Gospodarka Surowcami Mineralnymi - Mineral Resources Management

The interpretation of geothermal conditions in SW Poland presented here is based on temperature logs from 80 boreholes, acquired under steady-state conditions at depths exceeding 500 m. The recent and archived drillhole data is also considered. The wells penetrate several tectonic units, including the Sudetes and their foreland, the Fore-Sudetic Monocline and the Opole Basin, each representing a different lithology and structure. Our interpretations offer the spatial temperature distribution over the study area, depending on the depth and height coordinates of the measurements. Average temperature values were observed to increase from 22.8°C at a depth of 500 m, to 63.4°C at a depth of 2.5 km. The highest temperature of 97.7°C was measured at a depth of 1,870 m in the Jelenia Góra-Cieplice C-1 well. Average temperatures at various elevations increase from 16.5°C (0 m a.s.l.) to 61.5°C (–2,000 m a.s.l.). Over the Sudetic Block, higher temperatures can be achieved at the same elevations, while greater depths are required to reach these temperatures in other tectonic units. The results are crucial to planning investments aimed at sustainable management of geothermal resources. They facilitate the identification of locations for new thermal water intakes and thus new sources of renewable energy. The knowledge of thermal conditions of the area makes it possible to plan optimal use of water and geothermal energy in various sectors of the economy (heating, agriculture, recreation, balneotherapy) thus boosting economic development of the region, increasing energy efficiency and limiting negative environmental impact.

Considering the security problem experienced in the world in the supply of critical raw materials within the scope of energy transformation, it would be extremely strategic for countries to operate electric car (EV) factories from their domestic resources. A factory was opened in Bursa on 29/10/2022 for the production of “TOGG”, an electrically powered domestic automobile in Turkey, established by “Turkey’s Automobile Initiative Group” (TOGG). It is curious whether this electric car factory can meet the raw materials it needs in the presence of raw material supply risks worldwide. At this point, it can be considered that the supply from domestic sources gives a raw material supply assurance compared to the foreign supply. In this study, the supply risks of the minerals used in producing electric cars in Turkey were determined, and suggestions were presented to policymakers in this regard. Many metals and minerals are used in EV production. In this study, only lithium, nickel, cobalt, manganese, graphite, and REEs, declared critical in the EU critical raw materials list, have been analyzed in Turkey, considering their potential in the world. In the analysis, without examining the market of the mentioned minerals, the safety of the raw material supply of the TOGG electric car production factory, which is the only one in Turkey with the potential to supply the world, is discussed from domestic sources in Turkey. Considering the TOGG factory operating life and the capacity of the Li-battery factory, an evaluation was made on how many EVs the current apparent reserve potential of the raw materials in question would be enough to produce in total.

Orenagil barites are observed as space fillings, veins, and lenses incompatible with the host rock within the Devonian-aged Meydan formation belonging to the Bitlis metamorphics observed in the Bitlis suture zone in the north of Sason (Batman, Türkiye). Bitlis metamorphites are an important unit that hosts many mineral deposits. Since the study area is very close to the Bitlis suture zone, the effect of tectonism is intensely observed in the field. The mineral assemblage consists of barite, pyrite, chalcopyrite, hematite, goethite, magnetite, bornite, chalcocite, covellite, malachite, azurite, and limonite. The BaSO₄ content of barite samples ranges from 25 to 61 wt% and contains high SrO (2.04 wt%). Fluid inclusions observed in barite samples are predominantly of the fluid-rich two-phase (Liquid+Vapour) type. Homogenization temperatures of fluid inclusions in barites are observed in a wide range (169 to 382.1°C), and salinity values are collected in two different groups (0.27–6.9 wt% NaCl and 12.7–20.45 wt% NaCl). Eu/Eu* values (11.20–121.36) of barites indicate exhalative hydrothermal fluids, whereas Ce/La > 1 (10.03–54.76) indicates a terrestrial origin for barites. In spite of the average REE pattern of barite and their similar host rocks, barite differs from host rocks in terms of their negative Ce peak and strong positive Eu peak. The trends of the REE values of the samples and the values of the barites in the Ce_N/Sm_N–Ce_N/Yb_N diagram indicate that the barites are formed from multiple sources, including seawater and meteoric water.

The study’s relevance lies in the region’s strategic importance for energy security and economic development and the need to devise optimal strategies for hydrocarbon reserves production and management in the face of global market changes and environmental challenges. This study aimed to investigate the geological and geochemical characteristics that influence oil and gas formation and accumulation on the southeastern side of the Pre-Caspian Basin. The research used analytical, classification, statistical, structural-functional, functional, deductive, and synthesis methods. As part of the study of the southeastern flank of the Pre-Caspian Basin, a comprehensive analysis of geological and geophysical data, including detailed seismic interpretation and geochemical analysis of rocks and fluids, was carried out. This multivariate analysis revealed the essential structural features of the region and identified prospective traps for oil and gas. The findings of this study emphasize the strategic importance of the region as a potential source of energy resources while highlighting the importance of attention to environmental and social aspects in the development of these resources. This study represents a significant contribution to the oil and gas industry and helps guide the region’s strategic development with sustainability and resource efficiency in mind. The practical significance of this study is to provide a basis for more efficient exploitation and management of oil and gas resources on the southeastern side of the Caspian Basin, contributing to the region’s economic development and energy security.

Magnetite ore is a non-renewable resource that needs to be utilized effectively. Refined sorting of magnetite ore is not simply sorting it into good ore or waste ore but finely sorting it into different grades due to its magnetite content, which not only helps to improve its utilization but also reduces the energy consumption of the following process. However, traditional ore sorting methods based on optical sensors, X-ray sensors, and high-resolution cameras are challenging to achieve refined sorting for magnetite ores because of the limitations of their respective detection methods and classification algorithms. To this end, a new detection method for magnetite content is proposed in this paper; the magnetic induction signal of magnetite ore when it passes through an external magnetic field is captured by Hall sensors and made into a quantifiable time-series dataset. Meanwhile, a deep learning classification algorithm CNN-SK-BiLSTM with a multi-scale attention mechanism is proposed, which successfully sorts magnetite ore from a mine in Liaoning Province, China, into four classes finely. The experimental results show that the accuracy of the model is up to 99.44%, and the precision, recall, and F1 scores are acceptable. In addition, comparative experiments between the proposed model and other standard models were conducted. The results show that the performance of the proposed model is significantly better than the others. This paper provides ideas for the study of refined sorting of magnetite ore.

Due to the decline in the production of ceramic building materials (bricks, ceramic hollow blocks), alternative possibilities for managing clay raw materials and using equipment for their processing in production plants are sought. Therefore, the subject of this paper is the assessment of the suitability of selected raw clay materials from southeastern Poland for use as mineral sorbents. For this purpose, the following raw materials were used: Krakowiec clays, clay-silica raw materials from the Dynów Foothills, and Krosno slate in their natural state, as well as after sodium and acid activation. Sorption of copper, nickel, zinc, and chromium from their salts was carried out on the samples using the batch static method, aqueous solutions of experimentally determined concentrations. Experiments were performed using an AAS analyzer. The effect of the sorption environment was determined in conditions of changing pH.

It was found that the sorption of heavy metals depends to the greatest extent on pH and smectite content. However, it is also determined by the content of other mineral components, such as illite, kaolinite, opal, zeolite, iron, and manganese minerals. The influence of chemical modification of samples on sorption parameters and morphology of samples was also investigated. The latter factor was considered based on SEM micrographs. On their basis, prospects for developing the tested mineral raw materials for use as a medium-quality sorbent (clay-silica raw material) and in constructing mineral barriers (Krakowiec clays) were found.

The work explores the conditions for the formation of discontinuous linear deformations, which most often take the form of ground steps. These deformations pose a significant threat to building structures, which are extremely difficult to protect from such damage. The frequent occurrence of this type of deformation and the threat it poses to public safety make the issue of predicting them both current and significant. Deformations often occur as a result of intense mining extraction. The paper presents geological and mining conditions that favor the formation of these deformations. The influence of horizontal tensile strain on the occurrence of discontinuous linear deformations is highlighted. Based on the presented case study and the author’s previous work, a conclusion has been drawn about a strain limit under the given conditions at which ground steps may occur. The paper also highlights the potential for discontinuous surface deformation (sinkholes) due to the suffosion phenomenon in the zone where these linear deformations occur.

The paper proposes a method for predicting the location of zones where ground steps may occur due to planned underground mining operations. Despite ongoing decarbonization efforts, intensive extraction of coking coal, which is listed as a critical raw material, will occur. However, such extraction should be conducted in a manner that prioritizes its sustainable impact on the surface. Taking the above into account, an example of conducting underground extraction is provided in a way that minimizes the threat of linear discontinuous deformations.

The paper presents research conducted as part of the project from priority axis 1 Knowledge economy of the Regional Operational Programme for the Małopolska Region for 2014–2020, entitled: “Małopolska Region for 2014–2020, entitled: “Development of a technology for the production of pigment for dyeing red ceramics with the use of MnSi waste generated in the production of ferroalloys with contract number RPMP.01.02.01-12-0497/17-00”. On the basis of the studies of the phase composition of XRD, compressive strength, absorbability, and color measurements in the CIEL*a*b* and CIEL*C*h° color space, it has been shown that it is possible to use MnSi waste containing large amounts of manganese oxides, formed in the production of ferroalloys. The waste (pigments) used for the study differed significantly in the content of manganese and silicon. It was found that the addition of both pigments does not change the phase composition and does not have a significant effect on the functional properties of clinker bricks but changes their color. The color becomes less saturated.

Karst aquifers are among the most widely used drinking water resources worldwide. However, their water quality can deteriorate due to negative anthropogenic impacts. Monitoring the quality of spring water is crucial, both in terms of physicochemical and bacteriological parameters. In this study, 34 parameters of the Zygmunt Spring in Złoty Potok (southern Poland) were analyzed across three measurement series. The average water conductivity was 370 μS/cm, with a pH of approximately 7 and a flow rate of about 17 L/s. The Backman Pollution Index (average value: –13) and the Water Quality Index (average value: 94) were calculated, indicating that bacterial contamination poses the greatest risk to water quality. Additionally, geochemical modeling was conducted to identify minerals undergoing dissolution and precipitation. The results confirmed the dissolution of calcite and dolomite, as well as the precipitation of goethite and hematite.

Accurately identifying the load status of the ball mill during the grinding process is conducive to improving the overall production efficiency and ensuring the safe operation of the entire grinding process. In this study, ball mill loads were classified into nine categories based on charge volume ratio (CVR) and material-to-ball volume ratio (MBVR). Different sensors are utilized to collect cylinder vibration and acoustic signals in the grinding process, respectively, and the raw data are converted into time-frequency images by continuous wavelet transform. In this paper, the ResNet18 model is improved from three aspects, namely, depthwise separable convolution (DSC), dropout layer, and Hardswish activation function, and an improved residual fusion network (IRF-Net) based on the merging of two time-frequency image signals is proposed for load recognition. In order to validate the performance of the proposed model, time-frequency images of the acquired data are analyzed, single and multiple signals are used as network inputs, respectively, compared with other classical models, and ablation experiments are performed on the different modules of the improvement. The results show that the improved residual fusion network achieves the best results in recognition with an accuracy of 98.33%, demonstrating good load recognition. The IRF-Net-based multi-signal time-frequency diagram identification method can be utilized to make a sound judgment on the load status of the mill.