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Mineral resources are used in larger quantities than ever before in history, and are the basis of our modern society. The safe and sustainable supply of mineral resources is fostering a demand for innovative actions to cover the foreseeable future industry and human demands. Exploration is the first step in the mineral resources cycle. On one hand, most of the giant deposits at shallow depths have been already explored and mined out and the industry is moving towards deeper and more complex mineral systems, which brings significant exploration challenges. On the other hand, the exploration sector needs time-saving, cost-effective, and, particularly in Europe, environmentally friendly and socially acceptable techniques to ensure sustainable access to mineral resources.
This session aims to bring together geoscientists from various (e.g. remote sensing, geochemistry, geology, geophysics, modelling, mineralogy, structural geology) involved in mineral exploration for the 21st Century. Abstract submissions for this session can include, but are not limited to, the following topics: new methods of exploration; imaging; conceptual modelling and quantification of deposits and mineral systems; cost reduction in exploration; non-invasive exploration; integration of multidisciplinary methodologies and datasets; scale-up and replicability; industry-academia synergies and FAIR data repositories.

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Tentative schedule

14:00 EGU2020-2078ECS Mahmoud Mekkawi
14:06 EGU2020-12172ECS Jelena Markov
14:12 EGU2020-13586 Luís Lopes
14:18 EGU2020-20242ECS Helen Twigg
14:24 EGU2020-3598ECS Emma Soldevila
14:30 EGU2020-10911ECS Alba Gil
14:36 EGU2020-22146ECS Yesenia Martínez
14:42 EGU2020-11129 Alireza Malehmir
14:48 5-minutes break
14:54 EGU2020-19308 Sebastian Hölz
15:00 EGU2020-6682ECS Ulrich Kelka
15:06 EGU2020-10719 Louis Andreani
15:12 EGU2020-20765ECS Robert Jackisch
15:18 EGU2020-13563ECS Sam Thiele
15:24 EGU2020-13526ECS Cecilia Contreras
15:30 EGU2020-13121ECS Giorgia Stasi

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Co-organized by SM1
Convener: Juan AlcaldeECSECS | Co-conveners: Louis AndreaniECSECS, Ramon CarbonellECSECS, Alba Gil de la IglesiaECSECS, Fernando Tornos
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| Attendance Fri, 08 May, 14:00–15:45 (CEST)

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Chat time: Friday, 8 May 2020, 14:00–15:45

Chairperson: Alba Gil, Ramon Cabronell, Fernando Tornos, Louis Andreani and Juan Alcalde
D757 |
EGU2020-617
Irina Sidorova

This study was made with complex geophysical and geological observations by the DSS-MRW seismic reflection and refraction profiles, which cross Uzbekistan. The aim of our study was to reveal new features, which are characteristic of the upper mantle rocks, related to morphology of bodies, their physical properties, consisting mainly in their contrasting values for contiguous blocks, and general increased velocity and density of the rocks they contain.  The methodology of establishment of integrated dynamic interactive models on ore-magmatic concentres consists of two consecutive stages including: 1) the methodology of integrated geological-geophysical processing and interpretation of potential fields and seismic profiles cross cutting ore-magmatic concentres; 2) the methodology of creation of a united interactive 3-D model in ArcGIS in combination with materials of remote sensing. Each of these stages is divided into more detailed sub-stages. During the study of the deep structure of ore-magmatic concentres, the first step is the integrated methodology of the processing and interpretation of potential fields. It is mainly orientated at the identification of positions of geometric borders of the division of mediums determined by the data of seismic exploration of preferably deep seismic sounding. Our experiences shows  that the use of these potential fields for the area zoning of the territory, identification of the depth of manifestation of isolated blocks and their density may significantly affect the interpretation of seismic exploration data. Therefore, the implementation of the method-based interpretation of data of gravitational and magnetic fields preceding, the stage of the construction of the integrated model enables a more complete use of opportunities of these methods. Anomalous objects are isolated in the Earth crust on the basis of the interpretation of potential fields using the methods of the solution of direct and inverse tasks. An integrated interpretation of potential fields enablers the maximal use of information available in this field for the analysis of the deep structure. The processing of data is an important integrated part of the whole process of development of the 3-D model of the ore-magmatic concentre within the frames of the GIS project. New regional features have been revealed: they include peculiarities of the Earth's crust's deep geological structure and spatial distribution of deposits; they are contact areas of the Earth's crust geoblocks with anomalously high and low seismic and density parameters. Mapping of these zones helps select new ways in the search for mineral deposits.

 

How to cite: Sidorova, I.: Integrated dynamic interactive models of ore-magmatic concentres in Uzbekistan , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-617, https://doi.org/10.5194/egusphere-egu2020-617, 2020.

D758 |
EGU2020-2078
Mahmoud Mekkawi, Ayman Ismail, Mohamed Al Deep, Sultan Arafa, Mahmoud Abdel Hai, and Abbas Mohamed

The Haimur gold mine is located in the south Eastern Desert, Egypt, about 200 km far from Aswan city and is known as historical mine dated back to (7th–11th centuries). An evidence of ancient mining activities is manifested by excavated quartz veins and old stone tools used for gold extraction. A number of important ancient gold mines in the Allaqi area have, however, received relatively little geological and geophysical attention. Haimur area comprises a variety of Precambrian rocks including igneous and metamorphic units. It is covered by: ophiolite assemblage, metasediments and metavolcanic.

The geophysical measurements are carried out along the ancient mine where the quartz veins are concentered. Several geoelectrical and land magnetic profiles were done perpendicular to the structure of the area, The Electrical Resistivity was acquired by using dipole-dipole configuration of electrode spacing 5, 10 and 15 m of lengths ranging from 160-240 m. In additional to magnetic profiles are applied around old mine. The results indicate that the quartz veins are accomplished with sulfide zones which refer to low resistive zones, high chargeability with moderate to high magnetic anomalies.

Key words: South Eastern Desert, Alter mineralized zone, Land magnetic, Electrical Resistivity and Induced polarization.

How to cite: Mekkawi, M., Ismail, A., Al Deep, M., Arafa, S., Abdel Hai, M., and Mohamed, A.: The Mineral Exploration of the Haimur Gold-Mine in the South Eastern Desert-Egypt, by Using Geophysical Techniques, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2078, https://doi.org/10.5194/egusphere-egu2020-2078, 2020.

D759 |
EGU2020-8035
Laura Tusa, Mahdi Khodadadzadeh, Margret Fuchs, Richard Gloaguen, and Jens Gutzmer

Mineral exploration campaigns represent an essential step in the discovery and evaluation of ore deposits required to fulfil the global demand for raw materials. Thousands of meters of drill-cores are extracted in order to characterize a specific exploration target. Hyperspectral imaging is recently being explored in the mining industry as a tool to complement traditional logging techniques and to provide a rapid and non-invasive analytical method for mineralogical characterization. The method relies on the fact that minerals have different spectral responses in specific portions of the electromagnetic spectrum. Sensors covering the visible to near-infrared (VNIR) and short-wave infrared (SWIR) are commonly used to identify and estimate the relative abundance of minerals such as phyllosilicates, amphiboles, carbonates, iron oxides and hydroxides as well as sulphates (Clark, 1999). The distribution of these mineral phases can frequently be used as a proxy for the distribution of ore minerals such as sulphides. Typical core imaging systems can acquire hyperspectral data from a whole drill-core tray in a matter of seconds. Available sensors record data in several hundreds of contiguous spectral bands at spatial resolutions around 1 mm/pixel.

​​In this work, we apply a local high-resolution mineralogical analysis, such as SEM-MLA (Kern et al., 2018), for a precise and exhaustive mineral mapping of some selected small samples. We then upscale these mineralogical data acquired from thin sections to drill-core scale by integrating hyperspectral imaging and machine learning techniques. Our proposed method is composed of two main steps. In the first step, after initially co-registering the hyperspectral and high-resolution mineralogical data and making a training set, a machine learning model is trained. In the second step, we apply the learned model to obtain mineral abundance and association maps over entire drill-cores.

​​The mapping is further used for the calculation of other mineralogical parameters essential to exploration and further mining stages such as modal mineralogy, mineral association, alteration indices, metal grade estimates and hardness. The proposed methodological framework is illustrated on samples collected from a porphyry type deposit, but the procedure is easily adaptable to other ore types. Therefore, this approach can be integrated in the standard core-logging routine, complementing the on-site geologists and can serve as background for the geometallurgical analysis of numerous ore types.  

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​​Clark, R. N., 1999, “Spectroscopy of rocks and minerals, and principles of spectroscopy,” in Remote sensing for the earth sciences: Manual of remote sensing, vol. 3, John Wiley & Sons, Inc, pp. 3–58.

​​Gandhi, S. M. and Sarkar, B. C., 2016, “Drilling,” in Essentials of Mineral Exploration and Evaluation, pp. 199–234.

​​Kern, M., Möckel, R., Krause, J., Teichmann, J., Gutzmer, J., 2018. Calculating the deportment of a fine-grained and compositionally complex Sn skarn with a modified approach for automated mineralogy. Miner. Eng. 116, 213–225.

How to cite: Tusa, L., Khodadadzadeh, M., Fuchs, M., Gloaguen, R., and Gutzmer, J.: Hyperspectral drill-core imaging for ore characterization, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8035, https://doi.org/10.5194/egusphere-egu2020-8035, 2020.

D760 |
EGU2020-12172
Jelena Markov and Gerhard Visser

The Cloncurry region lies in NW of Queensland and includes the Mount Isa Inlier, one of the most highly endowed metallogenic provinces in Australia, which has a long history of mining and exploration. The area is covered by the Jurassic-Cretaceous Carpentaria and Eromanga Basin sediments with the Mount Isa Inlier outcropping to the West and South. The fully concealed Millungera Basin underlies younger basins to the East. In order to de-risk further mineral exploration in this region it is important to know the thickness of cover. There are a variety of geophysical data available that can be used to estimate cover thickness. The point depth estimates of cover are derived from geophysical data using different inference methods. In order to create a map, these individual depth estimates must be reconciled/interpolated. The conventional interpolation methods do not produce the most optimal solution since these methods don’t easily account for discrepancies in the geophysical data distribution, resolution of the data and consequently variable accuracy of the cover thickness depth estimates. Also, most of these techniques do not produce an uncertainty estimate of the result. We have developed a Bayesian estimate fusion method that accounts for the variable data inaccuracies of the point cover thickness estimates which produces a map of cover thickness and its uncertainty. Additionally, the method uses non-intersecting drill holes, which were not usually utilised to create a map of the cover thickness. The method deals with outliers, by differentiating between the point depth estimates related to the cover-basement interface and the false positives that might be coming from the intrasedimentary units or the deeper basement. Lastly, the method incorporates existing fault information which allows to better capture sharp cover thickness changes.

How to cite: Markov, J. and Visser, G.: Reconciling Cover Thickness Estimates in Cloncurry Region in Queensland, Australia using Bayesian Estimate Fusion, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12172, https://doi.org/10.5194/egusphere-egu2020-12172, 2020.

D761 |
EGU2020-13586
Márcio Pinto, Norbert Zajzon, Luís Lopes, Balazs Bodo, Stephen Henley, José Almeida, Jussi Aaltonen, Claudio Rossi, and Gorazd Zibret

The UNEXUP project, funded under EIT Raw Materials, is a direct continuation of the Horizon 2020 UNEXMIN project. While in UNEXMIN efforts were made towards the design, development and testing of an innovative exploration technology for underground flooded mines, in UNEXUP the main goal is to push the UNEXMIN technology into the market, while further improving the system’s hardware, software and capabilities. In parallel, the aim is to make a strong business case for the improved UNEXUP technology, as a result of tests and data collection from previous testing. Improvements to the UX-1 research prototypes will raise technology readiness levels from TRL 6, as verified at the end of the UNEXMIN project, to TRL 7/8 by 2022. A "real service-to-real client" approach will be demonstrated, supporting mineral exploration and mine surveying efforts in Europe with unique data from flooded environments that cannot be obtained without high costs, or risks to human lives, in any other ways.

The specific purpose of UNEXUP is to commercially deploy a new raw materials exploration / mine mapping service based on a new class of mine explorer robots, for non-invasive resurveying of flooded mines. The inaccessibility of the environment makes autonomy a critical and primary objective of the project, which will present a substantial effort in resurveying mineral deposits in Europe where the major challenges are the geological uncertainty, and technological / economic feasibility of mine development. The robot’s ability to gather high-quality and high-resolution information from currently inaccessible mine sites will increase the knowledge of mineral deposits in Europe, whilst decreasing exploration costs – such as the number of deep exploration drillholes needed. This can potentially become a game changing technology in the mining panorama, where the struggle for resources is ever increasing.

On the technical side, a fourth robot, modular in nature, will be added to the current multi-robot platform, providing additional functionalities to the exploration system, including better range and depth performance. Hardware and software upgrades, as well as new capabilities delivered by the platform will greatly extend the usefulness of the platform in different environments and applications. Among these: rock sampling, better data acquisition and management, further downsizing, extended range, improved self-awareness and decision making, mature post-processing (such as the deployment of 3D virtual reality models), ability to rescue other robots, and interaction with the data will be targeted during the next years. Upgrading the overall technology with these tools, and possibly additional ones, will allow the system to operate with more reliability and security, with reduced costs.

These added functions arise from different stakeholders’ feedbacks from the UNEXMIN project. UNEXUP targets parties from the mining, robotics and mineral exploration sectors, as well as all other sectors that have any kind of underwater structure that needs to be surveyed – caves, underground reservoirs, water pipelines and fisheries are among them. For the purpose of exploitation of the technology, a joint company was founded, “UNEXMIN GeoRobotics Ltd”, which is part of the UNEXUP consortium, and is responsible for selling the service to the market.

How to cite: Pinto, M., Zajzon, N., Lopes, L., Bodo, B., Henley, S., Almeida, J., Aaltonen, J., Rossi, C., and Zibret, G.: Making exploration of underground flooded mines a reality - the UNEXUP solution, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13586, https://doi.org/10.5194/egusphere-egu2020-13586, 2020.

D762 |
EGU2020-19269
Malcolm Aranha, Alok Porwal, Manikandan Sundaralingam, Amber Markan, Ignacio González-Álvarez, and Karunakar Rao

The rare earth elements (REEs) are a group of seventeen metals including 15 lanthanides, scandium and yttrium.  These metals have been projected to be critical for future industrial development. However, India currently does not have any economic grade primary deposit of REEs; all of India’s production comes from monazite-bearing beach sands along the eastern and western coasts that have been derived from REEs-enriched continental rocks such as pegmatites or carbonatites. This contribution documents a GIS-based prospectivity model for exploration targeting of REE associated with carbonatites and alkaline-complexes in the geologically permissive tracts of NW India comprising parts of western Rajasthan and northern Gujarat. A mineral systems approach is applied to model the key ingredients of an REE system including geodynamic setting; fertile mantle/crustal sources of REEs; deep to shallow crustal architecture; and REE deposition.  This conceptual genetic model of REE mineral systems is, in turn, used to identify the key regional-scale REE-deposit targeting criteria in NW India. Regional-scale multi-parametric exploration datasets are processed to represent the targeting criteria in form of predictor GIS layers. Finally, an expert-driven fuzzy inference system is designed for delineating and raking prospective REE targets. Simultaneously, the stochastic and systemic uncertainties in the prospectivity modeling are modelled to delineated (a) high priority REE exploration targets areas with low uncertainty and high prospectivity for immediate ground follow up and (b) areas with high uncertainty and high prospectivity for further data acquisition in order to reduce uncertainty.

How to cite: Aranha, M., Porwal, A., Sundaralingam, M., Markan, A., González-Álvarez, I., and Rao, K.: Regional scale prospectivity modelling of NW India for REE deposits associated with carbonatites and alkaline complexes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19269, https://doi.org/10.5194/egusphere-egu2020-19269, 2020.

D763 |
EGU2020-19308
Hölz Sebastian, Haroon Amir, Konstantin Reeck, and Jegen Marion

Seafloor massive sulfides (SMS) are regarded as a potential future resource to satisfy the growing global demand of strategic metals. Aside from mining and retrieving profitable amounts of massive sulfides from the seafloor, the present challenge is to detect and delineate significant SMS accumulations, which are generally located near mid-ocean ridges and along submarine volcanic arc and backarc spreading centers.

In the past years we have used the marine transient electromagnetic induction system MARTEMIS, a coincident-loop TEM system developed at GEOMAR (Kiel, Germany), in various marine geological settings for the detection and characterization of SMS in the shallow seafloor down to a depth of ~30m. The system was also used in combination with remote EM receivers (Coil2Dipole experiment) to allow for investigations of conductive structures, which are covered by up to ~100m of sediments.

We present experiments from two locations, one at an inactive site in the Mediterranean (Palinuro, Tyrrhenian Sea) where the occurrence of SMS had previously been confirmed by drilling, and one active site on the Northern Mid-Atlantic Ridge (Grimsey Hydrothermal Field, offshore Northern Iceland) where no SMS have been found in gravity cores up to now. The results demonstrate the suitability of the system to detect, delineate and characterize SMS even in scenarios, where the mineralizations are no longer connected to any hydrothermal activity or are buried under a sedimentary cover.

How to cite: Sebastian, H., Amir, H., Reeck, K., and Marion, J.: Electromagnetic experiments for the detection and characterization of seafloor massive sulfides: two case studies from the Mediterranean and Northern Mid-Atlantic Ridge, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19308, https://doi.org/10.5194/egusphere-egu2020-19308, 2020.

D764 |
EGU2020-19105
Adrian Flores Orozco, Lukas Aigner, Timea Katona, Matthias Bücker, Philipp Zehetgruber, and Alexander Römer

The prospection of electrical conductors and semi-conductors has been one of the classical applications of the induced polarization (IP) method, with recent laboratory studies permitting to gain a deeper insight into the parameters controlling the polarization response. However, the application of electrochemical models developed for laboratory measurements has been rarely taken into field-scale imaging data sets. To fill this gap, here we discuss IP imaging results collected in Zettlitz (Austria), a former quarry operated between 1855 and 1967 for the extraction of graphite, an electrical conductor. The general goal of the geophysical survey is to characterize the geometry and volume of the residual graphite at the site. To this end, frequency-domain IP imaging measurements were collected along 10 main transects using different geometries, with selected data sets collected in the frequency range between 0.25 and 1 Hz to gain information about the frequency-dependence of the electrical properties. As expected, initial measurements revealed a high IP response in the graphite-rich areas. Nevertheless, the high electrical conductivity of the materials resulted in low voltage readings and an important decrease in the signal-to-noise ratio for deep measurements; thus, significantly reducing the depth of investigation. To overcome this limitation, we conducted measurements at areas of interest using transient electromagnetic (TEM) soundings, which are favored by the high conductivity of the targeted graphite and permit a better delineation of the contact to the calcareous host-rock. Initial analysis of the TEM data revealed a poor consistency with the electrical models retrieved from the IP surveys. However, taking into account the IP effect within the inversion of the TEM data significantly improved the consistency in the subsurface models resolved by the different methods. In order to resolve for adequate parameters for the modeling of TEM signatures, IP measurements were also collected at relevant positions in the frequency-range between 0.01 and 10000 Hz, with a high accuracy electrical impedance spectrometer. Further IP measurements were also collected in rock samples in the laboratory to aid in the interpretation of the field surveys and to permit the numerical modeling of the electrical signatures using a recently proposed electrochemical model. Our results demonstrate that the combination of IP and TEM surveys provide an improved modeling of the field signatures and, thus, a better characterization of the site. Additionally, we discuss the applicability of existing empirical and numerical models for the quantitative interpretation of field surveys.

How to cite: Flores Orozco, A., Aigner, L., Katona, T., Bücker, M., Zehetgruber, P., and Römer, A.: Induced polarization and transient electromagnetic surveys for the characterization of a graphite ore, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19105, https://doi.org/10.5194/egusphere-egu2020-19105, 2020.

D765 |
EGU2020-18707
Bernd Trabi, Cornelia Tauchner, and Florian Bleibinhaus

Blasting operations in quarries are accompanied by ground vibrations which can endanger buildings nearby. A production blast is made of several holes with a small distance to each other, which are blasted with a time delay, to reduce the ground vibrations. These production blasts produce a specific radiation pattern. It would be favorable to focus the ground vibrations to a less dangerous direction or area. To optimize the radiation pattern of seismic waves the blast configuration can be modified. For the optimization an analytic solution, based on Fourier shift theorem can be used. This assumes a model with a homogeneous half space and similar source wavelets for low frequencies. Because we want to predict the ground vibrations for a more realistic inhomogeneous case, a numerical forward modeling on a 3D model of mount Erzberg was performed with a 3D elastic code with topography. The 3D model of mount Erzberg is the result of a tomographic travel time inversion. One problem is that the spectral response of a single blast is unknown and therefore we had to find a transfer function which transfers the numeric spectral response to the observed spectral response. After applying the transfer function the amplitude spectra of the numeric solution show a good match to the amplitude spectra of the observed production blasts. The main goal is to reduce the ground vibrations at sensitive areas. This is achieved by blasting simultaneously two blast arrays with a greater distance to each other with optimized time delays. To optimize the time delays we developed a global search algorithm, based on Marcov chain Monte Carlo method which finds potential blast configurations, with minimum impact to critical locations nearby the quarry. These blast configurations serve as proposal for real production blasts at mount Erzberg. This study is part of the EU-funded project SLIM (Sustainable Low Impact Mining, www.slim-project.eu).

How to cite: Trabi, B., Tauchner, C., and Bleibinhaus, F.: Radiation Characteristics of Seismic Source Arrays, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18707, https://doi.org/10.5194/egusphere-egu2020-18707, 2020.

D766 |
EGU2020-22146
Yesenia Martínez, Juan Alcalde, David Martí, Puy Ayarza, Mario Ruiz, Ignacio Marzán, Fernando Tornos, Alireza Malehmir, Alba Gil, Stefan Buske, Dirk Orlowsky, Imma Palomeras, Juan Manuel Pons, Juan Carlos Videira, Irene De Felipe, and Ramon Carbonell

In order to tackle the ever-increasing demand of raw materials, the European Institute of Technology (EIT) promotes research and innovation solutions for safe and sustainable mineral exploration through its Raw Materials Programme. The SIT4ME project (“Seismic Imaging Techniques for Mineral Exploration”) has been funded as part of this program to develop efficient techniques in seismic acquisition and imaging methods for mineral exploration in crystalline environments. Within SIT4ME, a multidisciplinary data acquisition experiment (i.e. 3D-3C active and passive source seismic datasets) took place in November 2009 in Sotiel-Coronada (Iberian Pyrite Belt, SW Spain). The aim of this experiment was to image a 300-500 m depth pyrite-rich massive sulfide orebody interbedded with felsic volcanic rocks and shales. The seismic dataset involves the recording of 875 vibration points in 653 seismic receivers, distributed in a 3D mesh around the target and six 2D crooked lines. Conventional processing workflow (such as static corrections, surface-consistent deconvolution, amplitude equalization, frequency filtering, and velocity analysis) was combined with more advance methods (e.g. ground roll attenuation or post-stack coherency filtering) to obtain robust images of the subsurface of the target area. The processing workflow has been applied to four 2D seismic sections, one in the North-South and three in the East-West directions, distributed across the study area. The preliminary imaging results show coherent reflective packages down to two seconds two-way traveltime (TWT). The North-South line contains a north-dipping ~400 m long highly reflective zone in the center at 130 ms TWT. The east-west profiles show a slightly folded structure (antiform and synform) which is evident down to 0.25 s TWT. Towards the north, the seismic lines become parallel to subsurface structures and therefore the track of these structures is lost. Current work involves the incorporation of well-log data to improve the quality and resolution of the interpretations. The next processing steps will involve pre-stack depth migration, P-wave travel-time tomography and a combined analysis of controlled source imaging and ambient noise interferometry data.

The SIT4ME project has been funded by EIT Raw Materials (17024).

How to cite: Martínez, Y., Alcalde, J., Martí, D., Ayarza, P., Ruiz, M., Marzán, I., Tornos, F., Malehmir, A., Gil, A., Buske, S., Orlowsky, D., Palomeras, I., Pons, J. M., Videira, J. C., De Felipe, I., and Carbonell, R.: SIT4ME: seismic imaging of mineral-hosting structures in Sotiel-Coronada (Spain), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22146, https://doi.org/10.5194/egusphere-egu2020-22146, 2020.

D767 |
EGU2020-10911
Alba Gil, Alireza Malehmir, Stefan Buske, Juan Alcalde, Puy Ayarza, Yesenia Martínez, Louise Lindskog, Bill Spicer, Ramon Carbonell, Dirk Orlowsky, Matthew Penney, and Anja Hagerud

Mineral resources are used in large quantities than ever before because they are fundamental to our modern society. To this front and facing an up-scaling challenge, the EIT Raw-Materials funded project SIT4ME (Seismic Imaging Techniques for Mineral Exploration) was launched involving several European institutions. As part of the project, a dense multi-method seismic dataset was acquired in the Zinkgruvan mining area at the Bergslagen mineral district of Sweden, which hosts one of the largest volcanic-hosted massive sulphide (VMS) deposits in the country.

In November 2018, a dense multi-method seismic dataset was acquired in the Zinkgruvan mining area, in a joint collaborative approach among Swedish, Spanish and German partners. A combination of sparse 3D grid and dense 2D profiles in an area of approximately 6 km2 was acquired using a 32t seismic vibrator (10-150 Hz) of TU Bergakademie Freiberg, enabling reasonable pseudo-3D sub-surface illumination. For the data acquisition, a total of approximately 1300 receiver positions (10-20 m apart), using different recorders, and 950 source positions were surveyed. All receivers were active during the data acquisition allowing a combination of 2D and semi-3D data to be obtained for various imaging and comparative studies. The main objective of the study, apart from its commercial-realization approach, was also to provide information useful for deep-targeting and structural imaging in this complex geological setting. The main massive-sulphide bearing horizon, Zinkgruvan formation, is strongly reflective as correlated with the existing boreholes in the mine. Careful analysis of the seismic sections suggests a dominant northeast-dipping structure, consistent with the general plunge of the main Zinkgruvan fold that has been suggested in the area.

Acknowledgements: EIT-RawMaterials is gratefully thanked for funding this up-scaling project 17024.

How to cite: Gil, A., Malehmir, A., Buske, S., Alcalde, J., Ayarza, P., Martínez, Y., Lindskog, L., Spicer, B., Carbonell, R., Orlowsky, D., Penney, M., and Hagerud, A.: SIT4ME project: Up-scaling seismic methods for mineral exploration in the Zinkgruvan mining area, Sweden, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10911, https://doi.org/10.5194/egusphere-egu2020-10911, 2020.

D768 |
EGU2020-11129
Alireza Malehmir, Lars Dynesius, Paul Marsden, Stefan Buske, Nelson Pacheco, Magdalena Markovic-Juhlin, Bojan Brodic, George Donoso, Tatiana Pertuz, Richard de Kunder, Lukasz Sito, and Christopher Juhlin

Mineral exploration industry needs to push its technological advancement towards finding the so-called critical raw materials. These materials are fundamental for our green technologies and help accelerate the energy transition towards decarbonisation. While in-mine and near-mine exploration will be more convenient in the short term, providing fresh raw materials and mines in greenfield or brownfield areas must not be forgotten in the longer term. As the chase for mineral deposits becomes deeper, seismic methods play a greater role for exploring at depth. Through a series of experiments conducted within the EU-funded Smart Exploration project, we have innovated a number of hardware and methodological solutions for in-mine as well as brownfield seismic exploration. Along with these, legacy data have also been recovered, reprocessed and their values for mineral exploration illustrated. The legacy data examples are from the Ludvika Mines (Nordic Iron Ore AB) of central Sweden and Neves-Corvo (Somincor-Lundin Mining) of southern Portugal.

In particular, through the development of a GPS-time system, we have managed to acquire a globally unique semi3D in-mine and surface seismic dataset at the world-class Neves-Corvo mine. This helped to utilize four exploration tunnels at 600 m depth and two receiver lines on the surface allowing over 1000 recorders to be synchronized for down-tunnel exploration. A broadband electromagnetic-based seismic source (7 kN or 1.5t), developed also in the project, was used as the seismic source.

In central Sweden, at an iron-oxide mining site of Nordic Iron Ore company, 2D seismic profiles helped to suggest potential resources in the down-dip continuation of the known deposits but also in their footwall. A follow-up and more recent survey employed over 1250 seismic recorders and a 32t vibrator to acquire a sparse 2 by 2 km seismic dataset. The data show great quality and allow to image lateral extent of the deposits and crosscutting reflections that may be important factors for mine planning and understanding structural evolution of the deposits. The broadband seismic source was also tested at the site along the existing 2D profiles with raw data already showing a number of reflections interpreted to be from the mineralization. This survey further illustrates that the seismic source functions well and has a great potential for hard rock seismic applications. 

Acknowledgements: This work was supported by the Smart ExplorationTM project. Smart Exploration has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 775971.

How to cite: Malehmir, A., Dynesius, L., Marsden, P., Buske, S., Pacheco, N., Markovic-Juhlin, M., Brodic, B., Donoso, G., Pertuz, T., de Kunder, R., Sito, L., and Juhlin, C.: Innovating surface and in-mine seismic exploration solutions , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11129, https://doi.org/10.5194/egusphere-egu2020-11129, 2020.

D769 |
EGU2020-3598
Emma Soldevila, Ramon Carbonell, David Amblas, and Miquel Canals

High-resolution (HR) 3D seismic acquisition is expensive and often not available due to a variety of reasons. This work builds an optimized workflow to convert a dense 2D HR seismic grid into a 3D seismic volume. The task has been developed within a broader project, NUREIEVA, which aims at characterizing a metal-rich onshore and shallow marine mine tailings deposit in Portmán Bay, Murcia, Spain, which developed from 1957 to 1990. Hence, in the framework of the NUREIEVA project a very dense set of 2D HR seismic lines was acquired. The geophysical equipment used to capture the submarine extent, thickness and internal structure of the mine tailings deposit was a hull-mounted Kongsberg TOPAS PS18 single-channel parametric source. The seismic grid thus acquired consisted of 1309 2D lines, with an approximate distance between lines of 10 m, covering an area of 7.45 km2. The parametric source yielded a vertical resolution of 15 cm, which is very high if compared with conventional seismic reflection data.

 

In order to visualize the internal architecture of the mine tailings deposit in all directions, it is desirable to convert the dense 2D network of lines into a full 3D data volume. Such a data volume is intended to assist reaching faster deposit delimitation and more accurate volumetric calculations. For this purpose, a new optimized 2D to 3D conversion processing flow including a 3D interpolation scheme has been designed. Given the specific characteristics of the input data, a number of challenges had to be addressed, namely: (i) a very high vertical resolution that differs by at least two orders of magnitude from the horizontal resolution; (ii) a large data volume (2 TB), which involves extensive computing time; (iii) the heterogeneity in the acquisition parameters. Because of this, the lines had to be processed previously to the 3D interpolation to homogenize the imaging characteristics and signal content. This new methodology can be now applied for obtaining a 3D volume to any case where a single channel dense 2D seismic grid is available. Furthermore, the new methodology, duly adapted to each particular scenario, represents a low cost alternative to conventional HR 3D seismic and could prevent further seismic shooting in areas when 2D data is already available.

How to cite: Soldevila, E., Carbonell, R., Amblas, D., and Canals, M.: 2D to 3D high-resolution seismic data conversion: imaging a shallow water metal bearing mine tailings deposit in Portmán Bay, Spain, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3598, https://doi.org/10.5194/egusphere-egu2020-3598, 2020.

D770 |
EGU2020-20765
Robert Jackisch, Robert Zimmermann, Björn H. Heincke, Arto Karinen, Heikki Salmirinne, Markku Pirttijärvi, Sandra Lorenz, Yuleika Madriz, and Richard Gloaguen

Geologic mapping in arctic regions faces demanding challenges, from accessibility to weather, light and infrastructure conditions. Field expeditions need to cover substantial area, and mostly are supported by satellite and airborne data. While named methods offer large-scaled insights, they often lack the required resolution for precise ground investigations. The rise of unmanned aerial systems (UAS) as new state-of-the-art platform in geoscience provides the means needed to close that scale gap.

Fieldwork within the frame of the EIT project MULSEDRO focused on the Paleocene flood basalt province of Disko Island (West Greenland). On the example of the Qullissat area, we demonstrate how UAS can bring new insights into strategies for magmatic Ni-PGE exploration in the area. Mineralization is associated to basalt sills of the Asuk Member, emplaced locally in coal-bearing cretaceous sandstones.  We conducted photogrammetric outcrop modelling, interpretation of orthoimagery, multi- and hyperspectral based lithological classification and analysis of magnetic data. While magnetics give the location, orientation and subsurface extension of the basaltic sills, spectral imaging, in particular with focus on the iron absorption feature, reveals mineral proxies due to sulphide weathering. A total of 216 line-km for magnetics and 18.5 km2 of multi- and hyperspectral data was covered.

First results show that integration of drone-borne spectroscopic and magnetic data highlights potential local mineralization. Based on our results, possible indications for mineralization are linear features in the first vertical derivative of the magnetic data and specific iron absorptions in the spectral data. Resulting maps are validated using handheld spectroscopy, ground magnetics, susceptibility measurements, combined with geochemistry and mineralogy of rock samples examined in the laboratory. Conclusively, the study solidifies UAS as highly valuable tool for exploration.

How to cite: Jackisch, R., Zimmermann, R., Heincke, B. H., Karinen, A., Salmirinne, H., Pirttijärvi, M., Lorenz, S., Madriz, Y., and Gloaguen, R.: UAS-based hyperspectral and magnetic mineral exploration targeting Ni-PGE mineralization on Northern Disko Island, West Greenland., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20765, https://doi.org/10.5194/egusphere-egu2020-20765, 2020.

D771 |
EGU2020-18576
Cornelia Tauchner, Bernd Trabi, and Florian Bleibinhaus

A seismic site characterization of the iron ore mine at Mt. Erzberg was performed in November 2016. The covered area measured about 4 km² within the active mine and the surrounding village. Within 4 weeks 125 3-component-geophones recorded 31 seismic events including production blasts. This data allowed for the computation of P and S velocity models. Which in turn were the basis for seismic wave field modelling with an elastic FD code. These simulations were used to calculate optimized blasting patterns for minimal vibrations at sensitive targets, like settlements and infrastructure, which were tested in a second and third experiment in June and October 19. (see contribution by Trabi et al.) 

In this study a statistical analysis of the resulting PPV-vector at any given geophone position was done, utilizing recorded blasts from 3 experiments. Using a scaled distance method, one can establish relationships between blast intensity, distance and ground vibrations. When compared to the PPV prognosis from the simulations, this analysis allows for assessments on prediction accuracy. General trends in PGV estimation can also be used to create site amplification factors to further enhance optimized blasting pattern calculations. 

This study is part of a large interdisciplinary EU funded project called SLIM, which focuses on sustainability in mining. 

How to cite: Tauchner, C., Trabi, B., and Bleibinhaus, F.: PGV-prediction for production blasts at the iron ore mine Mt. Erzberg, Austria, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18576, https://doi.org/10.5194/egusphere-egu2020-18576, 2020.

D772 |
EGU2020-10719
Louis Andreani, Erik Herrmann, Sandra Lorenz, Robert Zimmermann, Moritz Kirsch, Naomi Brazzo, and Richard Gloaguen

Satellite-based remote sensing offers a time-saving and cost-effective way of exploring mineral resources in support of mineral exploration and monitoring of mining activities. On one hand, the newest generation of non-commercial optical satellite sensors, such as Sentinel-2, provides data with improved spectral, spatial and temporal resolution. One of the main advantages of Sentinel-2 with respect to other sensors is that it has several bands that cover the 900 nm iron absorption feature. On the other hand, this unique feature still remains underrated as suggested by the lack of applications in the mining sector. We explored the potential of Sentinel-2 for regional-scale mapping of iron-bearing alteration minerals using several approaches commonly used in Earth Observation. We focused on the Iberian pyrite belt, which hosts several of the largest massive sulfide deposits on Earth and has been extensively mined for copper, manganese, iron and gold since the Bronze Age.

First, we attempted to characterize the part of the spectrum between 704 and 945 nm (bands 5 to 9), which is associated to the iron absorption feature, using normalized indices and curve-fitting techniques. These approaches do not require inputs and allow to easily and quickly produce a map of alterations zones revealing mineral prospects and mining sites, but at the cost of a lack of differentiation between the different mineral assemblages. The second approach used was to map specific mineral assemblages using the Spectral Angle Mapper algorithm, which determines the spectral similarity between a known reference spectrum and another unknown spectrum. Relevant mineral assemblages were defined using the mineral composition and resampled spectral signatures from field samples. The focus was mainly set on assemblages containing sericite, chlorite and goethite, which are closely associated to volcanic hosted massive sulfides. Despite known difficulties, related to the low spectral resolution and pixel mixing, several assemblages such as those containing chlorite and sericite could be successfully mapped and their overall distribution appeared consistent with field sampling and hyperspectral imaging from existing studies. Finally, we attempted to map specific mineral assemblages using classification methods based on state of the art machine learning algorithms such as Support Vector Machine, Multi-Layer Perceptron and Random Forrest. Training pixels for mineral assemblages were carefully selected based on field observations and existing hyperspectral data. Each classification method was assessed using a stratified K-fold cross-validation and all four classifications perform well if we consider the average accuracies for alterations, which range from 93.9 to 96.2%.

Sentinel-2 proves to be a powerful tool for mapping iron-bearing minerals. The different approaches we tested (from the simple ones requiring no inputs to the more complex ones requiring field data and knowledge) allow to efficiently map iron-bearing alteration minerals with an increasing degree of details and can find applications not only in mineral exploration but also in monitoring of mining activities.

How to cite: Andreani, L., Herrmann, E., Lorenz, S., Zimmermann, R., Kirsch, M., Brazzo, N., and Gloaguen, R.: Sentinel-2 as a tool for mapping iron-bearing alteration minerals: a case study from the Iberian Pyrite Belt (Southern Spain), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10719, https://doi.org/10.5194/egusphere-egu2020-10719, 2020.

D773 |
EGU2020-6682
Cericia Martinez, Ulrich Kelka, Ignacio Gonzalez-Alvarez, and Carmen Krapf

The Gawler Craton hosts significant economic mineralization within South Australia. Due to limited outcrops, deeply weathered profiles, and the absence of a clear variety of landscape surface features, mineral exploration is particularly challenging in this part of Australia. Here we present a workflow of data processing and interpretation to understand the neotectonics and landscape characterization of this region. We explore the potential to delineate surface lineaments and features from newly acquired high-resolution datasets. We aim to automatically identify landform domains based on the analysed data and investigate whether deep seated tectonic lineaments manifest in recognizable surface expressions.

The data we analyse in this study comprises digital elevation, radiometric, magnetic, and gravity data. We assume that elevation and radiometric data relate to surficial landscape features, whereas gravity and magnetic data represent subsurface basement features. Linking the analysis of both surface and subsurface datasets can potentially yield information on the neotectonic activity, and the association between landforms and basement structures as potential zones of fluid migration. We will show how processed digital elevation data can be used for automatic classification of different landform domains.

In order to assess mineral potential zones in the area, we compare the generated lineament data in terms of their geometric and topological properties to examine whether there is consistency in the subsurface and surface layers. We postulate that through a line density map, we may be able to quantify a potential relationship between lineaments that are representative in both the surface and subsurface, indicating potential faults or large-scale lineament trends that may link mineral systems in the basement with the landscape surface features. Areas that exhibit large numbers of surface and subsurface lineaments might be areas of enhanced mineral potential. This study contributes to enhance the efficiency of mineral exploration protocols in areas under cover.

How to cite: Martinez, C., Kelka, U., Gonzalez-Alvarez, I., and Krapf, C.: Neotectonics and landscape characterization in the Gawler Craton, South Australia - Insights through high-resolution remote sensing, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6682, https://doi.org/10.5194/egusphere-egu2020-6682, 2020.

D774 |
EGU2020-13102
Christian Burlet, Giorgia Stasi, and Yves Vanbrabant

The Horizon 2020 ROBOMINERS project (Grant No. 820971), is developing concepts and prototypes for a bio-inspired, modular and reconfigurable robot-miner for small and difficult to access deposits. This covers both underexplored or currently flooded mines not accessible anymore for conventional mining techniques; or places that have formerly been explored, but whose exploitation was considered non-economic due to the small size of the mineralization or its accessibility.

As part of the sensors payload of the miner, a modular segment of the robot will contain sophisticated geochemical/mineralogical sensors capable of characterising the slurry produced by the drilling process in real-time and interpreting the data as mining diagnostics and navigation parameters for the progression of the miner. This segment will perform in-stream analyses of the drilling slurry using sampling inlet-outlet ports. The sensing techniques currently considered for this segment are LIBS (Laser-induced breakdown spectroscopy), EDXRF (Energy dispersive X-Ray fluorescence), LINF (Laser-induced native fluorescence), Terahertz imagery and time-resolved Raman.

This study presents the first laboratory-scale prototype of this segment, and tests on slurry analogues (bentonite/baryte/salt mixtures of sphalerite ore) with a high-repetition LIBS analyser (1064nm 20 KHz laser, 200-850nm spectrometer, co-axial light collection). As a proof of concept for high-pressure operation, the plasma sparks are created inside the opaque liquid medium using a synchronized argon gas dispenser in front of the laser window. This innovative setup was successfully tested in this study under a pressure range of 1 to 10 bar and a superficial gas velocity range of 50 to 100 mm/s. The next steps in the study is to increase the slurry pressure to simulate deep borehole operation and couple LIBS with a complementary analyser like EDXRF.

How to cite: Burlet, C., Stasi, G., and Vanbrabant, Y.: The ROBOMINERS “advanced mineralogical segment”: an in-stream, in slurry analytical module designed for robotic ore exploration and production, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13102, https://doi.org/10.5194/egusphere-egu2020-13102, 2020.

D775 |
EGU2020-13121
Giorgia Stasi, Christian Burlet, Frederic Nguyen, and Yves Vanbrabant

The Horizon 2020 ROBOMINERS project (Grant No. 820971) is developing a modular robot miner prototype following a bio-inspired design, capable of operating, navigating and performing selective mining in a flooded underground environment.

The project has been set up with the long-term strategic objective to facilitate EU access to mineral raw materials – including those that are considered as strategic or critical for the energy transition - from domestic resources and decreasing thus the European import dependency. The use of the robot miner will especially be relevant for mineral deposits that are small or difficult to access.

Conventional DC resistivity and IP methods for geophysical exploration are well reported in the literature, however, in the framework of ROBOMINERS we wants to develop a new approach for DC resistivity and IP that use the deposit itself as a probe for the diffusion of the signal.

Ideally the electrode will be positioned at the end of the robot legs (in contact with the terrain) and the source on the drilling head. This set up will allow to move the source and electrode in preferential position in order to cover the biggest surface possible, and to maximize resistivity measurements avoiding the lack of resolution due to the positioning of electrodes on grounds surface or distant borehole.

In addition to resistivity measurement we are considering an additional technique, namely the Terahertz spectroscopy. The concept for the THz scanning spectroscopy is to use the body of the robot to arrange at 360° the THz detectors and install on the robot’s front the THz source (positioned on a mobile arm or on the drilling head). This technique will allow to scan the mine’s wall and produce a first model of the deposit section. This model will then help for the positioning of the DC/IP source. THz spectroscopy can be applied for the screening of the wall in case it is covered in drilling mud, where regular multispectral camera might not work. As this technique is highly affected by the presence of water is not yet defined its precise field of applicability that will need to be outlined within the project framework.

For our scope we are going to consider (narrow-) vein type and stratiform deposits; those kinds of deposits that could have formerly been explored but their exploitation was considered as uneconomic due to the small size of the deposits or their difficulty of access. More specifically we are going to investigate and review the geophysical properties of tin-lead-zinc wolframite vein type deposit for DC resistivity and IP technique and Terahertz spectroscopy.

2.11.0.0

How to cite: Stasi, G., Burlet, C., Nguyen, F., and Vanbrabant, Y.: Exploring geophysical properties of Sn-Cu-Pb-Zn deposits at depth using ROBOMINERS’ mid-perception capability. , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13121, https://doi.org/10.5194/egusphere-egu2020-13121, 2020.

D776 |
EGU2020-13526
Cecilia Contreras, Mahdi Khodadadzadeh, Laura Tusa, and Richard Gloaguen

Drilling is a key task in exploration campaigns to characterize mineral deposits at depth. Drillcores
are first logged in the field by a geologist and with regards to, e.g., mineral assemblages,
alteration patterns, and structural features. The core-logging information is then used to
locate and target the important ore accumulations and select representative samples that are
further analyzed by laboratory measurements (e.g., Scanning Electron Microscopy (SEM), Xray
diffraction (XRD), X-ray Fluorescence (XRF)). However, core-logging is a laborious task and
subject to the expertise of the geologist.
Hyperspectral imaging is a non-invasive and non-destructive technique that is increasingly
being used to support the geologist in the analysis of drill-core samples. Nonetheless, the
benefit and impact of using hyperspectral data depend on the applied methods. With this in
mind, machine learning techniques, which have been applied in different research fields,
provide useful tools for an advance and more automatic analysis of the data. Lately, machine
learning frameworks are also being implemented for mapping minerals in drill-core
hyperspectral data.
In this context, this work follows an approach to map minerals on drill-core hyperspectral data
using supervised machine learning techniques, in which SEM data, integrated with the mineral
liberation analysis (MLA) software, are used in training a classifier. More specifically, the highresolution
mineralogical data obtained by SEM-MLA analysis is resampled and co-registered
to the hyperspectral data to generate a training set. Due to the large difference in spatial
resolution between the SEM-MLA and hyperspectral images, a pre-labeling strategy is
required to link these two images at the hyperspectral data spatial resolution. In this study,
we use the SEM-MLA image to compute the abundances of minerals for each hyperspectral
pixel in the corresponding SEM-MLA region. We then use the abundances as features in a
clustering procedure to generate the training labels. In the final step, the generated training
set is fed into a supervised classification technique for the mineral mapping over a large area
of a drill-core. The experiments are carried out on a visible to near-infrared (VNIR) and shortwave
infrared (SWIR) hyperspectral data set and based on preliminary tests the mineral
mapping task improves significantly.

How to cite: Contreras, C., Khodadadzadeh, M., Tusa, L., and Gloaguen, R.: A supervised technique for drill-core mineral mapping using Hyperspectral data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13526, https://doi.org/10.5194/egusphere-egu2020-13526, 2020.

D777 |
EGU2020-13563
Sam Thiele, Sandra Lorenz, Moritz Kirsch, and Richard Gloaguen

Hyperspectral imaging is a powerful tool for mapping mineralogy and lithology in core and outcrops, as many minerals show distinct spectral features in the commonly analysed visible, near, short-wave and long-wave infrared regions of the electromagnetic spectrum. High resolution ground and UAS (unmanned aerial system)-based sensors thus have significant potential as a tool for rapid and non-invasive geological mapping in mining operations, exploration campaigns and scientific research. However, the geometrical complexity of many outcrops (e.g. cliffs, open-pit mines) can result in significant technical challenges when acquiring and processing hyperspectral data. In this contribution we present updates to the previously published MEPHySTo python toolbox for correcting, georeferencing, projecting and analysing geometrically complex hyperspectral scenes. We showcase these methods using datasets covering volcanogenic massive sulphide (VMS) mineralisation exposed within open pit mines in Rio Tinto (Spain), and interpret possible structural and lithological controls on mineralization. Potential applications of hyperspectral mapping for grade control, outcrop mapping and the characterisation of different mineral deposit styles are also discussed.

How to cite: Thiele, S., Lorenz, S., Kirsch, M., and Gloaguen, R.: Hylite: a hyperspectral toolbox for open pit mapping, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13563, https://doi.org/10.5194/egusphere-egu2020-13563, 2020.

D778 |
EGU2020-20242
Helen Twigg and Murray Hitzman

The Neoproterozoic Central African Copperbelt located in southern Democratic Republic of Congo (DRC) and the northwestern Zambia and contains 48% of the world’s cobalt reserves and significant resources of copper, zinc, nickel and gold. A good understanding of the geology is critical for successful mineral exploration. However, geological mapping is hindered by low topographic relief, limited outcrop, and a generally deep (10-100m) weathering profile developed since the Late Miocene.  Multielement soil geochemistry provides a means for conducting geological mapping.   Areas with outcrop or containing drill holes and/or trenches were utilized to relate known geological lithologies with soil geochemical results using major element and trace element ratios.

The lithostratigraphy within a study area along the DRC-Zambia border can be geochemically sub-divided into three units. Mixed carbonate and siliciclastic lithologies of the lower portion of the local stratigraphy are typically characterised by elevated V, Ti, and Nb. Mudstones and siltstones are dominated by elevated Al, Fe and Ba. The upper portion of the local stratigraphy is geochemically neutral with regards to trace elements.  Lithological discrimination through analysis of soil geochemical data is limited in some areas by intense weathering. A A-CNK-FM diagram exhibits how complete weathering of carbonate rocks and carbonate-rich breccias (after evaporites) results in the somewhat counter intuitive outcome that residual soils above carbonate rocks are amongst the most aluminum rich in the study area with >80% Al2O3 (mol%) or >80% combined Al2O3 (mol%) and FeO + MgO (mol%). The weathering of siliciclastic rocks (siltstones, mudstones, and diamictites) result in a shorter weathering path across a A-CNK-FM diagram, probably due to their higher original proportion of resistate phases.

An area specific geochemical database of baseline lithostratigraphy weathering paths allows the identification of atypical geochemistry which could indicate facies change, alteration or mineralization.

How to cite: Twigg, H. and Hitzman, M.: Lithostratigraphic Mapping Through Saprolitic Regolith Using Soil Geochemistry and High-Resolution Aeromagnetic Surveys. , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20242, https://doi.org/10.5194/egusphere-egu2020-20242, 2020.