Subjects -> MINES AND MINING INDUSTRY (Total: 82 journals)
 Showing 1 - 42 of 42 Journals sorted by number of followers Stainless Steel World       (Followers: 17) Journal of Metamorphic Geology       (Followers: 15) Journal of Applied Geophysics       (Followers: 15) International Journal of Hospitality & Tourism Administration       (Followers: 14) European Journal of Mineralogy       (Followers: 12) Journal of Geology and Mining Research       (Followers: 11) Contributions to Mineralogy and Petrology       (Followers: 11) Mineral Processing and Extractive Metallurgy : Transactions of the Institutions of Mining and Metallurgy       (Followers: 11) Minerals Engineering       (Followers: 9) Transactions of Nonferrous Metals Society of China       (Followers: 9) Lithos       (Followers: 9) International Journal of Minerals, Metallurgy, and Materials       (Followers: 9) Natural Resources Research       (Followers: 8) Journal of Human Resources in Hospitality & Tourism       (Followers: 8) Geotechnical and Geological Engineering       (Followers: 8) Clay Minerals       (Followers: 8) Rock Mechanics and Rock Engineering       (Followers: 7) International Journal of Rock Mechanics and Mining Sciences       (Followers: 6) International Journal of Mining Engineering and Mineral Processing       (Followers: 5) Journal of Quality Assurance in Hospitality & Tourism       (Followers: 5) Canadian Mineralogist       (Followers: 5) Mine Water and the Environment       (Followers: 5) International Journal of Mining and Mineral Engineering       (Followers: 5) Journal of the Southern African Institute of Mining and Metallurgy       (Followers: 5) Mining Engineering       (Followers: 5) Resources Policy       (Followers: 4) Reviews in Mineralogy and Geochemistry       (Followers: 4) International Journal of Mining Science and Technology       (Followers: 4) Mineral Processing and Extractive Metallurgy Review       (Followers: 4) Applied Earth Science : Transactions of the Institutions of Mining and Metallurgy       (Followers: 4) International Journal of Mining, Reclamation and Environment       (Followers: 4) Physics and Chemistry of Minerals       (Followers: 4) Mineralium Deposita       (Followers: 4) Journal of Convention & Event Tourism       (Followers: 4) Journal of Sustainable Mining       (Followers: 3) Mining Journal       (Followers: 3) Ghana Mining Journal       (Followers: 3) International Journal of Coal Geology       (Followers: 3) Lithology and Mineral Resources       (Followers: 3) Geology of Ore Deposits       (Followers: 3) Journal of Materials Research and Technology       (Followers: 2) Rocks & Minerals       (Followers: 2) BHM Berg- und Hüttenmännische Monatshefte       (Followers: 2) Environmental Geochemistry and Health       (Followers: 2) International Journal of Coal Science & Technology       (Followers: 2) Archives of Mining Sciences       (Followers: 2) Mining Report       (Followers: 2) Extractive Industries and Society       (Followers: 2) Mineralogy and Petrology       (Followers: 2) Mining Technology : Transactions of the Institutions of Mining and Metallurgy       (Followers: 2) Mineralogia       (Followers: 2) Geomaterials       (Followers: 2) Journal of Mining Science       (Followers: 2) International Journal of Coal Preparation and Utilization       (Followers: 2) Journal of Central South University       (Followers: 1) Journal of Analytical and Numerical Methods in Mining Engineering       (Followers: 1) Neues Jahrbuch für Mineralogie - Abhandlungen       (Followers: 1) Rangeland Journal       (Followers: 1) Gems & Gemology       (Followers: 1) Mineralogical Magazine       (Followers: 1) CIM Journal Natural Resources & Engineering Mining, Metallurgy & Exploration Podzemni Radovi Rudarsko-geološko-naftni Zbornik Journal of Mining Institute International Journal of Mining and Geo-Engineering Journal of China Coal Society Réalités industrielles Revista del Instituto de Investigación de la Facultad de Ingeniería Geológica, Minera, Metalurgica y Geográfica Mineral Economics Minerals Gold Bulletin Minerals & Energy - Raw Materials Report
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 Natural Resources ResearchJournal Prestige (SJR): 0.8 Citation Impact (citeScore): 3Number of Followers: 8      Hybrid journal (It can contain Open Access articles) ISSN (Print) 1573-8981 - ISSN (Online) 1520-7439 Published by Springer-Verlag  [2469 journals]
• Recognizing Multivariate Geochemical Anomalies Related to Mineralization
by Using Deep Unsupervised Graph Learning

Abstract: Abstract The spatial structure of geochemical patterns is influenced by various geological processes, one of which may be mineralization. Thus, analysis of spatial geochemical patterns facilitates understanding of regional metallogenic mechanisms and recognition of geochemical anomalies related to mineralization. Convolutional neural networks (CNNs) used in previous studies to extract spatial features require regular data (e.g., raster maps) as input. Due to the complex and diverse geological environment, geochemical samples are inevitably irregularly distributed and even partially missing in many spaces, leading to the inapplicability of CNN-based methods for geochemical anomaly identification. Also, interpolation from samples to regular grids often introduces uncertainties. To address these problems, this study innovatively transformed geochemical sampled point data into graphs and introduced graph learning to extract the geochemical patterns. Correspondingly, a novel framework of geochemical identification named GAUGE (recognition of Geochemical Anomalies Using Graph lEarning) is proposed. To assess the performance of the proposed method, this study recognized anomalies related to Au deposits in the Longyan area, the Wuyishan polymetallic metallogenic belt, China. For a set of regularly distributed samples, GAUGE achieved an accuracy similar to that of a traditional convolution autoencoder. More importantly, GAUGE achieved an area under the curve of 0.833, outperforming one-class support vector machine, isolation forest, autoencoder, and deep autoencoder network for a set of irregularly distributed samples by 10.6, 5.2, 4.8, and 2.5%, respectively. By introducing graph learning into geochemical anomaly recognition, this study provides a new perspective of extracting both spatial structure and compositional relationships of multivariate geochemical patterns, which can be applied directly to irregularly distributed samples in irregularly shaped regions without the need for interpolation. Such an improvement greatly enhances the applicability of machine learning methods in geochemical anomaly recognition, providing support for mineral resources evaluation and exploration.
PubDate: 2022-06-24

• Influence of Different Coal Seam Gas Pressures and their Pulse
Characteristics on Coal-and-gas Outburst Impact Airflow

Abstract: Abstract Coal-and-gas outburst (CGO) is a major challenge to safe and efficient coal mining worldwide. As the primary energy source of CGO, coal seam gas determines the impact dynamic characteristics of the coal–gas two-phase flow. Therefore, the process of gas pressure evolution obtained from an experiment was used as the initial condition to study the influence of the initial gas pressure on the flow characteristics of the CGO airflow. The results show that, during CGO process, the gas pressure decreased either periodically (pulse) or in a continuous manner. The static pressure in the roadway showed the evolution of alternating positive–negative pressure transition. The range of the positive pressure zone and static pressure value decreased with increasing gas pressure. The velocity of the CGO airflow exhibited a rapid rise to the maximum followed by a decreasing trend with periodic fluctuations. The increase in the coal seam initial gas pressure led to an increase in peak velocity of the CGO airflow, distribution range, and duration of the high-speed airflow in the roadway. During CGO process, expansion and compression waves appeared alternately at a frequency increasing with gas pressure. The existence of the pulse feature increased the velocity of the CGO airflow in the entire roadway. However, the effect weakened gradually with increasing distance from the working surface. A rational arrangement of disaster prevention fences, refuge chambers, and other facilities based on the distribution characteristics of impact airflow velocity distribution in the roadway during the CGO process can help reduce the damage caused by CGO impact disasters.
PubDate: 2022-06-22

• Six Novel Hybrid Extreme Learning Machine–Swarm Intelligence
Optimization (ELM–SIO) Models for Predicting Backbreak in Open-Pit
Blasting

Abstract: Abstract Backbreak (BB) is one of the serious adverse blasting consequences in open-pit mines, because it frequently reduces economic benefits and seriously affects the safety of mines. Therefore, rapid and accurate prediction of BB is of great significance to mine blasting design and other production activities. For this purpose, six different swarm intelligence optimization (SIO) algorithms were proposed to optimize the extreme learning machine (ELM) model for BB prediction, i.e., ELM-based particle swarm optimization (ELM–PSO), ELM-based fruit fly optimization (ELM–FOA), ELM-based whale optimization algorithm (ELM–WOA), ELM-based lion swarm optimization (ELM–LOA), ELM-based seagull optimization algorithm (ELM–SOA) and ELM-based sparrow search algorithm (ELM–SSA). In total, 234 data records from blasting operations in the Sungun mine in Iran were used in this study, including six input parameters (special drilling, spacing, burden, hole length, stemming, powder factor) and one output parameter (i.e., BB). To evaluate the predictive performance of the different optimization models and initial models, six performance indicators including the root mean square error (RMSE), Pearson correlation coefficient (R), determination coefficient (R2), variance accounted for (VAF), mean absolute error (MAE) and sum of square error (SSE) were used to evaluate the models in the training and testing phases. The results show that the ELM–LSO was the best model to predict BB with RMSE of 0.1129 (R: 0.9991, R2: 0.9981, VAF: 99.8135%, MAE: 0.0706 and SSE: 2.0917) in the training phase and 0.2441 in the testing phase (R: 0.9949, R2: 0.9891, VAF: 98.9806%, MAE: 0.1669 and SSE: 4.1710). Hence, ELM techniques combined with SIO algorithms are an effective method to predict BB.
PubDate: 2022-06-20

• Paleodepositional and Hydrocarbon Source-Rock Characteristics of the
Sonari Succession (Paleocene), Barmer Basin, NW India: Implications from
Petrography and Geochemistry

Abstract: Abstract Lignite deposits, associated with Akli Formation (Paleocene), from the Sonari mine of Barmer Basin, Rajasthan, were investigated by applying organic petrography, palynofacies, and geochemistry in order to understand the origin, nature, and character of these lignite-bearing deposits and to assess their thermal maturation and hydrocarbon generation potentiality. The studied samples contained an abundance of huminite group of macerals (av. 54.0 vol.%) and relatively higher abundance of C27 and C29 n-alkane hydrocarbons. High carbon preference index (CPI: 5.03–9.44) and high terrigenous aquatic ratio (TAR: 5.09–20.01), together with the liptinite macerals (av. 10.3 vol.%), inform the prevailing contribution of higher plants. Besides, the significant amount of detrohuminites (av. 26.8 vol.%) and non-biostructure phytoclasts (av. 42.25%), along with hopanoids, denote a meaningful herbaceous plants input and/or high level of tissue destruction (bacterial activity). The terpenoid composition was mainly constituted by pentacyclic triterpenoids and A-ring-degraded angiosperm-derived compounds and diterpenoids. The inertinite contents (av. 22.3 vol.%) and the pristane/phytane (Pr/Ph) ratio imply the variation in the redox conditions during the accumulation. The petrographic indices revealed that the paleo-flora were accumulated in a limno-telmatic condition, with fluctuating groundwater level. Likewise, the palynofacies data displayed that the peat was deposited in dysoxic-suboxic settings under proximal condition. Subsequently, the incidence of dinoflagellate cysts in the studied samples suggests a marine intrusion. The considerable total of pyrite (up to 16.7 vol.%, comprising framboidal) suggests a coastal swamp condition (marginal marine). The thermal alteration index (TAI: av. 2.15), Tmax (av. 411 °C for lignite and 414 °C for associated shale) and the gross calorific values (av. 4601 cal/g) showed the immaturity of the studied samples. The lignites contained low to moderate ash yields (av. 12.57 wt.%) and moisture (av. 12.79 wt.%) contents, whereas the carbondaf (daf = dry ash-free basis) contents were high (av. 67.22 wt.%) and corroborated well with the inertinite group of macerals. The fuel ratio varied from 0.77 to 1.32. The volatile matter yielddaf (av. 51.09 wt.%), fixed carbondaf (av. 48.91 wt.%), and the oxygendaf (av. 22.16 wt.%) contents were moderately high. The total organic carbon contents (TOC: 1.17–54.84 wt.%, av. 24.78 wt.%) and hydrogen index values (HI: 32–361 mg HC/g rock) exhibit that the studied samples mostly have type III kerogen and show an excellent potentiality to generate gaseous hydrocarbons.
PubDate: 2022-06-15

• 3D Constrained Gravity Inversion and TEM, Seismic Reflection and
Drill-Hole Analysis for New Target Generation in the Neves–Corvo VMS
Mine Region, Iberian Pyrite Belt

Abstract: Abstract Located in the Iberian pyrite belt, the Neves–Corvo mine is a world-class massive sulfide deposit and the largest operating mine in Portugal with underground mining down to 1000 m depth focused on massive and stockwork Cu, Zn, Pb rich ores. Gravimetric data have had a leading role in the discovery of the seven known deposits, together with time-domain electromagnetic (TEM) ground data. In this work, we present the results of a 3D constrained gravity inversion carried out with legacy ground gravity data. The 3D gravity inversions were carried out using an updated density database containing approximately 142,000 measurements. A recently constructed 3D geological model based on reprocessed 2D seismic reflection, 3D seismic, TEM and updated geology from detailed surface mapping and drill-hole data, was used to constrain the inversions. The results show multiple high-density anomalies that may indicate the presence of mineralization at depth. These anomalies were therefore cross-checked with holes previously drilled. Approximately 97% of more than 1000 available surface drill-holes located on or at a distance of less than 200 m from the high-density anomalies intersected mineralization. However, gravity anomalies have been drilled in the past and particularly dense black shales or rhyolitic/gabbroic rocks have been intersected. To increase the success of future drilling, gravimetric anomalies have been correlated spatially with high-conductivity TEM zones and strong-amplitude seismic reflections, because igneous rocks usually present weak-to-moderate conductivity and a massive column of black shales presents a seismic signature quite different from that of mineralization. We concluded that some of these locations represent high-quality targets to consider following up with drilling and further exploration.
PubDate: 2022-06-15

• Experimental Study of Desorption and Seepage Characteristics of Single Gas
and CO2–CH4 Gas Mixture in Coal

Abstract: Abstract Understanding the desorption and seepage behaviors of CO2 gas and CO2–CH4 gas mixture in coal is important for CO2 geological sequestration and enhanced coalbed methane recovery. An experimental study of desorption and seepage in coal under the action of a single gas (CO2) and a gas mixture (50% CH4, 50% CO2) was conducted under the influence of the pore pressure and stress environment. The results indicated that the CO2 permeability of coal increased with increasing pore pressure and decreased with increasing σ1 and σ3. CO2 desorption increased with increasing pore pressure, and the Dubinin–Astakhov model suitably captured the CO2 desorption behavior. Under the same hydrostatic and pore pressure conditions, the seepage volume of CO2 was significantly larger than the desorption volume. Regarding the considered CO2–CH4 gas mixture, the seepage volume decreased exponentially as a function of time and the desorption volume increased exponentially over time. Regardless of seepage or desorption in the tests, the CH4 concentration in the CO2–CH4 gas mixture at the outlet was always higher than that of CO2, which is closely related to the gas pressure, microscopic composition of coal, and coal rank. An increase in coal rank could increase vitrinite reflectance, due to the higher affinity of CH4 for vitrinite, and due to the relatively low solubility of CO2 under low pressures, preferential CH4 desorption occurred. As the test proceeded, the concentration of desorbed or seeped CH4 decreased gradually, the concentration of CO2 continued to increase, and finally, the relative concentrations of these two gases equalized eventually.
PubDate: 2022-06-10

• Visual Interpretable Deep Learning Algorithm for Geochemical Anomaly
Recognition

Abstract: Abstract Deep learning algorithms (DLAs) have achieved better results than traditional methods in the field of multivariate geochemical anomaly recognition because of their strong ability to extract feature from nonlinear data. However, most of DLAs are black-box approaches because of the high nonlinearity characteristics of the hidden layer. In addition, the integration of domain knowledge into the DLAs to ensure physical consistency is a challenge for DLAs in geoscience. In this study, we adopted the adversarial autoencoder (AAE) algorithm for geochemical anomaly detection. The interpretability of the model is improved by visualizing features and integrating geological domain knowledge into the loss function of the AAE. The feature visualization method was used to display the changes of information in the model calculation process to further understand the inherent operation law and principle of the neural network. The penalty term was added to the optimized loss function, and the spatiotemporal and genetic relationships between felsic intrusions and mineralization were integrated into the AAE with the aim of improving the geological interpretability of the network. The added penalty item can guide the changes in the stage of data reconstruction and improve the understandability of the results of geologically constrained AAE. In addition, the effectiveness of injecting the concept of physical constraints into the AAE can be verified via feature visualization. A case study in the southern Jiangxi Province and its surrounding areas was performed to identify multivariate geochemical anomalies. The results obtained by the geologically constrained AAE demonstrated a strong spatial correlation with the outcrop of intrusions in the study area, and most of the known mineral deposits are located in or near the highly anomalous areas.
PubDate: 2022-06-08

• Developments in Quantitative Assessment and Modeling of Mineral Resource
Potential: An Overview

Abstract: Abstract The special issue entitled “Developments in Quantitative Assessment and Modeling of Mineral Resource Potential” is composed of 17 papers that cover a diverse range of approaches to mineral resource assessment, including mainly multivariate statistical analysis, fractal and multifractal modeling, geostatistical modeling, machine learning, mathematical morphology and 3D mineral exploration. This introductory article first provides an overview of the developments and existing methods in quantitative assessment of mineral resources. Then, brief introductions of each of the 17 papers are provided. These papers can be grouped into three themes: (1) multifractal theory for mineral resource assessment; (2) machine learning for mineral prospectivity mapping; and (3) GIS-based 3D modeling for mineral exploration. The 17 papers either proposed novel methods or demonstrated innovative applications of existing methods.
PubDate: 2022-06-03

• Interference Analysis of Methane Co-Production from Two Coal Seams in
Southern Qinshui Basin

Abstract: Abstract Gas co-production has been touted to be a cost-effective way to increase the recoverable coal-bed methane (CBM) resource in multiple coal seams. However, co-production in the southern Qinshui Basin has met with disappointing results due to interlayer interference. In this study, a reservoir model was established around one co-production well with high water production and low gas production; with respect to seven reservoir parameters, the interferences were analyzed quantitatively. The results show that, for a given aquifer communicated with the lower reservoir, it can not only restrain the output of water from itself but it can also reduce the effective water production from the upper reservoir, and thus, reservoir pressure cannot be reduced in both layers effectively. Moreover, the interference intensity, which is triggered by discrepancies in reservoir parameters between the two CBM systems, varies from strong to weak and is due to reservoir pressure, aquifer thickness and permeability, coal seam thickness, fracturing permeability, in situ permeability, and gas content. Finally, when progressive drainage from either layer is considered, drainage from the lower seam first is more advantageous than the other; besides, the placement of co-production well in the well-pattern was verified to be an effective approach to improve gas recovery. This study can provide a reference for the development of CBM resources in the study area and as basis for the theoretical study of gas co-production from coal measures.
PubDate: 2022-06-01

• Nonlinear Characteristics of Granite After High-Temperature Treatment
Captured by Digital Image Correlation and Acoustic Emission Technology

Abstract: Abstract In order to understand the nonlinear characteristics of granite after exposure to high temperature, fracture tests were carried out. The fracture process of granite was monitored by combining digital image correlation (DIC) method and acoustic emission (AE) technology, and the changes of microcracks in granite after high-temperature treatment were observed. The apparent fracture toughness of granite decreased significantly after high-temperature treatment and showed obvious size effect, which is consistent with the size effect law of Bažant. The combined observations by DIC and AE showed that the crack of granite at room temperature started to grow significantly only when it approached the failure load, and the fracture process was rapid. However, the crack growth was observed clearly in the early stage of loading for the granite subjected to high temperature, and the process was slow and persistent. After granite was heated at high temperature, the critical crack tip opening displacement (CTODc), AE b value, effective fracture process zone length, and many other indicators all increased significantly. This indicates that the fracture types of granite changed from brittle to ductile. The microscopic results showed that the granite microcracks developed after high-temperature treatment, the number of microcracks increased significantly, and the porosity and fractal dimension increased. Finally, the relationship between work of cohesion and cumulative AE counts was estimated based on the fictitious crack model. The results showed that there was a significant linear correlation between the two variables, regardless of room temperature granite or heat-treated granite. The work of cohesion can characterize the activity of microcracks in the fracture process zone and it can be quantified by AE technology. This provides a new way to study crack propagation by AE technology.
PubDate: 2022-06-01

• A Geologically Constrained Variational Autoencoder for Mineral
Prospectivity Mapping

Abstract: Abstract Deep learning algorithms (DLAs) are becoming popular tools for mineral prospectivity mapping. However, purely data-driven DLAs frequently ignore expert and domain knowledge, imposing difficulty in interpretability from a geological perspective. The efficient integration of geological knowledge into DLAs remains challenging in geosciences. In this study, a geologically constrained variational autoencoder (VAE) was proposed to map prospectivity for gold mineralization in the Baguio District of the Philippines. A spatial nonlinear correlation between an ore-forming controlling feature and locations of mineral deposits was built as part of the loss function for constructing a geologically constrained VAE. A comparative study of a geologically constrained and a traditional VAE demonstrated that the former can enhance the probabilities in areas with high potential for locating mineralization and increase the interpretability of the obtained results.
PubDate: 2022-06-01

• In situ Stress–Coal Structure Relationship and Its Influence on
Hydraulic Fracturing: A Case Study in Zhengzhuang Area in Qinshui Basin,
China

Abstract: Abstract In situ stress (comprised of minimum horizontal principal stress (σh), maximum horizontal principal stress (σH) and vertical principal stress (σv)) and coal structure are the key control factors of hydraulic fracturing. In this work, 80 coalbed methane wells data were selected to explore the in situ stress–coal structure relationship and its influence on hydraulic fracturing. The results showed that the coal structure identification method based on principal components analysis is an effective tool in simplifying logging data and improving the recognition accuracy. Fracturing pressure (Pf) and σH are correlated positively with the content of undeformed coal, correlated negatively with the content of cataclastic coal and have a weaker relationship with the content of granulated coal. The coal seams in the southwest of the study area, which belong to I stress field (i.e., low vertical stress anisotropy (VSAI) and high horizontal stress anisotropy (HSAI)) are composed mainly of undeformed coal, and easily form planar fractures with long major fracture length and shorter major fracture height. The coal seams in the northwest–southeast study area, which belongs to II stress field (high VSAI and low HSAI), are composed mainly of cataclastic coal, and easily form complex plane fractures with second minister major fracture length and long major fracture height. The coal seams in the northeast study area, which belongs to III stress field (low VSAI and high HSAI), are composed mainly of granulated coal, and easily form complex fractures with shorter major fracture length and shorter major fracture height.
PubDate: 2022-06-01

• Prediction of Critical Desorption Pressure of Coalbed Methane in
Multi-coal Seams Reservoir of Medium and High Coal Rank: A Case Study of
Eastern Yunnan and Western Guizhou, China

Abstract: Abstract In the process of multiseam combined drainage, the critical desorption pressure (Pcd) is the basic measurement index for determining whether a multigas-bearing system can be combined with drainage, and it is the basic index for identifying effectively the contributions of productive strata. In actual exploration and development processes, the Pcd is constrained by geological factors, engineering factors and economic factors, and the Pcd of some key coal seams cannot be determined effectively, which restricts the efficient development and utilization of coalbed methane. Accurate prediction of the Pcd of multiple coal seams under formation conditions has become a key requirement. In this study, medium-rank and high-rank coal samples were collected from the main synclines in Eastern Yunnan and Western Guizhou. By introducing the fractal dimension using nuclear magnetic resonance and the Pearson–Spearman correlation coefficient, the influences of coal metamorphism, pore structure, coal quality, temperature (T), and others on coal adsorption capacity were revealed. The results showed that, affected by the hydrocarbon generation and evolutionary processes of coal, fractal dimensions of adsorption pore (D3) and seepage pore (D4), the ratio of vitrinite to inertinite (V/I), the Langmuir volume (VL) and Langmuir pressure (PL) showed segmentation as the degree of metamorphism increased significantly. Bounded by random reflectance Rr = 1.30%, before Rr = 1.30%, with increase in metamorphic grade, VL and Rr showed “U” type change due to the change of molecular structure, maceral content, and structure of seepage pore, and then the evolution of hydrocarbon generation was weakened mainly by the influence of coal and rock components, showing linear change. The slopes of PL and Rr were larger before Rr = 1.30% than after Rr = 1.30%. The variation in PL with metamorphic degree was controlled mainly by the seepage capacity of coal rock, followed by the macerals of coal rock. Based on these results, the Levenberg–Marquardt algorithm was used with Rr and T as independent variables, VL and PL as dependent variables, and the R2 as the judgment value. A piecewise equation for calculating adsorption parameters with a high-fitting degree was obtained. Combined with the Langmuir equation, the prediction equation of Pcd can be calculated under the conditions of Rr and T and the measured gas content of known key coal seams. The correlation between the prediction equation and the measured parameters was high, and the identification template of Pcd of medium–high-rank coal in the study area was given. The new calculation method is more convenient for obtaining parameters and can be applied effectively to coal seams without the need to perform isothermal adsorption tests.
PubDate: 2022-06-01

• Energy Evolution Characteristics of Coal–Rock Composite Bodies Based

Abstract: Abstract Taking coal mine dynamic disaster as research background in this paper, five samples of coal–rock composite bodies (CRCBs) with different coal thicknesses were designed, and the uniaxial loading tests were carried out on them by using the MTS uniaxial loading instrument and the DS5 acoustic emission instrument, and the damage process of the samples were analyzed from the perspective of energy conversion. The results were as follows. With increase in coal thickness of CRCBs, the uniaxial compressive strength and elastic modulus of CRCBs decreased while the peak strain increased, and the overall bearing capacity of the samples decreased, resulting in a decreasing trend of AE peak ringing count and peak energy. According to the theory of conservation of energy, it was found that the dissipated energy of the samples in the compaction stage accounted for a large proportion, and the elastic stage was dominated by the accumulation of elastic energy. After the plastic stage, the energy conversion rate in the samples accelerated, and the dissipated energy increased rapidly, leading to the gradual failure of the samples. The energy storage limit of samples decreased logarithmically together with increase in coal thickness. Finally, it was found that coal was the main energy storage structure of the whole coal and rock composite system by analyzing the energy accumulation mechanism of coal and rock composite structure in practical engineering. Therefore, to prevent and control underground dynamic disaster in practical engineering, the internal energy storage of a coal seam should be released and the clamping effect of roof and floor on coal body should be weakened. The achievements of this study will be a theoretical guidance for preventing and controlling dynamics.
PubDate: 2022-06-01

• Combined Geophysical–Geological Investigation for 3D Geological
Modeling: Case of the Jeffara Reservoir Systems, Medenine Basin, SE
Tunisia

Abstract: Abstract This work presents a comprehensive study based on geophysical and geological data to improve the characterization of regional multilayered reservoir systems in a complex geological setting. A combined approach, involving (a) data integration, (b) joint seismic-geological investigations, (c) mapping of reservoir surfaces and (d) 3D geological modeling, is proposed to characterize the “Jeffara of Medenine Basin” reservoir systems and to enhance the understanding of their functioning. The 3D geological modeling was performed using a 3D interpolation procedure based on potential field theory and integrating both observed data and knowledge-driven understanding. It was implemented using co-kriging techniques, involving two main variables: the “geological contact” and the “orientation data.” The interpolation was constrained by geological knowledge and hypotheses inferred through the stratigraphic pattern of the reservoir formations to be modeled and the faults affecting their continuity. A reliable 3D geological modeling was constructed, describing nine regional reservoir formations and associated structural features (folds and crosscutting faults). A comprehensive analysis of the outputs of the 3D geological model combined with a careful correlation of the potentiometric gradient/lithologic properties insured a better description of the reservoirs compartmentalization and connectivity and helped to construct the conceptual model of the fluid flow path at regional and local scales. All modeling results provide a direct foundation for subsequent numerical flow simulation and hydrodynamic modeling.
PubDate: 2022-04-30

• Simulated Block Variance for 3D Drillhole Infill

Abstract: Abstract Drillhole infill has an important role in the mining industry, especially when its aim is to enhance the assessment of variance representativeness of a mineralized rock or any other measured characteristics. Some infill optimization methods propose the use of kriging variance, which is feasible when the goal is to search for sub-sampled regions, but those methods may fail in more complex situations given that a fundamental limitation of kriging variance is to only depend on neighboring samples nearby the estimate location. This paper proposes a method to infer the best location for new drillholes through optimization using as objective function the sum of simulated block variance (SBV), which does not have the same limitation as to the kriging variance. The SBV is reached by stochastic simulation (sequential Gaussian simulation) to compute the variance of each block along with the grid model, and the values are summed to attain the objective function. The objective function minimization is computed by three different methods of search: random search, simulated annealing, and particle swarm optimization. Due to smaller objective function values when applied to a synthetic deposit, simulated annealing with fast cooling schedule algorithm performed better than the others. Further tests led to the conclusion that simulated annealing had more representation of the population. These methods were also applied to a real sampled site, the Capanema Mine, and the simulated annealing with fast cooling also produced the best results with regard to representativeness.
PubDate: 2022-04-25

• A Novel Spectral Index for Identifying Ferronickel (Fe–Ni) Laterites
from Sentinel 2 Satellite Data

Abstract: Abstract Field geological mapping is the initial step of preliminary research in mining. However, in the last decades, the rapid progress of remote sensing data processing and its use for reconnaissance of geological outcrops for the purpose of locating possible mining sites gained increasing attention due to the significant time and cost savings. In this study, a new methodology, focused on mapping ferronickel (Fe–Ni) laterite deposits by using Sentinel-2 satellite data, is introduced. It describes a novel spectral index (called laterite spectral index (LSI)) that enhances laterite surface outcrops. To the best of our knowledge, LSI is the first spectral index tailored for this task, concerning minerals that are simultaneously rich in Fe and Ni. The LSI was applied on a continuum removed image by taking advantage of the spectral features present in two specific spectral areas of 490–560 nm and 842–945 nm. The entire methodology was tested and validated on four different excavation sites in eastern Central Greece based on known drillholes. In all excavation sites, the proposed LSI compared favorably with other relative spectral indices proposed in the literature for the detection of Fe-bearing minerals or Fe-oxides.
PubDate: 2022-04-23

• A New Long-Term Photovoltaic Power Forecasting Model Based on Stacking
Generalization Methodology

Abstract: Abstract In recent times, solar energy has become a highly promising source of energy and one of the most regular types of sustainable energy. Forecasting the availability of solar energy has become a concern of many studies because of the intermittent characteristics of solar power. This study proposes a new stacked generalization methodology for predicting long-term photovoltaic power. In the proposed methodology, the base learners used consisted of group method of data handling (GMDH), least squares support vector machine (LSSVM), emotional neural network (ENN), and radial basis function neural network (RBFNN). The backpropagation neural network (BPNN) served as the meta-learner in the stacked approach. The proposed stacked generalization method showed superiority over the four standalone state-of-the-art methods (GMDH, LSSVM, ENN, and RBFNN) when tested with real data using performance indicators such as Bayesian information criteria (BIC), percent mean average relative error (PMARE), Legates and McCabe index (LM), mean absolute error, and root mean square error. The stacked model had the lowest BIC and PMARE values of 10,417.54 and 0.3617% for testing results. It also had the highest LM score of 0.996711 as compared with the benchmark standalone models, confirming its strength in forecasting photovoltaic power.
PubDate: 2022-04-18

• Isotope Rollover of Gaseous Hydrocarbons Induced by Water Pressure in
Laboratory Pyrolysis Experiments: Insights into the Influence of Pressure
on Carbon Kinetic Isotope Effects During Methane Generation

Abstract: Abstract Stable carbon isotope (δ13C) rollover of natural gas has attracted recent attention due to its association with highly productive shale gas. However, the mechanistic causes of δ13C rollover are not fully understood. In this investigation, pyrolysis was carried out using calcareous shale and carbonaceous mudstone under high water pressure (WP) (i.e., 5 × 106–1.2 × 108 Pa). It was found that WP induced the isotope rollover of gaseous hydrocarbons. For both sapropelic and humic organic matter, the δ13C rollover of CH4 (methane), C2H6 (ethane), and C3H8 (propane) occurred when the WP ranged from 3.25 × 107 to 1.2 × 108 Pa. This result can be explained by high WP conditions retarding oil cracking, and enhancing hydrocarbon expulsion and oil generation. The promotion of oil generation resulted in increasing trends of vitrinite reflectance, and inhibition of gaseous hydrocarbons generation resulted in decrease in δ13C1 values with increase in WP. Good functions were found between water pressure and the calculated carbon kinetic isotope effect (KIE) for 12CH4 and 13CH4 produced from sapropelic and humic organic matter. Further calculations showed that the increments of activation volume ( $${\Delta V}_{{12}_{{\mathrm{CH}}_{4}}}^{\ddagger }$$ – $${\Delta V}_{{13}_{{\mathrm{CH}}_{4}}}^{\ddagger }$$ ) were linearly correlated with the kinetic isotope effect of methane ( $$\Delta \mathrm{KIE}$$ ) produced from sapropelic and humic organic matter, indicating that WP may affect the KIE of 12CH4 and 13CH4 by changing the $$\Delta {V}^{\ddagger }$$ of 12CH4 and 13CH4. Overall, these findings suggest that WP affects the carbon isotope fractionation of gaseous hydrocarbons due to the different thermodynamic properties of 12CH4 and 13CH4.
PubDate: 2022-04-15
DOI: 10.1007/s11053-022-10052-9

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