Search Results (1,335)

Coalbed methane (CBM) is a vital clean energy resource, yet its extraction efficiency is often hindered by rapid production decline and low production rates in medium-shallow reservoirs. This study investigates the potential of CO₂ huff-and-puff technology to enhance CBM recovery and achieve CO₂ storage in low-productivity wells. A comprehensive model, constructed based on the geological conditions of the Qinshui Basin, was developed. Numerical simulations revealed that CO₂ huff-and-puff significantly improves CH₄ production by displacing adsorbed CH₄ and maintaining reservoir pressure. Key findings indicate that higher CO₂ injection volumes yield substantial increases in both peak CH₄ production and cumulative production compared with conventional extraction. Optimal soaking times balance recovery efficiency and operational costs. Sensitivity analysis identified gas diffusion coefficients, initial permeability, and Langmuir volume constants as critical geological parameters influencing the performance. This study preliminarily demonstrates the feasibility of large-scale CO₂ huff-and-puff for enhancing production in low-productivity CBM wells and provides theoretical insights for revitalizing China’s underperforming CBM wells while advancing carbon neutrality goals, although further experimental validation is still required. Full article

Subsidence over abandoned goaves is a primary trigger for secondary geological hazards such as surface collapse, landslides, and cracking. This threatens safe mining operations, impairs regional economic progress, and endangers local inhabitants and their assets. At present, goaf areas are mainly treated through grouting. However, owing to the deficiencies of traditional deformation monitoring methods (e.g., leveling and GPS), including their slow speed, high cost, and limited data accuracy influenced by the number of monitoring points, the surface deformation features of goaf zones treated with grouting cannot be obtained in a timely fashion. Therefore, this study proposes a method to analyze the spatio-temporal patterns of surface deformation in grout-filled goaves based on the fusion of Multi-temporal InSAR technologies, leveraging the complementary advantages of D-InSAR, PS-InSAR, and SBAS-InSAR techniques. An investigation was conducted in a coal mine located in Shandong Province, China, utilizing an integrated suite of C-band satellite data. This dataset included 39 scenes from the RadarSAT-2 and 40 scenes from the Sentinel missions, acquired between September 2019 and September 2022. Key results reveal a significant reduction in surface deformation rates following grouting operations: pre-grouting deformation reached up to −98 mm/a (subsidence) and +134 mm/a (uplift), which decreased to −11.2 mm/a and +18.7 mm/a during grouting, and further stabilized to −10.0 mm/a and +16.0 mm/a post-grouting. Time-series analysis of cumulative deformation and typical coherent points confirmed that grouting effectively mitigated residual subsidence and induced localized uplift due to soil compaction and fracture expansion. The comparison with the leveling measurement data shows that the accuracy of this method meets the requirements, confirming the method’s efficacy in capturing the actual ground dynamics during grouting. It provides a scientific basis for the safe expansion of mining cities and the safe reuse of land resources. Full article

The global demand for strategic minerals like scheelite is growing rapidly due to technological advancements and emerging industries, making it a key global resource. However, there is a lack of integrated research on utilization technology of scheelite from a global perspective and exploring its future development direction. Bibliometric methods have been widely applied due to their advantages in the analysis of qualitative and quantitative literature information. Based on 1137 publications from the Web of Science Core Collection spanning 1999 to 2024, this study systematically examines the global and Chinese research trajectories and emerging frontiers in scheelite resource utilization technologies. A paradigm shift from fundamental geological and material property studies to green beneficiation, low-carbon metallurgy, and intelligent process optimization has been revealed. Key global research hotspots include flotation separation, surface chemistry regulation, LA-ICP-MS micro-analysis, and photoluminescence properties, whereas China has developed distinctive strengths in complex polymetallic ore separation, leaching kinetics, and tailings valorization. Chinese institutions contribute over 54% of worldwide output, with Central South University leading in publication volume, collaboration networks, and academic impact. Future efforts should prioritize intelligent process control, the efficient separation of complex polymetallic ores, and the high-value recovery of secondary resources. Full article

Accurate grade prediction in porphyry copper deposits requires not only capturing spatial continuity but also accounting for geological controls. This study evaluates the added value of incorporating alteration and mineralization domains into machine learning (ML) models for copper grade estimation at the Iju porphyry Cu deposit, Iran. We compare four scenarios: spatial coordinates only, coordinates + alteration, coordinates + mineralization, and coordinates + both domains. A three-stage workflow was developed, in which Random Forest classifiers—optimized with Particle Swarm Optimization (PSO-RF)—classify alteration and mineralization zones, which are later integrated into regression models for ore grade prediction. Model performance was assessed using nested spatial cross-validation and benchmarked against Support Vector Machines (SVM). In comparative analysis, the PSO-RF framework consistently outperformed SVM, achieving more balanced accuracy between training and testing data and demonstrating greater robustness to class imbalance in domain classification. Moreover, results show that combining alteration and mineralization domains improves predictive performance (R² = 0.78; RMSE was reduced by 5.6% relative to coordinates-only). Although numerically moderate, this reduction in error translates into more reliable tonnage and grade estimations near cut-off grades, thereby enhancing the economic confidence of resource evaluations. These findings demonstrate that integrating multiple geological domains can improve both the accuracy and interpretability of ML-based grade models, providing a practical and reproducible workflow for porphyry copper resource evaluation. Full article

Remote sensing has emerged as an essential method for geological mapping, especially in complex environments such as the Mediterranean region. While earlier global reviews have been focused either on multi- and hyperspectral sensors in general for geological applications or on hyperspectral sensors using machine learning for lithological mapping and mineral prospecting, this review article provides the first regionally focused synthesis dedicated to the Mediterranean region. The review examines both passive sensors such as Sentinel-2 MSI, Landsat-8 (OLI), ASTER, MODIS, Hyperion, PRISMA, EnMAP, and active sensors such as Sentinel-1, ALOS, TerraSAR-X. Furthermore, the review emphasizes the sensor functionalities, the data integration within Geographic Information System (GIS) platforms and methodological advancements such as machine learning and multi-sensor fusion. A total of 42 case studies are assessed, covering Portugal, Spain, France, Italy, the Balkans, Greece, Turkey, Cyprus, Egypt, Tunisia and Morocco. These examples highlight how remote sensing techniques have been adapted to varying lithological, tectonic and geomorphological settings across the Mediterranean. The analysis identifies key methodological trends, including the transition from spectral indices to advanced data fusion, the growing reliance on open-access available multispectral archives, and the emerging role of new-generation hyperspectral missions (PRISMA, EnMAP) in high-resolution geological mapping. The findings illustrate the non-invasive and scalable advantages of remote sensing for geological mapping in complex terrains, while also noting current challenges such as atmospheric correction, spatial resolution mismatches, and field validation requirements. By combining region-specific applications, this review demonstrates how remote sensing contributes not only to fundamental geological understanding but also to sustainable resource management and mineral exploration within one of the world’s most geologically diverse regions. Full article

Tar-rich coal (with a tar yield ≥ 7%), as a special coal-based oil and gas resource, is of great significance for ensuring national energy security and promoting the clean conversion of coal. The selection of suitable geological sites represents a core challenge for the safe and efficient application of its in situ pyrolysis technology. Focusing on the tar-rich coal seams in the Santanghu Basin, this study constructed a comprehensive geological evaluation system for site selection by integrating numerical simulation, data mining, and laboratory experiments. The Analytic Hierarchy Process (AHP) and a fuzzy comprehensive evaluation method were employed to achieve a quantitative assessment and identify favorable areas within the study region. The results indicate that resource scale, coal seam conditions, and the properties of the roof and floor strata are the key controlling factors. One optimally comprehensive Class I favorable area (Tiao IV block) was successfully identified. This block exhibits a large resource scale, favorable coal seam conditions, a high tar yield, excellent geological sealing, and superior engineering compatibility, making it the recommended priority target for pilot testing. The evaluation system developed in this study can provide a theoretical basis and technical reference for the geological site selection of in situ pyrolysis of tar-rich coal in similar mining areas and advance its industrialization. Full article

Geological models form the basis for scientific investigations of both the surface and subsurface of urban environments. Urban cover, however, usually prohibits the collection of new subsurface data. Therefore, models depend on existing subsurface datasets that are often of poor quality and have an uneven spatial and temporal distribution, introducing significant uncertainty. This research proposes a novel method to mitigate uncertainty caused by clusters of uncertain data points in kriging-based geological modelling. This method estimates orientations from clusters of uncertain data and randomly selects points for geological interpolation. Unlike other approaches, it relies on the spatial distribution of the data and translating geological information from points to geological orientations. This research also compares the proposed approach to locally changing the accuracy of the interpolator through data-informed local smoothing. Using the Ouseburn catchment, Newcastle upon Tyne, UK, as a case study, results indicate good correlation between both approaches and known conditions, as well as improved performance of the proposed methodology in model validation. Findings highlight a trade-off between model uncertainty and model precision when using highly uncertain datasets. As urban planning, water resources, and energy analyses rely on a robust geological interpretation, the modelling objective ultimately guides the best modelling approach. Full article

Gallium (Ga) enrichment in sphalerite has been widely recognized; however, its enrichment mechanisms remain insufficiently understood. The South Hunan district, located at the intersection of the Nanling Region and the Qin-Hang Metallogenic Belt in South China, is characterized by abundant Jurassic magmatic-hydrothermal Pb–Zn deposits, which typically host Ga-depleted sphalerite. Recently, Ga-enriched sphalerite (up to 385 ppm by LA-ICP-MS) has been identified in newly drilled cores at Zhaojinci, adding complexity to the regional Pb–Zn metallogenic framework. EPMA elemental mapping and LA-ICP-MS time-resolved spectra indicate that Ga is homogeneously distributed within sphalerite, excluding the presence of micron-scale Ga-bearing mineral inclusions. A strong positive correlation between Ga and Cu concentrations suggests that Ga incorporation is facilitated by the coupled substitution of Zn²⁺ by Cu⁺. Sphalerite geothermometry yields formation temperatures of 118–138 °C (average 126 °C for GGIMF is and ~129 °C for SPRFT), accompanied by intermediate sulfur fugacity conditions (lg fS₂ = −22.9 to −21.2), which appear to favor Ga enrichment in sphalerite. The trace element geochemistry of the Zhaojinci sphalerite (Ga-Ge-Cd-enriched and Mn-In-Sn-Co-depleted), combined with its formation under low-temperature (120–180 °C) and intermediate fS₂ conditions (within the pyrite stability field), is consistent with MVT-like mineralization. This interpretation is supported by multiple lines of geological evidence, including the strict confinement of stratabound Pb–Zn mineralization to the Devonian Xikuangshan Formation limestone, structural control by syn-sedimentary normal faults, pervasive dolomitization of the host rocks, and the absence of genetic relationship to magmatic activity. Moreover, the sphalerite geochemical signature, corroborated by an XGBoost-based machine learning classifier, reinforce the MVT-like affinity for the Zhaojinci mineralization. This study not only emphasizes the importance of low-temperature and intermediate-fS₂ conditions in Ga enrichment within sphalerite, but also highlights the significance of discovering MVT-like sphalerite for Pb–Zn resource exploration in the South Hunan district, providing valuable new insights and directions for mineral prospecting in this geologically important region of South China. Full article

Ion-adsorption type rare earth element (IREE) deposits are critical strategic resources formed under strong lithological, geomorphological, and weathering controls. In Houaphanh Province, Laos, widespread granitic intrusions and tropical monsoon weathering provide favorable conditions for IREE mineralization; however, exploration is limited by rugged terrain, dense vegetation cover, and sparse geological data. This study integrates Landsat 9, ASTER multispectral, and digital elevation data to enhance IREE exploration. Band ratio and principal component analysis (PCA) were applied to extract lithological and alteration features, while six topographic parameters describing elevation, slope, relief amplitude, incision depth, surface roughness, and elevation variability were derived from ASTER GDEM data. These datasets were combined using a weighted overlay to delineate favorable geomorphic zones. Six prospectives zones were identified, and field verification at Nongkhang confirmed 19 IREE ore bodies. The results demonstrate that integrating spectral and topographic indicators significantly improves the accuracy for IREE prediction in tropical, densely vegetated regions, offering a transferable framework for similar geological settings worldwide. Full article

The article presents a study of the computational complexity and efficiency of various parallel algorithms that implement the numerical solution of the equation in the hereditary $\alpha \left(t\right)$-model of radon volumetric activity (RVA) in a storage chamber. As a test example, a problem based on such a model is solved, which is a Cauchy problem for a nonlinear fractional differential equation with a Gerasimov–Caputo derivative of a variable order and variable coefficients. Such equations arise in problems of modeling anomalous RVA variations. Anomalous RVA can be considered one of the short-term precursors to earthquakes as an indicator of geological processes. However, the mechanisms of such anomalies are still poorly understood, and direct observations are impossible. This determines the importance of such mathematical modeling tasks and, therefore, of effective algorithms for their solution. This subsequently allows us to move on to inverse problems based on RVA data, where it is important to choose the most suitable algorithm for solving the direct problem in terms of computational resource costs. An analysis and an evaluation of various algorithms are based on data on the average time taken to solve a test problem in a series of computational experiments. To analyze effectiveness, the acceleration, efficiency, and cost of algorithms are determined, and the efficiency of CPU thread loading is evaluated. The results show that parallel algorithms demonstrate a significant increase in calculation speed compared to sequential analogs; hybrid parallel CPU–GPU algorithms provide a significant performance advantage when solving computationally complex problems, and it is possible to determine the optimal number of CPU threads for calculations. For sequential and parallel algorithms implementing numerical solutions, asymptotic complexity estimates are given, showing that, for most of the proposed algorithm implementations, the complexity tends to be $n^2$ in terms of both computation time and memory consumption. Full article

Karst mining regions frequently encounter ecological and geological challenges during extraction, especially the increased water inflow into mine pits, water contamination, and karst collapse due to dewatering activities. These challenges not only threaten the safety of mineral resource extraction but also escalate operational expenses. To address these concerns, this study offers a detailed examination of the geohydrological conditions in a karst mining area. It integrates multiple data sources, such as the dynamics of groundwater, mine dewatering activities, and precipitation patterns, to identify the primary sources of water ingress into the mines. The result reveals that the primary water inflow of the mine pits is directly recharged by atmospheric precipitation through runoff zones. Additionally, the key factors leading to karst collapses are the decrease in groundwater levels due to dewatering and the stability of surrounding rock. Consequently, this paper presents a set of innovative methods for water hazard prevention and control. Utilizing the GMS (Groundwater Modeling System), the groundwater numerical model is built to estimate water consumption in mining operations, and also to validate the efficacy of these methods. The model reveals that application of these techniques can reduce groundwater inflow of the mine by 34.3%. The set of methods not only substantially lowers the risk of water inrush incidents but also avoids the contamination of groundwater. Consequently, it ensures the safety of mine production, especially in the wet season. Full article

The characterization of lithology within Quaternary aquifers holds significant geological importance for the protection, management, and utilization of groundwater resources, yet it continues to present considerable challenges. Indicator Kriging (IK) is a non-parametric, probability-based method of spatial interpolation. It considers the correlation and variability between data points, and its popularity stems from its alignment with geological experts’ principles. However, it still encounters issues in complex geological conditions. To address the limited capacity of conventional IK in reproducing geological variables within heterogeneous geological settings, this study develops an ordered IK method incorporating field variogram function parameters. This framework dynamically extends IK applications by integrating stratigraphic extension trends, requiring experts to formalize spatial variation trends into geological knowledge data, subsequently transformed into constraint parameters for interpolation. Estimation paths are determined via Euclidean distances between points-to-be-estimated and valid data, executing ordered IK following near-to-far and bottom-to-top principles. Results directly depict QLS formation spatial distributions or undergo expert modification for quantitative analysis, demonstrating superior integration of geological knowledge compared to empirical variogram fitting and partitioned IK estimation. The method reduces deviation from expert-interpreted spatial distributions while maintaining computational efficiency and multi-factor integration, with three case analyses confirming enhanced accuracy in lithology distribution reproduction and improved geostructural congruence in complex geological reconstruction. This approach revitalizes Kriging applications in complex geological research, synergizing domain cognition with computational efficacy to advance precision in geological characterization and support government decision-making. Full article

The predominant reliance on fossil fuel combustion for energy production continues to release significant amounts of CO₂, causing global temperatures to approach the critical threshold of 1.5 °C. This has led to an increasing frequency of extreme weather events, which pose severe threats to ecosystems, economic development, and human safety. CO₂ mineral carbonation, by mimicking the natural weathering process, facilitates the reaction between minerals and CO₂, resulting in long-term and stable sequestration. Over several decades of development, this technology has evolved from its initial application in natural mineral sequestration to broader use in sectors such as cement concrete, industrial solid waste recycling, and chemical production. It offers an innovative solution for emission reduction and resource utilization in high-emission industries, particularly those characterized by difficult-to-decarbonize point sources. This technology holds promise for the on-site treatment and value-added utilization of industrial flue gas and solid waste at the source. This review systematically presents the research advancements and emerging trends in CO₂ mineral carbonation, covering key aspects such as reaction mechanisms, research progress, engineering demonstrations, and prospects. A particular focus is placed on analyzing the principles of direct and indirect carbonation. The review synthesizes developments in three research domains—geological minerals, cement concrete, and industrial solid waste—and introduces several representative engineering demonstration projects. Furthermore, it discusses the challenges faced at the scientific, technological, and application levels and proposes future directions for the development of CO₂ mineral carbonation technology. This review aims to provide a comprehensive reference for future research, fostering the continued innovation and commercialization of CO₂ mineral carbonation. Full article

Quantitative seismic characterization of transitional shale gas resources in the Da Ning–Ji Xian area, Ordos Basin, is severely hampered by complex coal-measure stratigraphy and rapid lithological variations. These challenges are critically exacerbated by severe signal attenuation from a thick loess overburden and multiple coal seams, which significantly degrades vertical resolution and undermines the reliability of quantitative interpretation. To surmount these obstacles, this study proposes an integrated, attenuation-centric inversion workflow that systematically rectifies attenuation effects as a foundational pre-conditioning step. The novelty of this study lies in establishing a systematic workflow where a data-driven, spatially variant Q-estimation is used as a crucial pre-conditioning step to guide a robust inverse Q-filtering, enabling a high-fidelity quantitative inversion for shale gas parameters in a geological setting with severe attenuation. The proposed workflow begins with a data-driven estimation of a spatially variant quality factor (Q) volume using the Local Centroid Frequency Shift (LCFS) method. This crucial Q-volume then guides a robust post-stack inverse Q-filtering process, engineered to restore high-frequency signal components and correct phase distortions, thereby substantially broadening the effective seismic bandwidth. With the seismic data now compensated for attenuation, high-resolution shale gas parameters, including Total Organic Carbon (TOC), are quantitatively derived through post-stack simultaneous inversion. Application of the workflow to field data yields an inverted volume characterized by improved structural clarity, sharply defined stratigraphic boundaries, and more robust lithological discrimination, highlighting its practical effectiveness. This attenuation-compensated inversion framework thus establishes a robust and transferable methodology for unlocking high-fidelity quantitative interpretation in geological settings previously deemed intractable due to severe seismic attenuation. Full article

With the continuous construction and operation of urban subways, rapid changes in various urban elements have occurred, subsequently resulting in land subsidence along subway lines. Compared to the construction period, monitoring and multi-factor analysis of subway deformation during the operational period is relatively limited. In this paper, we examine the issue through the novel lens of socio factor agglomeration. Both Sentinel-1, TerraSAR-X, ascending/descending LuTan-1 images and a Block PS-InSAR method were used to monitor 8-year ground subsidence for Kemulang station on Guangzhou Metro Line 6. Compared with the leveling measurements, the root mean square error (RMSE) of the InSAR results was 2.24 mm. Furthermore, social agglomeration effects such as population concentration, property clustering, commercial aggregation and the intensification of resource consumption were considered to analyze the main reason of ground subsidence, the synergistic process of multiple factors and the mechanism of accelerated subsidence phenomenon. We can find from the results that the fundamental cause of the large-scale land subsidence along the subway line is groundwater over-extraction triggered by population agglomeration, coupled with the response of adverse geological formations. Groundwater over-extraction has caused irreversible damage to the local strata. The research shows that the social agglomeration effect will cause more complex disturbance to the subway and lead to more continuous ground subsidence and more covert safety threat for subway operation, which should not be ignored. Full article