Gospodarka Surowcami Mineralnymi - Mineral Resources Management

The paper presents non-standard decision-making methods for selecting exploitation parcels, based on the natural hazards risk assessment in a copper ore mine. Based on diversified quality characteristics of the ore in four preparatory sections, the possible revenues were estimated using the NSR formula. The obtained revenues were compared with the probability of natural hazards occurring including gas outbursts, sudden inflows of water into the workings, outflow of water and/or sand water in the workings, disappearance or reduction of the deposit in the elevation zone, disappearance of the deposit in oxidized Rote Fäule zone, simultaneous disappearance of the deposit in the elevation zone and oxidized zone. It was assumed that a possible natural hazard would affect the level of income achieved, according to the probability of its occurrence and its type, and the theoretical decision- -making model would explain and justify the selection of the safest exploitation sections. Utilizing the risk matrix, the possible effects of the emergence of hazards and their consequences from the standpoint of occupational safety and safety in terms of maintaining the continuity and profitability of mining operations were assessed qualitatively on a five-point scale. The quantitative measures obtained in this way were proposed as payoff amounts in two-player non-zero-sum games. The game solutions enabled to establish the hypothetical hierarchy of exploitation sections in relation to the above-mentioned safety criteria, indicating the optimal strategy for the exploitation front.

In the past two decades, the significance of LNG trade within the framework of international natural gas exchange has grown dynamically. In 2020, for the first time in history, the share of LNG exceeded 50% of global natural gas trade. The issue addressed in this article-namely, the role of liquefied natural gas (LNG) in balancing natural gas demand-holds critical importance for energy security, particularly in the current context of the war in Ukraine. The research analysis presented in the article, from a subjective (actor-oriented) perspective, pertains to the state, while the objective (issue-oriented) dimension concerns natural gas, with particular emphasis on LNG. The study employs factor analysis as well as comparative analysis. The following conclusions have been formulated. F irst, the ongoing war in Ukraine has emerged as a principal driver of increased global LNG demand and has significantly reshaped the architecture of gas supply contracts. Natural gas is gaining importance in Poland. Second, the rapidly evolving conditions in global energy markets have resulted in a shift in global LNG export leadership, with the United States now assuming the dominant position. Third, the diversification of natural gas supplies to Poland has been made possible by the development of a robust energy infrastructure. Notably, since 2022, the importance of the LNG terminal in Świnoujście has increased markedly, and it is now regarded as one of the most strategically significant components of the country’s energy infrastructure.

The energy transition of the power system in Poland has accelerated recently. The plans for coal phasing out are developed, and role of the natural gas is emphasized in mid- and long-term strategies. This trend is also observed in the recent capacity market results in which natural-gas-fired power plants and combined heat and power plants are among the main beneficiaries, provided the duration of the capacity contract is taken into account. The study is devoted to examining the impact of the main capacity auctions results (for the delivery years 2021–2029) on the future natural gas consumption in the Polish power system. For this purpose, the results of this support mechanism are analysed, and the capacity market units are identified with regard to the fuel used for electricity production. The auctions held by December 2024 are analysed to provide the most up-to-date remarks. The obtained results indicate that the additional demand for high-methane natural gas (mainly from CCGT power plants, but also from cogeneration CCGT units, simple cycle gas turbines, and gas engines, with a total gross installed capacity of approximately 5.0 GWe) could range between 2.8 and 8.5 billion m³ by 2030, depending on the assumed capacity factor (30–90%), with an estimated value of approx. 6.6 billion m³ for a capacity factor of 70%. The construction of large-scale gas-fired generating units with the support of capacity market mechanism, significantly impacts (i.e. changes in the fuel mix, the need for expansion of natural gas transmission infrastructure, dependence on imported fuel prices, risks of supply shortages, etc.) – in the long term perspective – not only on the power sector but also on the fuel sector, affecting the security of natural gas supply to Poland.

This study investigates the effectiveness of various polymer types, including hydrophobically modified polymers, polysaccharides, and synthetic polyacrylamides, in enhancing oil recovery and reducing environmental impact. This research aims to comprehensively evaluate the effectiveness of polymer compositions in flow-correcting technologies for oil production. Experimental research conducted at Satbayev University in 2024 evaluated polymer solutions under simulated high- -temperature and high-salinity reservoir conditions, examining their potential to improve fluid viscosity, control filtration processes, and optimize hydrocarbon extraction. The research revealed significant technological advantages of polymer compositions, demonstrating their ability to create stable emulsions, reduce water recovery, and improve oil displacement profiles. Hydrophobically modified polymers increased reservoir fluid viscosity by 30%, while synthetic polyacrylamides showed remarkable adaptability to diverse geological conditions. Economic analysis indicated that polymer technologies could increase oil recovery by approximately 43% without requiring additional well drilling, thus reducing capital expenditures. Despite challenges related to temperature stability and economic considerations, the study concludes that polymer compositions represent a promising strategy for sustainable and efficient oil production, offering technological flexibility and improved resource management.

Underground carbon dioxide storage is considered a technology that can significantly reduce CO₂ emissions into the atmosphere. Following the capture of CO₂ from large industrial emitters, implementing this technology is becoming increasingly urgent on the global path to net zero emissions. this technology requires searching for appropriate structures that meet the requirements of underground CO₂ storage. the suitability of a geological structure for underground CO₂ storage stems from its dynamic capacity, which ensures the injection of the largest possible and safe amount of gas. Its determination requires each time a simulation of CO₂ injection based on a reliable geological model of the structure.

A geological model of the Jeżów structure dedicated to CO₂ storage in the Lower Jurassic layers was built, and injection simulations were conducted for 36 different injection well locations. the dynamic CO₂ storage capacity was presented for the considered injection well locations using the CO₂ storage capacity map. Spatial variability of the CO2 storage potential was noted. It results from pressure-related constraints (both fracturing and capillary) and varies in the case of the Jeżów structure, depending on the injection well location, from 94.36 to 147.37 million tonnes of CO₂. the obtained result is influenced by the geological and reservoir parameters of the reservoir layers and the caprock, their arrangement, the distance of the injection well from the top of the structure, and the inclination of the layers. the presented results allow for more effective and safe planning of CO₂ storage, emphasizing the importance of optimal injection well layout for maximizing capacity, effectively using the structure, and reducing the risk of gas leakage.

Experimental studies were conducted in laboratory conditions to assess the suitability of alder and birch for use in individual home furnaces and the potential storage of ashes in the environment. Raw biomass samples were combusted at 450–500 ± 15°C. The tree species (alder and birch) originated from Poland (Małopolskie Voivodeship) and the “Bory Tucholskie” National Park (Pomorskie Voivodeship). This study aimed to determine the content of toxic metals (As, Cd, Cr, Cu, Hg, Ni, Pb, T l) in raw biomass and its ashes, ions eluted from water eluates of ash, and to analyze the thermal degradation process of wood. In addition to the analysis, the study used inductively coupled plasma optical emission spectroscopy (ICP-OES ) and ion chromatography (IC), thermogravimetric analysis analyses (TG /DSC), and powder X-ray diffraction. The content of volatile parts in wood biomass ranges between 67.2–82.5%, ash content 2.9–19.1%, and calorific value 14.8–17.1 MJ/kg. Moisture content in the wood biomass ranges from 14.6–18.7% (birch) and 17–19.2% (alder). The content of toxic metals was generally low in raw biomass, except for Co, Zn, and Ni, and higher in ashes, varying depending on the origin of the biomass. TG /DSC curves allowed for the identification of the main stages of wood biomass degradation, corresponding to moisture content in the range of 2.73–5.83% (wt.%), ash (0.58–3.68% wt.%), volatile matter (59.63–76.46% wt.%), and fixed carbon (20.23–32.3% wt.%). Higher sulfate and potassium ion concentrations were detected in water eluates of ashes from the “Bory Tucholskie” National Park. The research results do not indicate that alder and birch may be used for low-temperature combustion. However, it is advisable to conduct comprehensive studies research in this area.

A common direction of reclamation of open pits and land subsidence in post-mining areas is the water direction. The quality of water in reservoirs created in this way depends on a number of factors, e.g., the method of reclamation, current use, and the size of the reservoir. The paper presents the results of water toxicity tests for three anthropogenic reservoirs of different sizes, created in different ways and with different methods of use. Two of them are related to sulfur extraction; one was created in an open pit (Tarnobrzeg Lake), and the other in subsidence areas after borehole exploitation (reservoir on the area of the former Jeziórko Sulfur Mine). The third reservoir was created in a quarry after aggregate exploitation (Bagry Reservoir in Cracow). All forms of recreation are allowed in two of the reservoirs, and fishing is allowed only in one. The scope of the presented research results concerns the germination and early growth test against Lepidium sativum and the reproduction test against Daphnia magna. The results of toxicity tests of bottom sediments collected from Tarnobrzeg Lake and the Bagry reservoir were also presented (germination and early growth tests against Sorghum saccharatum, Sinapis alba, and Lepidium sativum). Based on the bioassays, it was found that the water in Tarnobrzeg Lake is of the best quality, while the water in the reservoir in the area of the former Jeziórko Sulfur Mine is of the poorest quality. The good quality of water in Tarnobrzeg Lake is undoubtedly due to its size. Bottom sediments from Tarnobrzeg Lake showed no toxicity towards plants, and bottom sediments from the Bagry reservoir showed low toxicity towards two plant species.

The article presents an innovative method for parameter identification of the Knothe integral- -geometric model, which is based on analyzing subsidence differences for pairs of points. This method leverages observations from monitoring the displacements of buildings and engineering structures in areas affected by mining activities. By utilizing relative observations, i.e., differences in subsidence between point pairs for individual structures, elevation benchmarks are not needed during measurements. A key assumption of the methodology is the use of the asymptotic subsidence state, corresponding to the final stage of subsidence trough formation. Model parameters are iteratively determined by solving the inverse problem using the Gauss-Markov algorithm. This approach minimizes the sum of squared differences between the measured and calculated subsidence differences, enabling precise parameter fitting to the observed data. The implementation of a computation stop criterion concludes the iterative process of parameter identification. This criterion is based on achieving convergence in the form of a defined change in the estimated parameter values of the model between iterations, ensuring the efficiency and stability of the computations. The practical applicability of the method was validated using simulation data, confirming its capability to reconstruct the entire displacement field. The results enable not only the assessment of risk for unmonitored structures but also the prediction of future impacts of planned mining operations on the surface of the studied region.

The existing target detection algorithms detect the ore on the conveyor belt after the crushing process with low precision and slow detection speed. This leads to challenges in achieving a balance between precision and speed, to enhance the detection precision and speed of ore, and in view of the problems of leakage, misdetection, and insufficient feature extraction of YOLOv5 in the task of ore image detection; this study presents a target detection approach relying on the CA attention mechanism (Coordinate attention for efficient mobile network design), the SIoU loss function and the target detection algorithm YOLOv5 combination of ore image particle target detection method. Integrating the CA attention mechanism into the YOLOv5 backbone feature network enhances the feature learning and extraction of ore images, thereby improving the precision of the detection model; the SIoU loss function is refined to boost the recognition precision of the network on ore images and address the shortcomings of the original loss function that fails to take angular loss, distance loss, and shape loss into account, thereby further improving the precision and speed of ore image detection. The experimental findings demonstrate that the AP value, value, and precision rate are improved compared with the pre-improved algorithm. The CA-YOLOv5 method is verified to be fast, effective, and advanced and provides a foundation for real-time target detection of ores on conveyor belts in subsequent intelligent mine production.

A robotic arm can determine the crushing center of ore using point clouds reconstructed by a binocular camera. However, noise in the original point cloud creates ambiguity, complicating the determination process. To address this, an efficient noise filtering and smoothing algorithm for point clouds is proposed. First, the topological relationships among the point clouds are established using a K-D tree, enabling neighborhood selection and query for each point. The density and density variance for each neighborhood are then calculated via the K-nearest neighbor density filtering method. Clustering is applied to determine the average density, and the optimal K value is adaptively obtained based on both the density variance and cluster densities with assigned weights. The local outlier factor is subsequently calculated using this K value, and noise points are filtered out by setting an outlier factor threshold. Based on the enhanced K-nearest neighbor density filtering algorithm, the experimental results demonstrate that this method achieves a denoising precision of 95.68%, representing an improvement of 55.06% over the traditional Radius filtering method and 27.5% over the statistical filtering method. Additionally, the noise recall rate reaches 99.92%, and the original retention rate is 94.17%, showcasing superior filtering performance while preserving data integrity. These advancements provide a reliable technical foundation for subsequent ore crushing and point cloud data processing tasks.