits within the extent of the that lack REE mineralisations, two types of negative training points were used: mineralised polymetallic deposit with no REE occurrence, and non-mineralised points.
The final RF model demonstrated and a true positive rate of 59.02%, a false positive rate of 4%, and a true negative rate 36.6%. The RF model gave an area under curve of 0.97, demonstrating a probable overfitting of the data. This may be due to the somewhat smaller number of training points than is typically ideal for RF modelling (Carranza and Laborte, 2015). Additionally, the tight clustering of many of the training points may point to the need for a wider spatial distribution of positive training points to improve the model. The extent of mineral claims made by prospecting companies were overlain on the final model as a secondary validation of the map where good correlation was shown between the most prospective areas and current exploration. RF mapping of the REE line thus shows good potential, though improvements to training data are needed.
McCuaig, T. C., Beresford, S., & Hronsky, J. (2010). Translating the mineral systems approach into an effective exploration targeting system. Ore Geology Reviews, 38(3), 128-138.
Andersson, S. S., Jonsson, E., & Sadeghi, M. (2024). A synthesis of the REE-Fe-polymetallic mineral system of the REE-line, Bergslagen, Sweden: New mineralogical and textural-paragenetic constraints. Ore Geology Reviews, 106275.
Carranza, E. J. M., & Laborte, A. G. (2015). Random forest predictive modeling of mineral prospectivity with small number of prospects and data with missing values in Abra (Philippines). Computers & Geosciences, 74, 60-70.
How to cite: Casey, P., Sadeghi, M., and Andersson, S.: Mineral potential mapping of the REE-Line of Bergslagen, Central Sweden using random forest classifier modelling: application and testing of the EIS toolkit for prospectivity mapping. , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8128, https://doi.org/10.5194/egusphere-egu25-8128, 2025.
In light of the relatively low degree of exploration, limited drilling activities, and scarce indicators of source rocks in the West Sag of Wushi, a comprehensive study was conducted to analyze the distribution and potential of source rocks within the second member of the Liushagang Formation. This study integrated geological, geochemical, and seismic data alongside thermal simulation experiments for hydrocarbon generation.
The findings indicate that: (1) The activity of sag-controlling faults, base subsidence, and sedimentary infill in the West Sag of Wushi exhibit a positive correlation with the paleo-productivity values of source rocks identified in drilled wells. (2) The paleo-productivity values for source rocks from the second member of the Liushagang Formation in this region range from 200 to 771 gC/m²·a. Three types of source rocks have been identified—medium quality, good quality, and high quality—with respective volumes measuring 10.1 km³, 13.3 km³, and 16.4 km³. Notably, high-quality shale serves as the primary mechanism for hydrocarbon supply and is predominantly located at the center of the sag. (3) The bottom hydrocarbon generation conversion rates for medium-quality, good-quality, and high-quality source rocks within this formation are recorded at 70%, 80%, and 85% respectively; corresponding hydrocarbon generation amounts are estimated at 3.0×10⁷ t, 8.6×10⁷ t, and 5.1×10⁸ t respectively. These results suggest that this area has undergone significant hydrocarbon generation processes while demonstrating considerable potential for future hydrocarbon production.
How to cite: Su, G. and Liu, H.: Evaluation of Source Rocks Based on Geology, Geochemistry and Seismology: A Case Study of the Second Member of the Liushagang Formation in the Wushi West Sag, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8645, https://doi.org/10.5194/egusphere-egu25-8645, 2025.
This study explores remote sensing methods for locating rare earth and rare metal deposits in Kazakhstan, a country with abundant rare element resources. The focus is on modern remote sensing technologies for identifying geological objects and highlighting prospective areas for exploration. These methods can significantly reduce exploration costs by narrowing down target areas before conducting fieldwork.
Kazakhstan holds more than half of the world’s tungsten reserves and ranks fourth globally in molybdenum. The country has substantial potential to expand its rare earth and rare metal industries through both dedicated deposits and associated elements in other mineral bodies.
Kazakhstan’s deposits are classified into the following types:
- Pegmatite deposits
- Albitite deposits (albite granites)
- Skarn-greisen deposits
- Greisen-quartz vein deposits
- Greisen-stockwork deposits
- Porphyry deposits
- Weathering crust deposits
- Placer deposits
Deposits with associated rare elements include porphyry, stratified, and hydrogenic types.
We applied various remote sensing methods to identify specific types of deposits. In the Kalbinsky area, spectral index calculations revealed zones of metasomatism. In the Verkhne Espinskoye deposit, different processing techniques identified alkaline granites, stockwork bodies, and structural elements. For the Karakamskoye deposit, remote sensing detected pegmatite bodies and metasomatism zones. At Zhetygorinskoye, texture analysis revealed hidden structures, and principal component analysis identified pegmatites. The Minimum Noise Fraction method pinpointed hydrothermally altered areas.
Satellite data processing helped distinguish intrusive complexes, host rocks, and structural features. RS methods successfully separated different geological facies and highlighted metasomatism zones.
The results demonstrate that remote sensing technologies are highly effective in Kazakhstan. In this presentation, we will present a comparison of the effectiveness of these methods, showing how they enhance exploration accuracy while reducing costs. By remotely detecting key geological features before fieldwork, remote sensing minimises unnecessary expenses and maximises resource utilisation. The application of modern remote sensing tools contributes to more efficient exploration and better resource management in the country’s mining industry.
How to cite: Seib, N.: Remote Sensing Technologies for Rare Metal Deposits in Kazakhstan, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9251, https://doi.org/10.5194/egusphere-egu25-9251, 2025.
Several Cu-Ni(-PGE) sulfide deposits, including the economically important Kevitsa and Sakatti, are present in the northern Finland. These deposits are related to a ca. 2.05 Ga magmatic event, which is characterized by widespread komatiitic magmatism. Sulfide saturation was reached locally by sulfur assimilation from black shales or anhydrites, which are common in the sedimentary basin hosting the magmatic rocks. Following the Mineral System Approach, we characterized the mantle melting and crustal fractionation conditions for these komatiites to estimate their exploration potential on the regional scale. To do this, we compiled a comprehensive whole-rock and olivine chemistry database and used computational simulations to quantitatively assess their formation. Using a chilled margin of a komatiitic dyke and most primitive olivine populations (Fo92–94) from Kevitsa and Sakatti, we calculated parental melt compositions (MgO = 20.6–25.7 wt.%) for the komatiites. REEBOX PRO simulations indicate that a chemically homogeneous but thermally stratified (mantle potential temperature = 1575–1700 °C) plume from a depleted mantle source can produce the parental melts when the degree of partial melting is 14–22 %. The degree of melting is sufficient to completely dissolve sulfur from the mantle source based on sulfide saturation modeling. Compared to most Archean komatiites, the degree of melting is relatively low, which means that the parental melts of these Paleoproterozoic komatiites were less diluted in sulfur and metals. Fractional crystallization simulations conducted with Magma Chamber Simulator show that the parental melt compositions are compatible with the data from the natural komatiites. The MgO vs. Ni systematics of the simulated olivine are well compatible with most of the data from Kevitsa and Sakatti and highlight subpopulations of Ni-depleted olivine. The Ni-depleted olivine most likely formed from sulfide saturated melt, hence the simulated compositions can be applied for geochemical exploration. Sulfide saturation modeling indicates that, depending on the minor differences in the degree of melting or sulfur content of the mantle source, the sulfur content of the parental melt is about 110–800 ppm below sulfide saturation. Either Ni-rich or Cu-rich sulfide melt (Ni/Cu = 0.2–1.8) can precipitate from the fractionating melt without assimilation, whereas formation of more Ni-rich sulfides, as locally present in Kevitsa and Sakatti, requires either early sulfide saturation, likely driven by the assimilation of external sulfur. Our simulations indicate that the Paleoproterozoic komatiites in the northern Finland have high exploration potential because they inherited high sulfur and metal contents from the mantle source and because they were relatively close to sulfide saturation during fractionation.
How to cite: Virtanen, V. J., Höytiä, H. M. A., Iacono-Marziano, G., Yang, S., Moilanen, M., and Törmänen, T.: Exploration potential of the Paleoproterozoic komatiites in the northern Finland: computational simulations applied to the Mineral System Approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10943, https://doi.org/10.5194/egusphere-egu25-10943, 2025.
This study proposes an integrated subsurface data methodology to identify zones with mineralization potential in mining contexts, focusing on detecting geological targets based on their geophysical properties. The case study encompasses an area of 400 km² around the Riotinto mine in the Iberian Pyrite Belt (southern Spain), a region internationally recognized for its significant accumulations of massive sulfides deposits. Our methodology integrates stochastic geological models derived from detailed mapping with a joint probabilistic inversion of gravity and magnetic data. Bouguer and magnetic anomaly digital maps are used to generate probabilistic density volumes of the target area. Additionally, petrophysical data from over a thousand rock samples were analyzed and used to construct predictive models of P-wave velocity and, total porosity using advanced Machine Learning (ML) techniques.
The generated 3D models reveal the geometry of the main rock units. Geo-bodies can be differentiated within the multiparametric volume. These are characterized by high values for density and P-wave velocity, and low values for porosity. These rock units are key parameters for identifying mineralized structures. However, the available data on physical properties reveals an overlap between different lithologies and mineralized ore bodies which hinders the accurate discrimination of the latter. The models illustrate the presence of anomalous rock bodies, including mafic rocks located at shallow structural positions, and highly compacted slates at depths greater than 1250 m. These feature significant contrasts in their physical property values that could lead to false exploration targets. Considering this, we were able to establish a classification and prioritization system for zones based on their probability of containing mineralized bodies, identifying areas with greater potential of hosting ore structures in specific geological units. Finally, it is proposed to continue evaluating the applicability and effectiveness of this methodology in other geological and ore bearing settings, promoting its replicability and, aiding the development of more precise, efficient, and sustainable exploration techniques, aligned with the growing demand for strategic minerals necessary for a responsible energy transition.
*This work, funded under reference CPP2021 009072, has been supported by MCIN/AEI/10.13039/501100011033 (Ministry of Science, Innovation, and Universities/State Agency for Innovation) with funds from the European Union's Next Generation/PRTR (Recovery, Transformation, and Resilience Plan).
How to cite: Balaguera, A., Torné, M., Carbonell, R., Sánchez-Pastor, P., Vergés, J., Rodríguez, S., and Davoise, D.: 3D Modeling, Stochastic Joint Gravity-Magnetic Inversion, and ML for Anomalous Zone Identification in a Mining Context., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11526, https://doi.org/10.5194/egusphere-egu25-11526, 2025.
The REE-Fe-polymetallic mineral system along the REE-line in Bergslagen, south-central Sweden, encompasses a range of magnetite-rich iron oxide deposits with variable REE and polymetallic enrichments (e.g., Cu, Co, Bi, Mo, Au), including the notable Bastnäs-type REE deposits. As part of the EU-funded Exploration Information Systems project, in-situ Re-Os LA-ICP-MS/MS geochronology of molybdenite has been conducted across various mineralisations along the REE-line. This research aims to better delineate the timing of key ore-forming processes, link them to regional geological events, and assess the implications for mineral system modelling.
Mineralogical and textural evidence indicates a prolonged evolution of mineralisation within this system, involving multiple stages of REE mineral and Fe-Cu-Mo-Bi-(Co) sulphide formation. The sulphide-rich assemblages often occur as fracture fillings, veins, or bands with, and occasionally as inclusions within, allanite-group minerals. These assemblages are hosted within various mineralisation types, including recrystallised cerite-(CeCa) and bastnäsite-(Ce) ores, hydrothermally altered and metamorphosed volcanic rocks, carbonate rocks with serpentine-dominated pseudomorphs (“ophicalcite”), and amphibole ± pyroxene or andradite-dominated magnetite skarns.
The new Re-Os geochronology, combined with previously published data, reveals two primary age domains: ∼1.91–1.88 Ga and ∼1.87–1.83 Ga. The earlier domain aligns with primary mineralisation, formed through hydrothermal replacement of carbonate interlayers in a volcano-sedimentary succession during shallow-marine, sub-seafloor, and back-arc volcanic activity during the Svecokarelian orogeny. The younger domain is synchronous with ∼1.87–1.84 Ga magmatism in parts of Bergslagen and the peak of regional metamorphism in the studied area. The combined textural and age data are best explained by the remobilisation of different ore-forming components (e.g., REE, Fe, Cu, Mo, Bi) during regional metamorphism and deformation.
The findings offer new insights into mappable proxies for prospectivity mapping within the REE-Fe-polymetallic mineral system, particularly for processes related to pathways and sinks. They further underscore the protracted nature of mineralisation and highlight the significance of deformation- and metamorphism-related structures and features as additional exploration targets, particularly for identifying mineralisation types that diverge from the classical carbonate-replacement styles of Bastnäs-type deposits.
We acknowledge funding from the European Union’s Horizon Europe research and innovation programme for the project Exploration Information Systems under grant agreement No. 101057357.
How to cite: Andersson, S., Jonsson, E., Zack, T., Rösel, D., and Sadeghi, M.: Tracing ore-forming processes in the REE-Fe-polymetallic mineral system of the REE-line, Bergslagen, Sweden: Insights from LA-ICP-MS/MS Re-Os geochronology of molybdenite, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19240, https://doi.org/10.5194/egusphere-egu25-19240, 2025.
Unearthing mineral ore deposits involves a complex and resource-intensive endeavor that typically integrates the diversity of geological, geochemical, geophysical, and remote sensing data. This study can set a framework for a preliminary structure in mineral exploration through the application of machine learning and deep learning (ML/DL) techniques which is one of the most demanding approaches now a days in artificial intelligence (AI) world. Leveraging neural networks, convolutional techniques, and spectral analysis methods, our proposed efficient and time-saving approach seeks to uncover meaningful insights from large and intricate geospatial datasets. The workflow begins with the collection and preprocessing of diverse datasets, including Lithological unit, Tectonic component, Multispectral imagery, Geophysical anomaly, Geochemical composition, and point-based sample evidence of Copper and Graphite commodity (critical minerals in India) in Jharkhand and its surroundings. These data layers further stack and cross-correlate through ensemble supervised ML/DL algorithms and are taking through rigorous model sampling and training process to recognize trends indicative of mineralization, enabling automated identification and classification of mineralogical features for critical mineral deposits. Results from the application of this advanced technique in our study with some statistics such as (Area under the Receiver Operating Characteristics Curve (AUC-ROC), F1-score, Precision, Recall) > 0.85 which would be able to showcase the model's ability to identify prospective areas and generate insightful geologic depositional environments with an accuracy over 80%. This also validate with ground truth data and comparison with traditional exploration methods which demonstrate the effectiveness of the proposed approach. In conclusion, this approach surpasses traditional methods by incorporating temporal aspects and cost-effective analysis, revolutionizing the identification and prioritization of evolving patterns and trends in mineral occurrences. Mineral Prospectivity Mapping (MPM) is employed to predict the likelihood of mineral deposits, providing exploration teams with valuable information for targeted and efficient resource allocation.
Keywords: Mineralization, Iron Ore deposits, Mineral Prospectivity Mapping, Machine learning, Multispectral Imagery.
Graphical Abstract:
How to cite: Dutta, L., Munda, D., and Mandal, P. P.: Data-driven Mineral Prospectivity Mapping: Unlocking Critical Mineral Resources using Artificial intelligence techniques in Jharkhand and its Surroundings, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20402, https://doi.org/10.5194/egusphere-egu25-20402, 2025.
The Beja Layered Gabbroic Sequence (LGS) was emplaced in the southern border of the Ossa Morena Zone in Portugal during the Variscan orogeny climax. With an area of 315 km2 it remains one of the largest synorogenic intrusions worldwide, being chiefly preserved from postmagmatic tectono-metamorphic events. The intrusion hosts potentially economic oxide mineralization and ore showings developed at different evolution stages intrusion. It overlaps in time the Ni-Cu-PGE Aguablanca deposit (Spain), sharing also similarities in the geological setting, which led to an in-depth revaluation of LGS in the scope of HEU SEMACRET project (www.semacret.eu).
From W to E, the LGS comprises olivine leucogabbros and chromite bearing troctolites+wehrlites (SB I Series, Fo88) that formed from high-Mg, high-alumina parental melts. SB II Series represents a secondary chilled margin that is parental to polybaric assemblages of ferrodiorites and ferrogabbro, the latter hosting massive Fe-Ti-V oxide mineralisation at Odivelas (ODV I). A voluminous sequence with narrow compositional ranges formed under steady state replenishment/crystallization conditions (ODV II-ODV-III-BRG I-BRG II-BJA), locally showing evidence for large-scale channelled melt flow. The E block at Serpa (SRP) represents an isolated domain, forming a zoned lopolith with distinctive features, such as cumulus Opx, a primary hydrous character and a strong N-dipping foliation instead of the modal layering common to other Series.
The Nd-Sr-Os isotope compositions for LGS indicate derivation from a source slightly more enriched than the Depleted Mantle. Most Series follow typical AFC paths however troctolites show contaminated compositions due to the higher assimilating capability of most primitive melts. Modelling shows that marble and amphibolite country rocks cannot be the main contaminants for LGS magmas, thus implying a main contamination stage prior to their emplacement. The enriched components, increasing from W to E of LGS with SRP closing into the field of Aguablanca, suggest a progressive contamination of the magma source zones at the scale of the orogen.
Median V2O3 concentrations in spinel (> 1 wt%) are comparable to those reported for tholeiitic intrusions (e.g. Bushveld, Skaergaard) and significantly higher than in calk-alkaline-derived magmas. The synorogenic character can favour effective mechanical sorting of oxide-rich magma slurries, with BJA and SRP Series displaying multiple magnetic anomalies that require further investigation. While the assessment is very positive for oxide mineralization, indicators for magmatic Ni-Cu-PGE are mixed. The high-Mg chromite-bearing rocks include both depleted and undepleted olivine (Ni <2200 ppm) and indicate moderately positive fertility for sulfide mineralization. The ubiquitous presence of accessory sulfide blebs suggests sulfur saturation at an early evolving stage. The evidence for deep seated/source contamination increases the likelihood of sulfur saturation at lower crustal levels. This would have led to a decrease of the chalcophile budget in the magmas, as corroborated by the systematically high base/noble metal ratios and very low PGE abundances. The fertile ultramafic rocks at the LGS southern border are therefore the primary targets for magmatic sulfides as they may represent dismembered portions of the intrusion conduits.
-funded by the EU SEMACRET GA#101057741 and FCT I.P./MCTES through national funds (PIDDAC): UID/50019/2025 and LA/P/0068/2020 https://doi.org/10.54499/LA/P/0068/2020).
How to cite: Jesus, A. P., Oliveira, A., Bartolomeu, B., Mateus, A., Gonçalves, M. A., and Antunes Dias, M.: Assessing the mineral prospectivity of the Beja Layered Gabbroic Sequence, Portugal, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20765, https://doi.org/10.5194/egusphere-egu25-20765, 2025.
Posters virtual: Thu, 1 May, 14:00–15:45 | vPoster spot 4
EGU25-5044 | ECS | Posters virtual | VPS17
Advanced Copper Prospectivity Mapping in Northwestern India through Machine Learning and Multisource Data IntegrationThu, 01 May, 14:00–15:45 (CEST) | vP4.14
The growing demand for copper, driven by its critical role in green energy technologies such as electric vehicles and renewable energy systems, underscores the need to identify new copper resources. The Aravalli-Delhi Mobile Belt (ADMB), a geologically complex terrain spanning Rajasthan, Haryana, Gujarat, and Delhi, represents significant potential for copper mineralization within its Archaean to Neoproterozoic sequences. In this study, we developed a high-resolution copper prospectivity map for the ADMB by leveraging advanced machine learning techniques and integrating diverse geoscientific datasets. Our methodology incorporated geological features (e.g., proximity to folds, faults, and lineaments), geophysical data (gravity and magnetic anomalies), and remote sensing inputs (SRTM and LANDSAT imagery). Comprehensive processing of potential field data included upward continuation to multiple heights (500 m, 1000 m, 2000 m, 5000 m, 7500 m, 10,000 m, 15,000 m, 25,000 m, and 40,000 m), followed by the computation of first- and second-order directional derivatives, resulting in a total of 154 predictive features. Known copper deposit locations (56 in total) across the ADMB were used as training points, with feature sampling creating the dataset for machine learning model training. We addressed the challenge of class imbalance posed by the limited number of known deposits, by employing synthetic data generation techniques, including Variational Autoencoder (VAE) and Synthetic Minority Oversampling Technique with Generative Adversarial Networks (SMOTE-GAN). Comparative analysis showed that SMOTE-GAN produced more realistic synthetic samples, significantly improving model performance. The enriched datasets were used to train supervised learning models, including Explainable Boosting Machine and Random Forest, optimized within a Positive-Unlabeled (PU) Bagging framework to classify unlabeled regions. Our trained model achieved a predictive accuracy of 95.75% on an unseen dataset. The resulting copper prospectivity map effectively delineates high-probability zones, with nearly all known deposits falling within regions predicted to have probabilities >0.7. Our maps highlight regions of high prospectivity for copper resources that currently lack known deposits, suggesting potential new exploration targets.This demonstrates the robustness of our integrated data approach and machine learning models in identifying unexplored copper-rich areas within the ADMB. Our study highlights the importance of integrating geoscientific data with synthetic data generation to address data scarcity in mineral exploration. The demonstrated scalability of this framework provides a robust solution for prospectivity mapping in other similar Archaean to Neoproterozoic terrains worldwide.
How to cite: Kumar, M., Singh, S. P., Singh, U., Sarkar, S., Goyal, T., Sukhbir, S., and Shirmard, H.: Advanced Copper Prospectivity Mapping in Northwestern India through Machine Learning and Multisource Data Integration, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5044, https://doi.org/10.5194/egusphere-egu25-5044, 2025.
EGU25-10108 | Posters virtual | VPS17
The controlling factors of major metallogenic systems in south china based on gravity and magnetic analysisThu, 01 May, 14:00–15:45 (CEST) | vP4.15
Metallic deposits such as W-Sn, Cu-Au, rare earth deposits, thus serving as a “giant granary” of metal mineral resources in China(Lü et al.,2021). There are five large-scale metallogenic belts only in the east of South China, namely the Middle-Lower Yangtze River Metallogenic Belt (MLYMB), Qingzhou-Hangzhou Metallogenic Belt (QHMB), Nanling Metallogenic Belt (NLMB), Wuyishan Metallogenic Belt (WYSMB), and Xiangxi-E’xi Metallogenic Belt (XEMB).
The source zones of the mineral systems in major metallogenic belts in South China are reflected by the vertical structures of the lithosphere in this area. In MLYMB, the mineral systems of the Fe and Cu deposits have multi-level source zones. The initial-level source zone is the enriched mantle, which is formed owing to the thinning of the lithosphere and deformation caused by the fluids in the asthenosphere. In QHMB, the source zone of Cu deposits such as the Dexing deposit is the mantle, while the source zone of W deposits on the margin of the Moho uplift such as Zhuxi and Dahutang deposits is the remelted crust. As for QHMB, the W and Sn mineral systems originate from the crustal magma. In WYSMB, the diagenism and mineralization are mainly related to the interactions between materials in the crust and the mantle. The crust-derived materials form the deposits mainly containing W and rare earths, and mantle-derived materials form polymetallic deposits such as Cu and Au. As for XEMB, it consists mostly of metal deposits of the type of strata-bound sedimentation with the crust as the source zone, such as Sb, Pb, Zn, and Mn deposits.
The pathways of the mineral systems of the major metallogenic belts in South China are deep faults and block or terrane boundaries determined by edge detection of gravity anomalies, as well as density contrast boundaries obtained with the 3D density model. The metallogenic pathways of Fe and Cu deposits in MLYMB mainly include the Yangtze River deep fault in NE trending and Tongling-Taizhou fault in SE trending and its secondary faults. The eastern segment of QHMB is mainly controlled by the faults in northeast Jiangxi, the southern segment of QHMB and the NLMB are mainly under the control of the boundary faults of F1, and WYSMB is related to Zhenghe-Dapu fault and Heyuan-Shaowu fault.
A 3D density and susceptibility model was obtained by 3D gravity and magnetic inversion. The distribution of different types of deposits was qualitatively reflected by different combination of density and susceptibility model, revealing the distribution of termination sites of different mineral systems in South China.Mineral systems in this area, providing indications for future ore-prospecting exploration in South China.
How to cite: Yan, J., Zhou, Q., Chen, C., and Tang, H.: The controlling factors of major metallogenic systems in south china based on gravity and magnetic analysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10108, https://doi.org/10.5194/egusphere-egu25-10108, 2025.
