As the global need for aluminum constantly rises, bauxite is considered to be a critical mineral, and the mining industry is in search of new and effective exploration solutions. In this context, we design and implement a purely earthquake-based passive seismic survey at the Gerolekas bauxite mining site in Greece. It is a very difficult exploration setting, characterized by rough topography, limited accessibility, and a very complex geotectonic regime. We gather a passive seismic data set consisting of four months of continuous recordings (May to August 2018) from 129 stand-alone 3C seismological stations. We then analyze this data set and extract 848 microearthquakes that will serve as sources for the application of local earthquake tomography (LET) and transient-source seismic interferometry (TSI) by autocorrelation. We apply LET to estimate the 3D P- and S-wave velocity models of the subsurface below the study area and TSI by autocorrelation to retrieve the zero-offset virtual reflection responses below each of the recording stations. The velocity models provide a relatively coarse image of a previously completely unexplored part of the mining concession, whereas the higher-resolution virtual reflection imaging illuminates in detail the different interfaces. We also reprocess three lines of legacy active seismic data that were shot in 2003, using the LET P-wave velocity model for depth migration, and confirm the improvement of seismic imaging. Finally, we evaluate the obtained results using well data and jointly interpret them, extracting useful information on the expected target depths and indicating that earthquake-based passive seismic techniques can be an innovative and environmentally friendly option for mineral exploration.

This study presents a gravity survey conducted for mineral exploration in the Gerolekas overthrust area at a bauxite mining site in Central Greece. In the summer of 2018, a gravity survey, covering 28 km², was conducted, including confirmed and unexplored zones. By utilizing gravity data, we investigated the shallow subsurface geology and structural sequences, resulting in a high-resolution 3D density model. This model is generated through constrained gravity inversion by the exploitation of the boreholes available at mining sites, and the geological survey fills the areas with boreholes, which provides the stratigraphy to some depth. The suggested data-processing techniques provide information for the tectonism of the area, which is also important for mineral exploration, as well as mining design. The interface with density contrast between the flysch and the underlying limestone in the high-resolution 3D density model provides useful information on the geological status, but also, the slight density difference in limestone provides an interface where bauxite deposits can be. The inversion, conducted with EMIGMA software, incorporated high-resolution topography data and density constraints to produce a reliable 3D density model. The findings highlight the gravity method’s potential to enhance mineral exploration efficiency, offering a robust tool for further geological and mining considerations.

This work introduces a methodology for the automatic unmineable inclusions detection and Bucket Wheel Excavator (BWE) collision prevention, using electromagnetic (EM) inspection and a fuzzy inference system. EM data are collected continuously ahead from the bucket wheel of a BWE and subjected to processing. Two distinct methodologies for data processing were developed and integrated into the MATLAB programming environment. The first approach, named “Simple Mode”, utilizes statistical process control to generate real-time alerts in the event of a potential collision involving the excavator’s bucket and hard rock inclusions. The advanced processing flow (“Advanced Mode”) requires accurate instrument positioning and data from successive EM scans. It incorporates techniques of local resistivity maxima detection (Position Prominence Index) as well as Neural Network-based Pattern Recognition (NNPR). A decision support process based on a Fuzzy Inference System (FIS) has been developed to assist BWE operators in avoiding collision when digging hard rock inclusions. The proposed methodology was extensively tested using synthetic EM data. Limited real data, acquired with a CMD2 (GF Instruments) EM instrument equipped with GPS, were used to control its efficiency. Increased accuracy in the automatic detection of unmineable inclusions was observed using the Advanced Mode. On the other hand, the Simple Mode processing technique offers the advantage of being independent of instrument positioning as well as it provides real-time inspection of the excavated mine slope. This work introduces a methodology for hard rock inclusion detection and can contribute to the optimization of mine operations by improving resource efficiency, safety, cost savings, and environmental sustainability.

Shear‐wave velocity constitutes an important characterization parameter in terms of engineering properties. Several techniques of surface wave analysis have been widely adopted for building near‐surface 1D, or even 2D, S‐wave velocity models, but comparable 3D approaches, such as the surface wave tomography (SWT) method, are usually limited to global or regional seismological studies. Moreover, a reliable 3D subsurface imaging in a complex and noisy near‐surface environment becomes difficult when using the fully automated processing techniques that are commonly suggested for the SWT method. Here, a new strategy that is well adapted to geotechnical investigations is proposed to accomplish automatically the frequency‐dependent mapping of Rayleigh waves, both for group and phase velocity, throughout an active seismic network. The specific methodology can be implemented in both 2D and 3D active seismic data acquisition schemes involving both uniform and non‐uniform layouts of receivers. It combines the advantages of a newly created common‐midpoint (CMP) cross‐correlation (CC) analysis technique, with the precision of the travel‐time tomography method that is usually used in regional seismological studies. The main analysis is based on partitioning the different wave propagation directions, weighting the CC frequency–velocity analysis around one‐wavelength and stacking the CMP dispersion images. The tomographic inversion is applied to frequency‐dependent virtual travel‐times, produced from the azimuth‐dependent results of the specific analysis, in order to generate, as output, the local dispersion curves. The output of the proposed processing method can be interpreted with any preferred inversion algorithm for group and phase velocity, either individually or jointly. Simple synthetic tests together with a 3D seismic experiment in well‐known conditions, using standard refraction and multichannel analysis of surface waves (MASW) equipment, confirmed the effectiveness of the proposed methodology in detecting both lateral and vertical S‐wave velocity variations. A ‘construction site’ case study finally highlighted the potential of the new tool in a very difficult and noisy environment.