Search Results (784)

In comparison to shallow coal seams, deep coal seams exhibit characteristics of high temperature, pressure, and in-situ stress, leading to significant differences in reservoir properties that constrain the effective development of deep coalbed methane (CBM). This study takes the Carboniferous deep 8# coal seam in the Yulin area of Ordos basin as the research subject. Based on the test results from core drilling wells, a comprehensive analysis of the characteristics and variation patterns of coal reservoir properties and a comparative analysis of the exploration and development potential of deep CBM are conducted, aiming to provide guidance for the development of deep CBM in the Ordos basin. The research results indicate that the coal seams are primarily composed of primary structure coal, with semi-bright to bright being the dominant macroscopic coal types. The maximum vitrinite reflectance (R_o,max) ranges between 1.99% and 2.24%, the organic is type III, and the high Vitrinite content provides a substantial material basis for the generation of CBM. Longitudinally, influenced by sedimentary environment and plant types, the lower part of the coal seam exhibits higher Vitrinite content and fixed carbon (FC_ad). The pore morphology is mainly characterized by wedge-shaped/parallel plate-shaped pores and open ventilation pores, with good connectivity, which is favorable for the storage and output of CBM. Micropores (<2 nm) have the highest volume proportion, showing an increasing trend with burial depth, and due to interlayer sliding and capillary condensation, the pore size (<2 nm) distribution follows an N shape. The full-scale pore heterogeneity (fractal dimension) gradually increases with increasing buried depth. Macroscopic fractures are mostly found in bright coal bands, while microscopic fractures are more developed in Vitrinite, showing a positive correlation between fracture density and Vitrinite content. The porosity and permeability conditions of reservoirs are comparable to the Daning–Jixian block, mostly constituting oversaturated gas reservoirs with a critical depth of 2400–2600 m and a high proportion of free gas, exhibiting promising development prospects, and the middle and upper coal seams are favorable intervals. In terms of resource conditions, preservation conditions, and reservoir alterability, the development potential of CBM from the Carboniferous deep 8# coal seam is comparable to the Linxing block but inferior to the Daning–Jixian block and Baijiahai uplift. Full article

The continuous deposition of coal fine in the well can lead to complex problems, such as pump blockage and reduced capacity. The traditional critical velocity model applicable to rigid spherical particles, such as sand grains and glass beads, finds it difficult to accurately predict the migration behavior of coal fine in the wellbore. Therefore, this study aims to reveal the sedimentation law of coal fine particles, establish a critical velocity prediction model applicable to pulverized coal, and provide a theoretical basis for effectively preventing pump blockage and capacity decline problems. This paper analyzes the particle characteristics of coal fine in different mining areas and conducts experiments on the static settling of coal fine particles and the critical transport velocity. The experimental results showed that the larger the mesh size of coal fine, the lower the static settling velocity of coal fine particles. The critical velocity of coal fine increased with the particle size and concentration of the coal fine particles, as well as with the increase of the pipe column inclination. A new empirical formula for calculating the critical velocity of coal fine particles was derived by considering the effects of the coal fine concentration and pipe inclination. Full article

In order to mitigate the reduction in soybean yield caused by soil salinization, a soybean gene, GmSNF4, which promotes plant tolerance to salt–alkali stress, was identified in this study. The STRING database was used to predict the interaction between GmSNF4 and GmPKS4. The GmPKS4 gene was experimentally shown to be involved in salt–alkali stress tolerance. Firstly, the yeast two-hybrid technique and bimolecular fluorescence complementation (BiFC) technique were used to confirm the interaction between GmSNF4 and GmPKS4: the AMPK-CBM-CBS1 conserved domain was thereby determined to be the region of the GmSNF4 protein involved in the interaction. Secondly, the GmSNF4 gene was induced by salt–alkali stress according to qRT-PCR analysis, and the GmSNF4 protein was localized in the nucleus and cytoplasm. Finally, analysis of GmSNF4’s role in resistance to salt–alkali stress in transgenic soybean plants showed that transgenic lines had better phenotypic, physiological, and stress-related gene expression than non-transgenic soybeans. Thus, GmSNF4 may play a significant role in plant salt–alkali stress tolerance. Full article

Concrete resistivity is a critical parameter for assessing durability and monitoring the structural health of reinforced concrete. This study systematically evaluates the effects of the water-to-cement (w/c) ratio, saturation ratio (SR), and temperature on concrete resistivity using three different predictive models: linear regression, cubic Support Vector Machine (SVM), and Gaussian Process Regression (GPR). Each model was independently trained and tested to assess its ability to capture the nonlinear relationships between these key parameters. Experimental results show that resistivity decreases significantly under increasing load due to geometrical effects. For a w/c ratio of 0.4, resistivity decreases by −12.48% at 100% SR and by −6.68% at 60% SR under 20% loading. Higher w/c ratios (0.5 and 0.6) exhibit more pronounced resistivity reductions due to increased porosity and ion mobility, with a maximum decrease of −13.68% for w/c = 0.6. Among the developed predictive models, the Matern 5/2 Gaussian process regression (GPR) model demonstrated the highest accuracy, achieving an RMSE of 5.21, R² of 0.99, MSE of 27.19, and MAE of 3.40, significantly outperforming the other approaches. Additionally, a permutation importance analysis revealed that the saturation ratio (SR) is the most critical variable influencing resistivity, followed by the water–cement ratio, while temperature has the least impact. These findings provide valuable insights into the durability assessment and corrosion prevention of reinforced concrete, offering practical implications for the optimization of material design and structural health monitoring in civil engineering. Full article

As renewable energy technologies advance, identifying efficient photocatalytic materials for water splitting to produce hydrogen has become an important research focus in materials science. This study presents a multi-task regression model (MTRM) designed to predict the conduction band minimum (CBM), valence band maximum (VBM), and solar-to-hydrogen efficiency (STH) of inorganic materials. Utilizing crystallographic and band gap data from over 15,000 materials in the SNUMAT database, machine-learning methods are applied to predict CBM and VBM, which are subsequently used as additional features to estimate STH. A deep neural network framework with a multi-branch, multi-task regression structure is employed to address the issue of error propagation in traditional cascading models by enabling feature sharing and joint optimization of the tasks. The calculated results show that, while traditional tree-based models perform well in single-task predictions, MTRM achieves superior performance in the multi-task setting, particularly for STH prediction, with an MSE of 0.0001 and an R² of 0.8265, significantly outperforming cascading approaches. This research provides a new approach to predicting photocatalytic material performance and demonstrates the potential of multi-task learning in materials science. Full article

Water within coal reservoirs exerts dual effects on methane adsorption–desorption by competing for adsorption sites and reducing permeability. The bound water effect, caused by coal wettability, significantly constrains coalbed methane (CBM) production, rendering investigations into coal wettability crucial for efficient CBM development. Compared with other geological formations, coals are characterized by a highly developed microporous structure, making the CO₂ sequestration mechanism in coal seams closely linked to the microscale interactions among gas, water, and coal matrixes. However, the intrinsic mechanisms remain poorly understood. In this study, molecular dynamics simulations are employed to investigate the wettability behaviors of CO₂, CH₄, and water on different coal matrix surfaces under varying temperature and pressure conditions, for coal macromolecules representative of four coal ranks. The study reveals the evolution of water wettability in response to CO₂ and CH₄ injection, identifies wettability differences among coal ranks, and analyzes the microscopic mechanisms governing wettability. The results show the following: (1) The contact angle increases with gas pressure, and the variation in wettability is more pronounced in CO₂ environments than in CH₄. As pressure increases, the number of hydrogen bonds decreases, while the peak gas density of CH₄ and CO₂ increases, leading to larger contact angles. (2) Simulations under different temperatures for the four coal ranks indicate that temperature has minimal influence on low-rank Hegu coal, whereas for higher-rank coals, gas adsorption on the coal surface increases, resulting in reduced wettability. Interfacial tension analysis further suggests that higher temperatures reduce water surface tension, cause dispersion of water molecules, and consequently improve wettability. Understanding the wettability variations among different coal ranks under variable pressure–temperature conditions provides a fundamental model and theoretical basis for investigating deep coal seam gas–water interactions and CO₂ geological sequestration mechanisms. These findings have significant implications for the advancement of CO₂-ECBM technology. Full article

In the development of deep coalbed methane (CBM) resources, the adsorption behavior of supercritical methane is a key factor restricting reserve evaluation and development efficiency. This study integrates scanning electron microscopy (SEM), low-temperature CO₂ adsorption (LTCO₂A), mercury intrusion porosimetry (MIP), high-temperature and high-pressure CH₄ adsorption experiments (HTHP-CH₄A), and theoretical models to reveal the pore–fracture structure of deep coal seams and the adsorption characteristics of supercritical methane. Based on a predictive model for supercritical methane adsorption capacity, the adsorption capacity of deep methane was predicted. Results show that micro-pores are well-developed in deep coal rocks, but pore connectivity is generally poor, predominantly consisting of fine bottleneck pores and semi-closed pores, with a certain proportion of open pores. The fractal dimension (D_m) of micro-pore structures in deep coal samples ranges from 2.0447 to 2.2439, indicating high micro-pore surface roughness and a large specific surface area, which provide favorable sites for methane adsorption. Pores larger than 100 nm exhibit fractal values between 2.6459 and 2.8833, suggesting that the pore surfaces in deep coal seams approach a three-dimensional pore space with rough surfaces and complex pore structures. As temperature and pressure enter the supercritical region, the adsorption capacity shows an abnormal trend of “first increasing and then decreasing” with increasing pressure. The deep coal rock–supercritical methane adsorption system exhibits two scenarios in low-pressure and high-pressure regions, corresponding to self-adsorption driven by strong methane adsorption potential and external force adsorption or overpressure micro-pore adsorption, respectively. The supercritical adsorption prediction model considering temperature and methane adsorption phase density has extremely low deviation (1.11–1.25%) and high accuracy. The average dispersion between predicted and actual values ranges from 0.44 cm³/g to 0.48 cm³/g, with small error fluctuations and no significant deviation. This study provides theoretical support for the recoverability evaluation and efficient development of deep CBM resources. Full article

The phase-change solidification plugging material (PSPM), a novel type of plugging material for severe fluid loss in demanding formations, necessitates performance enhancement and deeper insight into its hydration mechanism. In this paper, with a foundational formula comprising a nucleating agent (S1), activator (M1), and deionized water, a comprehensive investigation was conducted. This involved basic performance testing, including fluidity, setting or thickening time, hydration heat analysis, SEM and XRD for hydration products, and conduction of kinetics model. The focus was on analyzing the effects of three additives on system properties, hydration process, and hydration products, leading to the inference of the hydration mechanism of PSPM. It was found that the structure additives (SA) and flow pattern regulator (6301) did not partake in the hydration reaction, focusing instead on enhancing structure strength and maintaining slurry stability, respectively. Conversely, the phase regulator (BA) actively engaged in the hydration process, transitioning the system from the KG-N-D to the KG-D model, thereby extending the thickening time without altering the final hydration products. The morphology and composition of the products confirmed that SI and M1 dissolve in the aqueous solution and progressively form Mg(OH)₂ and MgSO₄·zMg(OH)₂·xH₂O. The slurry gradually solidifies, ultimately resulting in the formation of a high-strength consolidated body, thereby achieving the objective of lost circulation control. Full article

A quantitative characterization of the change in coal molecular structures with different cyclical microwave modification parameters and a better understanding of the reaction mechanism of the modification are of great significance for the commercial extraction of coal bed methane (CBM). Therefore, long-flame coal samples obtained from the Ordos Basin, China, were modified by microwave radiation with different times, and the long-flame coal molecular structure parameters were determined by solid-state ¹³C nuclear magnetic resonance (ss¹³C NMR), Fourier transform infrared (FTIR) spectrometry, and X-ray photoelectron spectrometry (XPS). Atomistic representations of the raw long-flame coal molecular model and modified long-flame coal molecular models were established. The temperature rise, pore volume increase, mineral removal, and functional group changes after the modification have a negative effect on methane adsorption. After the modification, the decrease in surface area of the micropores reduced the adsorption site of methane in coal. As a result, the methane adsorption amount decreased linearly with the decreasing surface area. The CH₄ adsorption isotherms of the long-flame models were dynamically simulated and analyzed. The results of this study can prove that after multiple cycles of microwave modifications, the functional groups in long-flame coal were fractured, and the number of micropores was reduced, which effectively decreased the methane adsorption performance in long-flame coal seams, thereby promoting methane extraction. Microwave modification is a promising method for enhancing CBM recovery. Full article

The rise of hybrid electric vehicles (HEVs) marks a shift away from traditional engines driven by environmental and economic concerns. With the rapid growth of HEVs worldwide, their reliability becomes of utmost concern; thus, guaranteeing the proper operation of HEVs is a crucial quest. Condition-based monitoring (CBM), which intends to observe different kinds of parameters in the system to detect defects and reduce any unwanted breakdowns and equipment failure, plays an efficient role in enhancing HEVs’ reliability and ensuring their healthy operation. The permanent magnet machine (PMM) is the most used electric machine in the electric propulsion system of HEVs, as well as the most expensive. Hence, the condition monitoring of this machine is of great importance. The magnet crack is one of the most severe faults that may arise in this machine. Artificial intelligence (AI) is showing high capability in the field of CBM, fault detection, and fault identification and prevention. Hence, the aim of this paper is to present two data-based fault detection approaches, which are the support vector machine (SVM) and the Hidden Markov Model (HMM). Their capability to detect primitive faults like tiny cracks in the machine’s magnet will be shown. Applying and evaluating various CBM methods is essential to identifying the most effective approach to maximizing reliability, minimizing downtime, and optimizing maintenance strategies. A strategy to specify the remaining useful life (RUL) of the defected element is proposed. Full article

The mechanism of low- to middle-rank coal seam gas accumulation in the Baode block on the eastern edge of the Ordos Basin is well understood. However, exploration efforts in the Shizuishan area on the western edge started later, and the current understanding of enrichment and accumulation rules is unclear. It is important to systematically study enrichment and accumulation, which guide the precise exploration and development of coal seam gas resources in the western wing of the basin. The coal seam collected from the Shizuishan area of Ningxia was taken as the target. Based on drilling, logging, seismic, and CBM (coalbed methane) test data, geological conditions were studied, and factors and reservoir formation modes of CBM enrichment were summarized. The results are as follows. The principal coal-bearing seams in the study area are coal seams No. 2 and No. 3 of the Shanxi Formation and No. 5 and No. 6 of the Taiyuan Formation, with thicknesses exceeding 10 m in the southwest and generally stable thickness across the region, providing favorable conditions for CBM enrichment. Spatial variations in burial depth show stability in the east and south, but notable fluctuations are observed near fault F1 in the west and north. These burial depth patterns are closely linked to coal rank, which increases with depth. Although the southeastern region exhibits a lower coal rank than the northwest, its variation is minimal, reflecting a more uniform thermal evolution. Lithologically, the roof of coal seam No. 6 is mainly composed of dense sandstone in the central and southern areas, indicating a strong sealing capacity conducive to gas preservation. This study employs a system that fuses multi-source geological data for analysis, integrating multi-dimensional data such as drilling, logging, seismic, and CBM testing data. It systematically reveals the gas control mechanism of “tectonic–sedimentary–fluid” trinity coupling in low-gentle slope structural belts, providing a new research paradigm for coalbed methane exploration in complex structural areas. It creatively proposes a three-type CBM accumulation model that includes the following: ① a steep flank tectonic fault escape type (tectonics-dominated); ② an axial tectonic hydrodynamic sealing type (water–tectonics composite); and ③ a gentle flank lithology–hydrodynamic sealing type (lithology–water synergy). This classification system breaks through the traditional binary framework, systematically explaining the spatiotemporal matching relationships of the accumulated elements in different structural positions and establishing quantitative criteria for target area selection. It systematically reveals the key controlling roles of low-gentle slope structural belts and slope belts in coalbed methane enrichment, innovatively proposing a new gentle slope accumulation model defined as “slope control storage, low-structure gas reservoir”. These integrated results highlight the mutual control of structural, thermal, and lithological factors on CBM enrichment and provide critical guidance for future exploration in the Ningxia Autonomous Region. Full article

The efficiency of coalbed methane (CBM) extraction is closely related to the drilling response of coal seams, which is significantly influenced by natural fracture development of coal seams. This work investigated 11 coal samples from the Baode, Xinyuan, and Huolinhe mines, employing quantitative fracture characterization, acoustic wave testing, drilling experiments, and cuttings analysis to systematically reveal the relationships and mechanisms between fracture parameters and coal drilling response characteristics. The result found that acoustic parameters (average wave velocity v and drilling surface wave velocity v₀) exhibit significant negative correlations with fracture line density (ρ₁) and area ratio (ρ₂) (|r| > 0.7), while the geological strength index (GSI) positively correlates with acoustic parameters, confirming their utility as indirect indicators of fracture development. Fracture area ratio (ρ₂) strongly correlates with drilling cuttings rate q (r = 0.82), whereas GSI negatively correlates with drilling rate w, indicating that highly fractured coal is more friable but structural stability constrains drilling efficiency, while fracture parameters show limited influence on drill cuttings quantity Q. Cuttings characteristics vary with fracture types and density. Type I coal (low-density coexisting exogenous fractures and cleats) produces cuttings dominated by fine particles with concentrated size distribution (average particle size d ≈ 0.52 mm, crushability index n = 0.46–0.61). Type II coal (exogenous-fracture-dominant) exhibits coarser particle sizes in cuttings (d ≈ 0.8 mm, n = 0.43–0.53). Type III coal (dense-cleat-dominant) drill cuttings are mainly coarse particles and are concentrated in distribution (d ≈ 1.53 mm, n = 0.72–0.98). Additionally, drilling response differences are governed by the coupling effects of vitrinite reflectance (R_o), density, and firmness coefficient (f), with Huolinhe coal being easier to drill due to its lower R_o, f, and density. This study elucidates the mechanism by which fracture development affects coal drilling response through multi-parameter correlation analysis, while also providing novel insights into the optimization of fracturing sweet spot selection for CBM development. Full article

As a crucial energy source and chemical raw material, coal’s micro-pore structure holds a pivotal influence on the occurrence and development of coalbed methane (CBM). This study systematically analyzed the nano-pore structure, surface roughness, and fractal characteristics of six coal samples with varying volatile matter content (V_daf) using Atomic Force Microscopy (AFM) combined with Scanning Electron Microscopy (SEM), revealing the correlation between volatile matter and the micro-physical properties of coal. Through AFM three-dimensional topographical observations, it was found that coal samples with higher volatile matter exhibited significant gorge-like undulations on their surfaces, with pores predominantly being irregular macropores, whereas low volatile matter coal samples had smoother surfaces with dense and regular pores. Additionally, the surface roughness parameters (R_a, R_q) of coal positively correlated with volatile matter content. Meanwhile, quantitative analysis of nano-pore parameters using Gwyddion software showed that an increase in volatile matter led to a decline in pore count, shape factor, and area porosity, while the average pore diameter increased. The fractal dimension of samples with different volatile matter contents was calculated, revealing a decrease in fractal dimension with rising volatile matter. Nano-ring analysis indicated that the total number of nano-rings was significantly higher in low volatile matter coal samples compared to high volatile matter ones, but the nano-ring roughness (R_r) increased with volatile matter content. SEM images further validated the AFM results. Through multi-scale characterization and quantitative analysis, this study clarified the extent to which volatile matter affects the nano-pore structure and surface properties of coal, providing critical data support for efficient CBM development and reservoir evaluation. Full article

Coal and gas outburst remains a critical and persistent challenge in coal extraction, posing a profound threat for mine safety. The underlying mechanisms of such disaster, particularly the gas-driven coal fragmentation, continue to elude comprehensive understanding. To explore this problem, in this paper, gas seepage regularity in different structural bituminous coal and its influence on outburst-coal breaking were investigated through strength tests, isothermal adsorption tests, and gas seepage tests of stressed coal under various conditions. The results indicated that coal permeability decreased as axial stress, confining pressure, and gas kinetic diameter increased. That meant outburst-induced abrupt stress unloading and coal matrix destabilization changed gas seepage characteristics. As a result, a self-reinforcing cycle effect where outburst-coal breaking and gas seepage are mutually stimulated was formed in a short time period when outbursts initiated, which further promoted outburst-coal breaking and outburst initiation. The findings of this study enhance our understanding of the mechanism of gas participating in coal fragmentation during outbursts, which are significantly conducive to gas disaster prevention, sustainable coal production, and efficient CBM development, further ensuring global energy security. Full article

This study systematically investigates the pore–fracture architecture of deep coal seams in the JiaTan (JT) block of the Ordos Basin using an integrated suite of advanced techniques, including nuclear magnetic resonance (NMR), high-pressure mercury intrusion, low-temperature nitrogen adsorption, low-pressure carbon dioxide adsorption, and micro-computed tomography (micro-CT). These complementary methods enable a quantitative assessment of pore structures spanning nano- to microscale dimensions. The results reveal a pore system overwhelmingly dominated by micropores—accounting for more than 98% of the total pore volume—which play a central role in coalbed methane (CBM) storage. Microfractures, although limited in volumetric proportion, markedly enhance permeability by forming critical flow pathways. Together, these features establish a dual-porosity system that governs methane transport and recovery in deep coal reservoirs. The multiscale characterization employed here proves essential for resolving reservoir heterogeneity and designing effective stimulation strategies. Notably, enhancing methane desorption in micropore-rich matrices and improving fracture connectivity are identified as key levers for optimizing deep CBM extraction. These insights offer a valuable foundation for the development of deep coalbed methane (DCBM) resources in the Ordos Basin and similar geological settings. Full article