As the depth of coal mining increases, concealed fires from residual-coal spontaneous combustion in goaf pose a significant threat to underground mining safety. Preferred index gases are used to predict temperature of coal spontaneous combustion (CSC), providing ideas for an early warning system for concealed fires. Here, a new mathematical method of slope grey relation analysis (SGRA) is established

The global imperative for a low-carbon energy transition is prompting significant shifts in the coal industry, driving the need to identify and analyze emerging research hot spots in coal-related research. Traditional methods that rely on domain knowledge to identify hot spots may have limitations, such as time costs and incomplete coverage. Moreover, a comprehensive analysis of coal-related research

The primary objective of this study was to evaluate the effectiveness of three machine learning techniques in the confidence categorization of mineral resources within a copper deposit in Peru: extreme gradient boosting (XGBoost), random forest (RF), and deep neural network (DNN). To achieve this, geostatistical and geometric datasets were employed to categorize mineral resources into measured, indicated

Hot dry rock undergoes cyclic temperature variation during an enhanced geothermal system (EGS) operation, resulting in variations in reservoir rock’s transport properties and subsequently influencing the heat extraction efficiency of EGS. Therefore, the subject of this study was to systematically investigate the effect of cyclic heat treatment on the transport properties of granite, commonly employed

The efficient characterization of heterogeneous carbonate reservoirs remains a significant challenge due to complex depositional environments and diagenetic alterations. While traditional methods like electrofacies analysis and clustering techniques offer inherent benefits, they often yield incomplete or conflicting results if used solely. This paper suggests an integrated study using petrophysical

Coal deformation-induced by adsorption/desorption is dynamic and anisotropic, influenced by various factors, such as pressure, temperature, and gas type. This paper investigates the dynamic deformation of coal during the adsorption–desorption process and analyzes the anisotropic and hysteretic characteristics. Results show that maximum deformation is reduced by approximately half with every 10 °C increase

The deterioration of coal strength caused by geological conditions of high gas in deep mines and disturbance from mining operations is one of the elements that influence the incidence of dynamic disasters like gas outbursts and rock bursts. To study how gas pressure and cyclic loads interact to determine the mechanisms and phenomena of coal dynamics, the split Hopkinson pressure bar apparatus was used

Optimizing hydrocarbon recovery in the Illizi Basin requires precise reservoir characterization. Traditional methods face challenges in efficiently handling large datasets from multiple wells. This paper employs principal components analysis (PCA) to evaluate the petrophysical properties of the reservoir intervals (IV-3, IV-1b, IV-1a) using wells P8, P4, and P6, situated in the northern, center, and

Mineral prospectivity mapping (MPM) can be deemed a binary classification task, with classifiers trained and validated on labels indicating the presence or absence of the targeted mineralized zones. Using economically viable mineral deposits as positive labels could, in theory, yield prospectivity models with geometallurgical reliability, thereby aiding land management and decision-making. The inherent

Machine learning (ML) is increasingly being used in geosciences for complex classification tasks. Mica minerals are commonly found in deposits of precious metals, rare metals, and rare earth elements, including tungsten, tin, lithium, and copper, among others. These minerals can provide insights into the formation environment and age of various deposits. While ML has been applied mainly for optical

Shale gas reserves represent a significant source of natural gas, but unlocking their full potential depends on effective hydraulic fracturing. This research investigates the application of machine learning (ML) techniques to predict fracability index (FI), offering a faster and more cost-effective alternative to traditional experimental methods. Focusing on the Upper Ordovician Wufeng to Lower Silurian

Handling the micro-occurrence mechanisms of fluids is vital for the exploitation of shale gas. As the research hotspots shift towards the deep strata, the gas storage and transport capacity in shale relies to a great extent on the nanostructure. In this work, the grand canonical Monte Carlo and molecular dynamics simulations were performed to systematically study the adsorption and diffusion behaviors

Fine-grained carbonate-siliciclastic mixed sequences, formed in saline lacustrine settings, constitute substantial unconventional and conventional hydrocarbon resources. Clarifying the key controlling factors of hydrocarbon accumulation is pivotal for predicting potential resources and enhancing exploration strategies. However, there is still a lack of research on how hydrocarbons accumulate in fine-grained

The Eocene Cave Peak intrusive complex in western Texas was the site of a major exploration program in the late 1960s, principally for Mo in a porphyry mineral system. Although neither Texas nor the US federal government have protocols for the archiving of data and materials resulting from private sector exploration programs, much of the Cave Peak exploration results has been preserved through a fortuitous

Lithology classification is a crucial task in geological exploration, playing a significant role in oil and gas exploration as well as mineral resource development. However, traditional supervised learning methods rely heavily on large amounts of labeled data, and obtaining labeled well-logging data is both costly and time-consuming, significantly limiting their widespread application. To address this

Injecting mixed gas (CO2/N2) into coal seams is an effective method to realize a win-win situation of CO2 sequestration and enhanced coalbed methane (ECBM) recovery. The ratio of gas mixtures is a critical factor in pore structure evolution. In this study, we used high-pressure saturated systems to examine the effects of different gas mixture ratios on anthracite. The pore structure and mineral content

Lithium-rich (Li-rich) sedimentary brine has emerged as a valuable unconventional resource, driven by the blooming global market, advancements in direct extraction technologies, and a lower environmental impact compared to traditional mining methods. However, resource delineation and estimation remain challenging due to inefficient field sampling and unreliable correlations between Li concentration

The occurrence mechanisms of shale oil in saline lacustrine basins are complex, and accurately quantifying the state of occurrence and assessing mobility present significant challenges, impeding deeper insights into the enrichment processes of shale oil. To comprehensively elucidate the occurrence mechanisms of continental saline lacustrine basin shale oil, and to clearly define the advantageous lithofacies

The mechanical properties of continuous rock fiber (CRF), particularly its elastic modulus and tensile strength, are essential requirements for the ever-increasing applications of this material. Studies on CRF have primarily focused on its application in fiber-reinforced composites, with much less emphasis on the analysis of the fiber structure–property relationship. This review summarizes and discusses

This study investigated the effect of varying strain rates on the dynamic behavior and damage mechanisms in coal. We employed the split Hopkinson pressure bar to conduct dynamic unconfined compression tests on coal samples. This involved obtaining the coal samples dynamic mechanical properties and failure characteristics. We performed analyses on the extent of impact damage before and after testing

Precise characterization of reservoir rocks, particularly regarding porous media properties such as porosity, pore throat permeability, and fluid saturation, is essential for efficient hydrocarbon extraction and management. Traditionally, these properties have been assessed through core sampling and well log analysis. However, the data obtained from point-by-point measurements using these methods are

The process of dry–wet cycling in coal mining areas exerts a more pronounced degrading effect on coal pores compared to prolonged water immersion, and it enhances the tendency of coal spontaneous combustion. To investigate the fractal characteristics of coal during dry–wet cycling and the evolutionary changes in its overall pore structure, various pore properties were analyzed using scanning electron

Efficient development of coalbed methane is crucial for optimizing energy structure, ensuring energy security, and achieving carbon emission reduction targets. This study investigated the combined influence of wettability and pore structure on gas and water production in coal seams. Coal samples from three regions were characterized using low-temperature CO2 and N2 adsorption, high-pressure mercury

Accurate forecasting of water quality is pivotal for compelling pollution control and enhanced water management practices. This study predicted total dissolved solids in groundwater samples from West Bengal, India, using data sourced from the Central Pollution Control Board for the span 2020–2022. The parameters include temperature, pH, conductivity, biological oxygen demand, nitrate-N + nitrite-N

One of the most common catastrophes that occur during the coal mining process is the coal-and-gas outburst. However, due to the complexity of this phenomenon, there are many variables affect it, and the degree of synergistic coupling of various factors is deep, and so the mechanism of its occurrence cannot be fully grasped so far. Existing research mainly focused on the temperature variation law of

Reservoir sensitivities play a crucial role in affecting the production efficiency of coalbed methane, relating to adsorption/desorption dynamics, pore–fracture interactions, and pressure characteristics within the reservoir. This study examined changes in permeability sensitivity within a heterogeneous coal structure reservoir by continuously sampling seven coal sections from roof to floor. The samples

Spatial models are fundamental across the mineral value chain, forming the basis for exploration and extraction. Geodata science and increasingly bigger data permit alternatives to traditional mineral resource estimation methods, particularly in spatial data interpolation. Interpolation has been formulated as a machine learning (ML) task, providing new capabilities, such as automated deployment and

Exploration for graphite in Canada is of economic, strategic and governance priority. In this study, we aimed to develop a reliable prospectivity map for graphite in Canada. Our approach mitigated multiple sources of workflow-induced uncertainty by propagating uncertainty due to the selection of negative labels, machine learning algorithms, feature space dimensionality, and hyperparameter tuning metrics

A pivotal aspect in the evaluation of mining projects is the classification of mineral resources, which directly influences the definition of mineral reserves and significantly impacts mine planning and operational stages. However, the current classification methodologies often need specificity regarding the methods and parameters employed and heavily rely on the qualified/competent person’s judgment

The surface movement law induced by continuous mining across multiple working faces is distinct compared to that of a single working face. It is essential to understand and analyze this law to ensure the safety of coal mining operations. This study employed a research method that integrates numerical simulation and theoretical analysis to define, for the first time, the concepts of the repeated mining

Gas hydrate is anticipated to serve as a viable substitute for traditional fossil fuels in the near future. Unfortunately, some geomechanical issues may arise during its development, threatening its efficient development and the marine ecology. It is regrettable that research in this area remains inadequate. In the present work, a coupled mathematical model was used to analyze sediment stability during

The influence of diagenesis on the heterogeneity of pore structures in tight sandstone reservoirs is essential for accurately assessing hydrocarbon potential. This study employed polarized light microscopy and X-ray diffraction to characterize lithofacies in tight sandstones from the Jurassic Badaowan Formation in the Mo-Yong region of the central Junggar Basin. Additionally, the study integrated low-temperature

Several coals and coal by-products around the world have been identified as important alternative sources for rare earth elements and yttrium (REY) recovery, as these are considered crucial. However, many pre-existing coal chemical data and coal samples do not contain REY data, and in many cases, it is not possible to re-determine the REY concentrations in these samples. In this investigation, 528

In lithium mineral exploration, rapid and accurate identification of lithium-related rock lithologies is critical. Traditional manual methods are time-consuming and have limited accuracy, whereas some deep learning models, despite offering high precision, suffer from high computational complexity and low inference speeds, limiting their practical application. To address these issues, this study proposes

The grade of iron content in ore was measured using X-ray fluorescence, and three iron ore grades (i.e., 28%, 34%, and 40%) were selected to prepare disk specimens. The Brazilian splitting test was performed, and acoustic emission and digital image correlation methods were used to capture the surface strain distribution and crack propagation behavior. The microscopic morphology of the fracture surfaces

Integrated workflows for mineral resource estimation from exploration to mining must be able to process typical geodata (e.g., borehole data), perform data engineering (e.g., geodomaining), and spatial modeling (e.g., block modeling). Several methods exist, however they can only handle individual subtasks, and are either semi or fully automatable. Thus, an integrated workflow has not been established

This study aimed to predict the lithium resource potential in the Jiulong region of western Sichuan using a spectral residual attention convolutional neural network (SRACN) model, which integrates hyperspectral imagery from the GF-5B satellite with spectral measurement data from field rock core samples. By incorporating residual connections and a spectral attention mechanism, the SRACN model efficiently

Groundwater is the primary source of drinking water in the world, but its contamination and reduction cause environmental problems. Traditional hydraulic and numerical models for assessing groundwater and land subsidence are time-consuming and expensive. Thus, this study used the long short-term memory (LSTM) neural network to predict groundwater level and employed linear regression analysis and the

Groundwater is a vital renewable natural resource that largely supports the agriculture sector, especially in semi-arid climate of hard rock. However, the over-exploitation and inadequate recharge of groundwater in crystalline granitic terrains have depleted the shallow aquifer systems constraining the groundwater to be sporadically distributed in deep fractures. Therefore, tracing bedrock fractures

In the context of mining exploration, local earthquake tomography serves as a valuable complementary tool, applicable across varying scales from greenfield to brownfield projects. Nevertheless, interpreting body-wave velocity anomalies within tomographies poses a significant challenge, which largely depends on the expertise of the analyst and the availability of information. Addressing this challenge

As mining depth increases, the temperature of coal seams increases gradually, which increases the risk of spontaneous coal combustion in goaf areas. This paper uses a programmed temperature rise experiment to analyze the oxidation combustion characteristics of high ground temperature coal and calculates the oxidation kinetic parameters and limit characteristic parameters. The results show that, above

The pore–fracture structure of deep coal deposits is highly important for the potential evaluation, investigation, and utilization of deep coalbed methane resources. This study used methods such as low-pressure CO2 adsorption, low-temperature N2 adsorption, high-pressure mercury intrusion porosimetry, scanning electron microscopy, and optical microscopy to describe the pore–fracture structure of deep

Witwatersrand-type gold deposits in South Africa are generally amenable to cyanidation due to their free-milling nature. However, the relatively easy-to-process gold ores have been mostly depleted, and the remaining ores are of low-grade combined with semi-refractory properties. Here, we use an integrated approach to understand the mineralogical and textural characteristics of the Witwatersrand-type

Accurate assessment of in situ fluid occurrence and content in complex shale reservoirs is crucial for effective resource evaluation and shale oil extraction. Laboratory tests on placed samples often lead to misestimations due to movable fluid loss. Low-field nuclear magnetic resonance (NMR) technology, which eliminates the need to crush cores for pyrolysis experiments, is emerging as a vital tool

Lithological mapping is an effective tool for geological surveys and mineral exploration. However, it faces challenges in identifying complex rock types and improving classification accuracy. We mapped lithological units in the Karamaili ophiolite-mélange belt of Xinjiang using integrated machine learning algorithms, including artificial neural network (ANN), Mahalanobis distance (MD), support vector

Geophysical exploration for disseminated chromite deposits has always been challenging because the ore body does not exhibit significant geophysical anomalies. An understanding of petrophysical rock parameters can make the interpretation of geophysical data more accurate. The spectral induced polarization (SIP) method emerged as a promising technique to understand the electrical and petrophysical properties

The Pokiok Plutonic Suite (PPS) lies within the southern segment of New Brunswick's Central Plutonic Belt, Canada. The PPS exhibits significant Devonian intrusive events, including four main phases, namely the Hartfield Tonalite, the Hawkshaw Granite, the Skiff Lake Granite, and the Allandale Granite, hosting notable intrusion-related W–Mo–Sb–Au deposits. This study aimed to identify potential exploration

Coalbed methane primarily exists as adsorbed gas within the microscopic pores and fractures of coal. However, the complex pore structure of deep coal seams and its quantitative relationship with methane adsorption capacity remain unclear. This study investigated nine samples from a coal seam in the Ningwu Basin, representing different burial depths, including five middle-shallow and four deep burials

Predicting flyrock is key to safety and efficiency in open pit mining. In this study, we developed and tested four hybrid models utilizing an adaptive neuro–fuzzy inference system (ANFIS) integrated with metaheuristic optimization techniques: Lévy-enhanced Jaya (ANFIS–LJ), bat algorithm (ANFIS–BA), firefly algorithm (ANFIS–FA) and social spider optimization (ANFIS–SSO). Remarkably, the Lévy technique

The overmature Lower Cambrian shale in southern China typically exhibits underdeveloped organic matter (OM) pores, with low porosity, and it is commonly believed that both of them have a causal linkage. However, there remains a lack of in-depth study on the characteristics of OM pores and their controlling factors for this shale. In this study, a suite of Lower Cambrian shale samples was taken from

The discovery of new lithium resources is essential because lithium plays a vital role in the manufacturing of green technology. Along with brines and volcano–sedimentary deposits, approximately a one-third share of global lithium resources is associated with lithium-cesium-tantalum (LCT) pegmatites, with Canada hosting numerous examples. This research applied generative adversarial networks, natural

In geochemical exploration, a small number of positive samples and a large number of unlabeled samples can be defined according to the geochemical exploration data and the mineral deposits (occurrences) found in the exploration area. The positive samples usually comprise multiple types of mineral deposits (occurrences) while the unlabeled samples usually comprise a large number of background samples

The goaf residual coal is more susceptible to oxidation after long-term soaking that raises the spontaneous combustion risk level. This paper investigates the oxidation thermodynamic mechanism and the active functional group proliferation trend in soaked coal. A coal macromolecular model C217H171O44N3S2 is constructed to evaluate the oxygen adsorption effectiveness via molecular dynamics simulation

Machine learning is becoming a popular and appealing tool in mineral prospectivity mapping (MPM); however, it has always been challenged by some essential limitations, such as scarcity of training samples, overfitting, and uncertainties. Data augmentation has been proven to be effective in addressing these issues and improving the performance of artificial intelligence models, but its mechanism regarding

The Sousse governorate (Tunisian Sahel) is an important socio-economic pole with a strong need for water. Intense drought during the last years has harmed the governorate’s activities. Therefore, groundwater exploitation is increasingly becoming necessary for ensuring sustainable development. It takes in-depth knowledge of aquifers to create an appropriate exploitation plan. In this context, the present

Determination of reservoir production schemes has always been a difficult problem during the close-loop management of waterflooding reservoir. Different well control results in significant influence on production, water breakthrough time and recovery rate of producing wells, especially in heterogeneous reservoirs. To optimize well controls, a new method using transpose convolution neural network (TCNN)

In petroleum and natural gas exploration, lithology identification—analyzing rock types beneath the Earth’s surface—is crucial for assessing hydrocarbon reservoirs and optimizing drilling strategies. Traditionally, this process relies on logging data such as gamma rays and resistivity, which often require manual interpretation, making it labor-intensive and prone to errors. To address these challenges

In the realm of mineral prospectivity mapping, a novel hybrid approach for optimizing hyperparameters of the support vector machine (SVM) algorithm is proposed here. The concept of ant colony optimization (ACO) algorithm, inspired by collective intelligence of ant colonies, and grid search (GS) that systematically evaluate all hyperparameter combinations to find the optimal model configuration are

In surface deformation monitoring for mining areas, interferometric synthetic aperture radar (InSAR) technology has become a popular research topic due to its efficiency and high accuracy. However, transforming temporal monitoring data into surface deformation predictions remains challenging. In practical applications, InSAR data often face limitations like low acquisition frequency and insufficient

Acid fracturing technology is one of the most effective methods for resolving mineral plugging and for improving the pore structure of coal reservoirs. To investigate the characteristics of shallow and deep coal nanopore structures under the influence of acidic fracturing fluids, experiments using synchrotron radiation small-angle X-ray scattering were conducted on shallow and deep coal samples soaked