The Iberian Pyrite Belt (IPB), a historically mined Volcanogenic Massive Sulfide (VMS) region in southern Spain and Portugal, suffers from severe environmental degradation due to unregulated mine closures. This thesis develops a scalable rehabilitation strategy for legacy mine waste in the IPB, using data and samples obtained from the inactive San Miguel mine site. The findings are expanded into broader recommendations for an arbitrarily chosen study area, addressing both active and inactive sites, and offering guidance for sustainable mine management in the IPB and similar mining regions worldwide. In doing so, a multidisciplinary methodology is applied, integrating geochemical analysis, ArcGIS-based spatial modelling, literature reviews, cost assessments, and a Social Life Cycle Assessment (S-LCA) to ensure a comprehensive evaluation of rehabilitation potential and impact in the study area. Heavy metal contamination, primarily arsenic (As), copper (Cu), and lead (Pb), was identified as a major concern, with all sampled materials from San Miguel exceeding regulatory thresholds. The pollution in this area is mainly linked to acid mine drainage (AMD) and mobilization of heavy metals from historic mine waste and slag deposit. Geo-spatial extrapolation using Sentinel-2 imagery enabled mapping of contamination across the study area, justifying areawide remediation measures. A multifaceted rehabilitation strategy is proposed for the study area, combining physical and biological treatments to address AMD and heavy metal pollution from the inactive mine sites. The proposed interventions include the installation of geo-membranes in historical mine ponds to prevent leachate migration,while Sulfate Reducing Bacteria (SRB), applied via Diffusion Active Reactive Permeable Barriers (DAPRB) systems, will treat AMD by neutralizing acidity and precipitating insoluble sulfide metal compounds. Phytostabilization, using metal tolerant native plants, will immobilize contaminants in soil, and revegetation will enhance slope stability and support ecosystem recovery. Together, these approaches address historical and present mining related pollution in the study without aiming to eliminate naturally occurring acid rock drainage (ARD), focusing instead on mitigating its mining induced intensification. The total estimated rehabilitation cost for the seven historical mine sites in the study area is approximately €25.2 million, with revegetation and geo-membrane installation being the most expensive components. A S-LCA was conducted to evaluate the socal and socio-economic impacts of legacy and ongoing mining activities, as well as the projected outcomes of the proposed rehabilitation efforts in the study area. The S-LCA shows that historical and active mining have disproportionately affected local residents, farmers, and municipalities in terms of health and environmental degradation.For instance, the study area is commonly referred to as the triangle of death, whereas it has the largest cancer mortality rate in all of Spain. Conversely, reclamation improves outcomes in those same domains, especially for communities closest to the intervention zone of the study area. Recommendations are also formulated for Zones 2–4, which include active and inactive mine sites. Inactive mines should adopt the study area plan with minimal adaptation. Active mines must incorporate early-phase AMD mitigation, proactive monitoring, and closure planning to prevent legacy pollution.

Analysis of petrographic thin sections is crucial to determine rock properties such as texture, crystal size distribution, porosity and structure of rocks at a microscopic level. However, an accurate determination of minerals and textures in petrographic thin sections is a time-consuming process. Despite efficiency improvements through intensity-based segmentation, thin section petrography remains slow and manual, leaving a significant amount of sections unexamined due to time constraints. This project aims to determine whether object-based segmentation can be used to segment similar mineral phases in petrographic thin sections using the AI-driven ZEISS arivis Cloud (formerly APEER).

Samples used in this project were collected by the authors of Schmiedel et al. (2021) across a traverse of the high viscosity Sosa Dyke (37°2’S, 68°52’W) in Argentina. Ten thin sections of trachyte/trachydacite composition were scanned under bright light (BL), circularly polarized light (CPL), cross-polarized light (XPL) and plane-polarized light (PPL) using the ZEISS Axioscan 7 and provided to be used in this project.

The effects of annotation quantity, image resolution and the combination of CPL and BL images in a single model were investigated through the creation of multiple AI segmentation models using arivis Cloud. Additionally, the time spent on segmentation was compared to intensity-based segmentation, point counting, and manual segmentation. The classes used to segment images were amphiboles, plagioclase, and opaque minerals.

Results from this project show that ZEISS arivis Cloud can be used to segment thin sections using object-based AI models. Object-based segmentation with ZEISS arivis Cloud is shown to be more time-efficient than other manual and intensity-based segmentation methods. Larger datasets of similar thin sections result in greater time savings, and the platform also generates valuable data which can be used for geologic interpretation. BL images produced more accurate models than CPL images, and increased annotation of images improves model accuracy. Models trained on higher resolution images more accurately differentiated between plagioclase and amphiboles. Conversely, higher resolution models were less consistent in identifying large plagioclase crystals. Annotation bias and arivis Cloud performing optimally when objects are no larger than 320*320 could be reasons for this. Although contradictory to the recommendations of the arivis Cloud documentation, combining BL and CPL images into a single model may improve segmentation accuracy when applied to BL images.

If fully optimized, ZEISS arivis Cloud could become an important tool for analyzing thin sections that were previously deemed too time consuming, potentially unlocking new geologic insights

Surface mining operations can have a significant visual impact on the surrounding landscape and communities. There have been numerous cases of local populations pushing back against the development of mining operations near their communities. This study aims to determine whether it is possible to assess the visual impact of surface mining operations before the development has started. With this assessment it would become possible to make informed decisions as to pitshell development and selection in terms of visual impact. A tool was developed to determine whether it is possible to make this assessment. This tool must be able to be used to determine the visual impact of two or more scenarios in the pre-feasibility phase of development to assist in the decision of
which scenario will be developed further in the feasibility phase. In this context, the visual impact is defined as the perceived change in the landscape as a result of mine development on local communities around the surface mine development. The scenarios are defined as the option of pitshells designed during the pre-feasibility phase of mine development.

The tool makes a distinction between the physical changes in the landscape caused by the surface mining operation and how this physical change is perceived by anyone viewing the operation.

The tool is GIS based and utilizes the free open-source software QGIS to calculate the physical change in the landscape. The tool calculates the vertical and horizontal visibility angle. The visibility angle describes the extent that the change in the landscape takes up in the view of an observer. In addition
to that, the tool calculates the contrast between the changed colour in the landscape and its surroundings, which describes how much the change stands out. It requires two sets of data to work: a digital elevation model of the prospected surface mine pitshell and the surrounding landscape and a
RGB satellite image of the surrounding area. The DEM provides elevation data for every square metre of the landscape to the GIS, while the satellite image provides RGB colour data. All other data can be generated from the previously mentioned data features.

The tool is tested using a case study, in which several distinct pitshell scenarios are compared against one another on their visual impact. The case study is based on the extension of a limestone quarry in
Belgium, which aims to secure reserve for future operations. The area of interest is surrounded by several small to medium size villages, which would be affected visually by the extension. Therefore, a comparison should be made regarding the visual impact of the several pitshell scenarios. The results showed it is possible to determine the visual impact of surface mining operations before the
development has started. On this basis, it is possible to compare different pitshell scenarios and determine which scenario would be least impactful in terms of visual impact on the local community and surrounding landscape. The reliability of the tool can only be assessed theoretically, however a high level of accuracy is achieved by adhering to guiding principles which are set out in this thesis.

More than 30% of the world’s hydrocarbon reserves are located in carbonate reservoirs, and this percentage is likely to increase, as a result of discoveries of new giant oil fields in carbonate rocks, generically named “Pre-salt layers”. However, there are still some problems in understanding karst systems that still unresolved. The karst caves are one of the suitable analogs for karstic reservoirs that also spread all over the world. In this study, the mobile LIDAR (Light Detection and Ranging) data is used to characterize the geometries and to analyze the stability of tunnels under several depths from 5 caves in Bahia, Brazil. The studied caves are representing both of the karstification mechanism (Epigene & Hypogene). In general, there are two tunnel shapes among the caves: horizontal ellipse & Vertical ellipse shapes. Several factors could be controlled the shape origin of the tunnels, but from this study mainly caused by lithology or the geology structure factor. By comparing with the structural data, the conduit orientation generally shows the same trend. Therefore, these conditions suggest a geometrical correlation between the fractures and the caves, and that the observed fractures almost certainly acted as conduits for fluid flow. The stability analysis showed that the vertical ellipse tunnels are more stable compared to the horizontal ellipse. However, all of the tunnels are already unstable in shallow depth (on average less than 2 km depth). The sensitivity tests show several parameters that would affect the stability: Rock Properties (Rock Mass strength, Rock mass elastic, density), number of tunnels in the system and the distances between multiple tunnels.

The decrease in the production of hydrocarbons in combination with a growing urgency to reduce carbon emissions drives a rapid study and application of geothermal energy in the Netherlands. The produced heat from the low enthalpy geothermal energy can be used for heating up the buildings and greenhouses. A doublet system is used in the geothermal scheme, which consists of one production well and one injection well. The reinjection is done to maintain the reservoir pressure and reduce pressure decline due to production, earthquake and subsidence prevention, and environmental safety. Thus, it is crucial to model the aquifer distributions appropriately as the injection and production well should be placed at the communicated sand bodies.
In this study, the architecture of the Alblasserdam Member in the Drechtsteden, West Netherlands Basin is modelled. An investigation of the paleo flow and the distribution of sand prone succession within the Alblasserdam Member is done by integrating seismic interpretation, reservoir sedimentology, and petrophysical evaluation. The data used consist of seismic data, well log dataset and core data from the acquired hydrocarbon exploration data. The Alblasserdam Member was deposited during the Late Jurassic to Early Cretaceous when the high tectonic activities occurred in the West Netherlands Basin and followed by series of inversion impulses made this member bounded by various members at the bottom and the top. The seismic response of the Alblasserdam Member shows a high thickness and depth variations. The sediments of the Alblasserdam Member are highly accumulated in the central part of the study area, bounded by two major faults striking SE-NW.
Several sections of well correlation are made based on cycles of changing accommodation to sediment supply ratio (A/S cycles). The correlation is supported with seismic interpretation, allow to map the distribution of sand-rich interval of the Alblasserdam Member in the Drechtsteden. Two potential aquifer intervals are found. A southwestward shifting of the main fluvial system is observed from the thickness trend of the shallower aquifer intervals. A petrophysical evaluation is made to analyze the properties of the potential aquifer that encompass net to gross thickness (N/G), average porosity, and average permeability. The deeper potential aquifer has a higher clean sand N/G, but lower average permeability, that might be caused by the compaction, and mineral precipitation after the inversion period, especially in the highly inverted area. In the end, a recommendation to place a pair of production and injection wells are proposed based on the high accumulation of sand-rich intervals, sufficient depth to produce heat >70^oC and absences of the fault. The wells are placed toward SE-NW trend which is parallel to the distribution of the main fluvial distribution and the orientation of the faults, with production well placed at the deeper level.

In the mining industry the initial capital expenditure budgeted in the feasibility study is being overrun structurally. These capital expenditure overruns have long been recognised, yet no method is available predicting the probability a mining project will experience an overrun.

This thesis introduces a method to assess the likelihood and magnitude of an initial capital expenditure overrun occurring for future gold mining projects. A database is populated with 65 gold mining projects that have experienced an overrun. For each project, 19 variables are described in the database that define the projects. The variables are analysed using individual variable analysis and multivariate regression analysis to investigate whether a correlation can be found between the variables and the initial capital expenditure overrun. Using the results of the individual variable analysis, a tool is developed to semi-quantify the risk a future gold mining project is exposed to regarding an initial capital expenditure overrun. The tool can visualise the risk a project is exposed to in a 2D risk matrix displaying the likelihood and magnitude of a possible overrun.

For 16 of the 19 variables a possible correlation is found. The variables are grouped together, representing root causes with regards to the initial capital expenditure overrun. The database analysis suggests that relatively small gold mining projects experience a larger capital expenditure overrun than large gold mining projects. In addition, projects owned by relatively large companies tend to experience a larger capital expenditure overrun. Furthermore, projects where a low number of payback years or a high internal rate of return presented in the bankable feasibility study indicate a profitable project tend to experience a smaller capital expenditure overrun. Finally, the database suggests a correlation between the relative gold price and the capital expenditure overrun. Projects from which the bankable feasibility study was published when the gold price was relatively high, tend to experience initial capital expenditure overruns more frequent and with a larger magnitude. Using the correlations resulting from the database analysis, a predictive tool is successfully developed for which future gold mining projects can be assessed on initial capital expenditure overrun risk.