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.

In mineral resource estimation, identification of the geological domains to be used for modeling, and the type of boundaries dividing them, is a major concern. Generally, the variables within a domain are estimated with an assumption of the hard boundaries (sharp contact). However, in many cases, the geologic structures that generate a deposit are transitional (overlapping of several geologic domains). Consequently, boundary identification of the geological domains is essential for an accurate estimate of resources. This paper considers a real application to examine whether the addition of geologic information benefits grade estimation in the presence of transitional boundaries. Results proved that the accuracy of the grade estimation can be improved by adding geological information and there is a significant sensitivity in grade estimation results in the existence of transitional boundaries.

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.

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.

Rock mass fractures adversely affect the production of ornamental stone quarries. Fractures cause natural rock blocks, which threaten extraction of the required commercial block size of ornamental stones. Accurate subsurface detection and modeling of fractures are required for pre-exploitation evaluation and planning. This paper introduces a new three-dimensional deterministic fracture modeling approach using ground penetrating radar (GPR) as a data acquisition tool. A case study was performed in a fractured bench of a sandstone quarry in Firenzuola, Italy, using a 400 MHz GPR antenna. To accurately detect fractures at true depth, an in situ calibration based on previous knowledge of the depth of a subsurface reference reflector allowed us to estimate a bulk dielectric constant of the rock mass during the time of data acquisition. A data interpretation tracing technique was developed to model fractures as 3-D surfaces in two forms, either irregular or planes. The modeled fractures were visualized through a multi-platform visualization software package (ParaView). A comparison between the orientations of the fractures measured by the traditional manual method and the orientations of the modeled fractures is presented as a possible geologic validation for the detection and interpretation of fractures. For the objective of pre-exploitation evaluation, a distribution analysis provided an evaluation-based fracture index for the bench in the case study.