Abandoned mining wastes are both an environmental challenge and a possible secondary raw material source. The characterization and monitoring of these sites are often expensive and cumbersome because ...of the need of repeated field surveys. Remote sensing data are a cost-effective alternative that helps in producing multiscale maps of mining wastes. These maps can be used to investigate and monitor the spatial patterns of different elements within the mining wastes. In this work, Sentinel-2 images are combined with the geochemical samples in order to map the distribution of iron, copper, chromium, and cobalt. The target area was the Vigonzano mining wastes in Northern Apennines (Italy) where there are a small number of geochemical analyses but a large amount of satellite image data. We used the multivariate geostatistical estimation method (Co-Kriging) that exploit the meaningful spatial correlation between the elements of interest and band ratios (obtained from Sentinel-2 images). The concentration maps highlighted subareas for Cu and Cr with an estimated grade of about 0.3% and 0.2%, respectively. In addition, the critical element Co showed an enrichment in the south-east part of the mining wastes, in a similar pattern as Cr. Instead, the obtained maps show Ce, La, Rb, and Nb depletion compared to the surrounding agricultural areas. The concentration maps were intended as a prefeasibility study to determine enriched areas for further detailed investigation.
There is a growing interest in the characterization of mining residues, both for environmental assessments and critical raw materials recovery. The lack of sufficient in situ samples hampers an ...effective geostatistical modelling of material concentrations variability. This paper proposes a method to characterize the aluminum spatial variability in a mine residue from remote sensing data and imprecise information from daily dumping procedures. The method is proposed for the mapping of aluminum within a Greek bauxite residue, using Sentinel-2 imagery. The spatial correlation between metal concentrations and remote sensing indicators (e.g., spectral band ratios) is the premise for mapping aluminum varieties. The proposed method is based on Conditional Gaussian Co-Simulation, where Sentinel-2 images can be used as auxiliary variables. Simulation results are compared with the Co-kriging estimation method. To perform the Co-kriging estimation, the same conditions as simulation are used (same inputs, models, and neighborhoods). Simulation results quantified the metals variability in mining residues, presenting the metal concentration of piled materials in two time periods. For results validation and selecting the best map, fourteen validation samples were used. For the best representative maps of aluminum concentration, a correlation coefficient of about 0.7 between the validation data and obtained aluminum concentration map was obtained.
Remote sensing can be fruitfully used in the characterization of metals within stockpiles and tailings, produced from mining activities. Satellite information, in the form of band ratio, can act as ...an auxiliary variable, with a certain correlation with the ground primary data. In the presence of this auxiliary variable, modeled with nested structures, the spatial components without correlation can be filtered out, so that the useful correlation with ground data grows. This paper investigates the possibility to substitute in a co-kriging system, the whole band ratio information, with only the correlated components. The method has been applied over a bauxite residues case study and presents three estimation alternatives: ordinary kriging, co-kriging, component co-kriging. Results have shown how using the most correlated component reduces the estimation variance and improves the estimation results. In general terms, when a good correlation with ground samples exists, co-kriging of the satellite band-ratio Component improves the reconstruction of mineral grade distribution, thus affecting the selectivity. On the other hand, the use of the components approach exalts the distance variability.
This paper presents a chance-constrained integer programming approach based on the linear method to solve the longterm open pit mine production scheduling problem. Specifically, a single stockpile ...has been addressed for storing excess low-grade material based on the availability of processing capacity and for possible future processing. The proposed scheduling model maximizes the project NPV while respecting a series of physical and economic constraints. Differently from common practice, where deterministic models are used to calculate the average grade for material in the stockpiles, in this work a stochastic approach was performed, starting from the time of planning before the stockpile realization. By performing a probability analysis on two case studies (on iron and gold deposits), it was proven that the stockpile attributes can be treated as normally distributed random variables. Afterwards, the stochastic programming model was formulated in an open pit gold mine in order to determine the optimum amount of ore dispatched from different bench levels in the open pit and at the same time a low-grade stockpile to the mill. The chance-constrained programming was finally applied to obtain the equivalent deterministic solution of the primary model. The obtained results have shown a better feed grade for the processing plant with a higher NPV and probability of grade blending constraint satisfaction, with respect to using the traditional stockpile deterministic model.
Rock mass fractures adversely affect the cutting of commercial-size blocks and cause rock material loss in ornamental stone quarries. In order to obtain a reliable evaluation and an optimized ...production of ornamental stone deposits, it is fundamental to detect fractures in a non-destructive manner identifying them through 3D deterministic modeling. In this study, a recently published fracture modeling strategy, based on Ground Penetrating Radar (GPR) survey was implemented on a large area of bench (27.0 m × 65.0 m) in a limestone quarry in Italy. The survey was done using a dual-frequency GPR system (250 MHz and 700 MHz). The objective of this work was to investigate the large-scale applicability of the mentioned fracture model for future consideration in quarrying optimization studies. Only the 700 MHz radargrams were considered for the fracture modeling, as they provided a higher resolution than the 250 MHz radargrams and a penetration depth of about 4.0 m. The bulk dielectric constant of the rock mass of the bench was estimated by averaging the velocities obtained from fitting the hyperbolic diffractions of fractures at different depths. The model showed that fractures from the same family set can have noticeable spatial variations. The results allowed us to roughly estimate the sizes of the blocks exploitable from the different rock layers of the quarry bench.
Rock mass is typically characterized by inherent fractures that cause natural blocks of rocks. Unplanned cutting of stone deposits in quarries may lead to over-producing waste (rock debris) or ...extracting unfit (fractured) stone blocks. This paper presents two case studies through the use of low and high frequency Ground Penetrating Radar (GPR) antennas to detect fractures in two benches of a quarry. In the first case study, a high frequency GPR antenna was used aiming to: (i) compare the GPR results with a map of the out-cropping fracture intensity in the bench surface, developed using the data of the GPR survey marks and interpolated by the Ordinary Kriging technique, and (ii) present how sub-vertical fractures can be numerically modelled in three dimensions from the GPR results. The second case study was focused on using a low frequency antenna to detect large aperture size of fracture surfaces as deep as possible in order to evaluate a deposit stratum before quarrying. This could be done through studying the reflections from a 3D cross-sectional GPR model and a 3D transparent GPR model. In the discussion section, an exploitation planning approach, based on modelling fractures as 3D surfaces, is theoretically and graphically proposed to optimize the stone production recovery. The two case studies showed that GPR is a successful tool for the assessment of ornamental stone deposits and a promising tool for recovery optimization.
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•GPR allowed to detect discontinuities of tiny-size aperture in a limestone block.•Discontinuities and defects were deterministically modeled and visualized in 3D.•It’s the first kind ...of this application in the commercial size scale of stone blocks.•The authors will use the resulting model for the cutting optimization of slabs.
Discontinuities can be hidden or out-cropping with variable aperture sizes in rock media. Obtaining deterministic geo-spatial features of discontinuities inside quarried ornamental stone blocks is a decision-making tool for the post processing phase of cutting slabs. In a case study of a limestone block, discontinuities were detected by the Ground Penetrating Radar (GPR) through a high frequency antenna (700 MHz) and deterministically modeled in three dimensions following the method presented in Elkarmoty et al. (2017). The use of the 700 MHz GPR antenna in this kind of rock allowed to detect tiny-size apertures of discontinuities. The results showed that it is possible to detect and model not only the outcropping discontinuities, but also the hidden ones. Hidden three-dimensional voids or defects were detected and modeled as well. The resulting model was visualized in different orientations, using a 3D data visualization software package, for a better perception of the results.
Bauxite residuals from abandoned mining sites are both an environmental challenge and a possible source of secondary raw materials. Processing of multispectral and hyperspectral images with the best ...available techniques can help to produce multiscale spatial maps of elements inside and around the mining sites. The authors propose a procedure for mapping elements concentration using multiple data sets at different scales and resolutions. A comparison between multispectral Sentinel-2 images and hyperspectral PRISMA processing is performed over some case studies of bauxite residues in the Mediterranean area. Specifically, a case study from Italy is composed regarding artificial canyons created by past artisanal mining activities and by stockpiles of extracted bauxite. Hyperspectral punctual measurements (spectroradiometer surveys) were taken in various zones of the bauxite site, where infield topsoil samples were also taken for X-ray fluorescence chemical analysis. Final concentration maps were estimated by performing geostatistical techniques.
Earth Observation (EO) data can become an essential tool in the transformation of a raw materials sector that aims to reconfigure its model of operation. The high demand for the mineral resources ...necessary for the transition to a carbon neutral and circular economy conflicts with the increasing difficulties of finding new deposits. As the sector heads towards embracing circularity and reducing the environmental impacts, a clear focus has been set on developing appropriate tools to boost the efficiency of mineral resource management, both technologically and economically. In this scenario, the Sentinel satellites of the European Copernicus program come into play. Despite being satellites considered medium resolution, they provide great temporal and spatial coverage in a continuous record, which makes them tools with great potential for the raw materials sector. However, the lack of applications in the raw materials sector suggests that these technological advances have remained underrated by sectoral actors. The RawMatCop program was designed to bridge this gap. This program, co-funded by the European Commission and EIT RawMaterials, aims to develop applications and promote the use of Copernicus data in the raw materials sector to contribute to a safe and sustainable supply of mineral resources. The presented applications can be grouped into three categories covering the whole mining cycle from exploration to exploitation and post-mining. Two of the presented case studies cover the study of primary sources including exploration of Iron Oxide Copper Gold mineralisations to identify high-potential mining areas and mapping of informal gold mining and its environmental impacts. Another project focused on secondary sources tackled data applications for grade mapping and sample optimisation in mining residues. And the forth project focused on monitoring ground stability related to mining activity. The results demonstrate the high cost-effectiveness of Sentinel 1 and 2 in extending ground-based measurements to larger areas, especially when these are hard-to-reach areas. Finally, the presented projects examine the industrial and social impacts of technological innovations, as well as contribute to the achievement of prominent European Union policy objectives and the United Nations Sustainable Development Goals.
•Use of Copernicus for sustainable mineral applications has been tested.•Characterization of tailings and evaluation of hazards are possible by Copernicus.•RawMatCop Projects have proved to support UN Sustainable Development Goals.•Impacts of Projects' results on EU regulations and strategies are highlighted.•Social, industrial and economical challenges are described for each Project.
Rad prikazuje uporabu vjerojatnosnoga cjelobrojnog programiranja, temeljenoga na linearnome algoritmu, za dugoročno rješavanje proizvodnje u rudniku otvorenoga kopa. Obrađeno je jedno odlagalište ...jalovine sa „siromašnom” koncentracijom rude u cilju aktiviranja toga materijala u budućoj preradbi korisne sirovine. Takav projekt maksimizira trenutačnu vrijednost rudarenja uzimajući u obzir niz fizičkih i ekonomskih varijabli. Posebnost u odnosu na determinističke modele koji se danas uglavnom koriste za izračun granične prosječne vrijednosti koncentracije rude prije odlaganja kao jalovine izražena je stohastikom. Ona je uključila vjerojatnosnu analizu dvaju slučajeva, tj. za ležište željeza i zlata. U obama je dokazano kako se varijable određene na odlagalištu mogu opisati normalnom razdiobom. Stohastički model programiran je za rudnik zlata te je uzeta u obzir optimalna vrijednost rude razvrstane na različitim rudničkim razinama, a prije slanja na obradbu (mljevenje). Optimizirani model zatim je primijenjen za dobivanje usporednoga determinističkog modela. Rezultati su upozorili na to da je konačno rješenje pokazalo znatno bolji odabir granične koncentracije rude koja se mogla poslati na daljnju obradbu. Time je uvećana i ukupna vrijednost rudnika/ležišta.
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