Background Water hazards in coal seam floors represent a core challenge restricting the exploitation of deep coal resources in North China-type coalfields. As coal mining extends to greater depths, previous studies and experience exhibit limited applicability in the pattern classification, mechanism interpretation, and prevention and control of water hazards in thick floor aquicludes. Therefore, there is an urgent need to make breakthroughs and improvements in these three aspects.Methods Using several methods, including case-based induction, theoretical analysis, numerical simulation, and technical summary, this study developed a classification system based on parallel multiple criteria for floor water hazards by combining available water hazard patterns and representative cases of water inrushes. Based on a review of classical mechanisms behind water inrushes, this study systematically expounded on the disaster-causing mechanisms underlying water inrushes from thick floor aquicludes using the circular hole model in an infinite elastic plate (also referred to as the elastic circular hole model). In combination with numerical simulation, these mechanisms were further supplemented from a dynamic evolutionary perspective. Based on the derived disaster-causing mechanisms, the prevention and control system for water hazards from thick floor aquicludes was improved.ResultsRegarding water hazard patterns, this study developed a four-level classification system based on parallel criteria, i.e., the mechanisms and dynamic sources of water inrushes, as well as geological structures (including their types and characteristics). The mechanisms underlying water inrushes were classified into two general categories: the holistic failure of thin aquicludes and fracturing-induced water uplift of thick aquicludes. For water inrushes from thick floor aquicludes, the rupture process of defects in the floor was characterized using the elastic circular hole model. Accordingly, the distributions of the defect rupture pressure and fracture reopening pressure were proposed to serve as indicators for characterizing the floor state in the full spatiotemporal domain. Under the condition of thick floor aquicludes, the disaster-causing mechanisms of two water inrush subcategories, i.e., those with dynamic sources of mining pressure combined with water pressure (for intact aquicludes and aquicludes bearing faults, collapse columns, folds, and fractures) and merely water pressure (for equivalent homogeneous thick aquicludes), were elucidated. Besides, a water hazard prevention and control system incorporating six major links was organized. Based on mechanisms underlying water inrushes from thick floor aquicludes, this study refined eight specific tasks of three links in the system, namely exploration and evaluation, engineering prevention and control, and monitoring and early warning. Conclusions The four-level classification system provides a basis for the multi-perspective categorization of water hazard patterns. The elastic circular hole model enables the systematic analysis of mechanisms underlying water inrushes from thick floor aquicludes, overcoming the limitation of conventional models, each of which corresponds merely to a single pattern and mechanisms of water hazards. The controlling effects of the defect rupture pressure and fracture reopening pressure on the fracturing-induced confined water uplift are clarified, facilitating a shift from a static to a dynamic perspective in understanding the mechanisms behind water inrushes. The improved water hazard prevention and control system provides theoretical and methodological support for preventing and controlling water inrushes from thick floor aquicludes in the case of deep coal mining above confined aquifers. Overall, the results of this study provide a systematic basis for the prevention and control of water hazards in coal seam floors, holding significant theoretical and practical implications for enhancing the prevention and control level of water hazards in coal mines and ensuring the safe exploitation of deep coal resources.
[Objective]Uranium(U)and thorium(Th)in rocks and minerals are the material basis for the generation and release of crust-derived helium.[Methods]The enrichment characteristics and mechanisms of U and Th are key to un-derstanding the accumulation of crust-derived helium reservoirs.Taking the bauxite series of the Benxi Formation in the central North China Block as the research object,this study reveals the enrichment mechanisms of U and Th in the baux-ite series and calculates the helium generation rate by means of petrogeochemical and chronological research methods,combined with detrital zircon dating,sedimentary environment identification,and mass balance calculation.It provides theoretical support for exploring bauxite-type helium reservoirs.[Results and Conclusions]The results show that the bauxite series of the Benxi Formation in the central North China Block is widely developed,but its planar thickness var-ies significantly,being relatively thicker on both the north and south sides close to the provenance area.From bottom to top,the bauxite series can be divided into an iron-rich interval,an aluminum-bearing interval,a bauxite ore interval,an-other aluminum-bearing interval,and a dark mudstone interval,with diaspore as the main component in the bauxite in-terval.The enrichment of U and Th in the bauxite series is mainly controlled by provenance supply,sedimentary envir-onment evolution,and supergene leaching.The detrital zircons have main peak ages of 320 and 453 Ma,indicating that the provenance is magmatic rocks input from both north and south directions.After weathering and diagenesis of the source rocks,U and Th are preserved in detrital zircons in the form of isomorphism.During the formation of the bauxite series,there were dynamic changes in the oxidation-reduction environment,which provided conditions for the release,reduction,and precipitation of U.Under the influence of acidic leaching fluids,alkali metal ions(e.g.,K+,Na+)and al-kaline earth metal ions(e.g.,Mg2+,Ca2+)exhibit high chemical reactivity and undergo significant leaching loss.In con-trast,Al and Th,characterized by their chemical stability,are less mobile during the leaching process.Subject to the pH value and chemical composition of the system,U can be adsorbed and enriched by aluminum,iron,and manganese ox-ides/hydroxides.In the bauxite series,the U content in bauxite ranges from 13.26×10-6 to 57.10×10-6,the Th content ranges from 42.19×10-6to 136.00×10-6,and the helium generation rate is 2.85× 10-12 to 10.94×10-12 cm3/(a·g),showing good helium-generating capacity.The areas with thicker bauxite rock distribution in northwestern Henan Province,as well as in southern and northern Shanxi Province,exhibit strong helium generation capacity,making them potential fa-vorable zones for helium enrichment.
BackgroundAs coal mining in mines constantly expands to greater depths, water hazards in the Ordovician limestone aquifers of coal seam floors pose a serious threat to the mining of coal seams in lower formations. Fault reactivation represents a primary factor inducing water inrushes. However, the original water inrush coefficient (T = p/M) suffers from certain limitations when used to assess the water inrushes in areas with faults. MethodsFour models of floor water inrushes induced by non-penetrating faults (i.e., concealed hydraulically conductive faults, concealed isolated faults, and exposed faults) and penetrating faults were constructed, and the mechanisms behind various water inrushes were elucidated. Based on the original water inrush coefficient, improved water inrush coefficients corresponding to various faults were developed. Using mining face 81501 of the Liangzhuang Coal Mine in the Xinwen Coalfield of Shandong Province as an engineering case, the accuracy of the water inrush coefficients corresponding to non-penetrating and penetrating faults was verified through field measurements and numerical simulations, respectively. Results and ConclusionsThe improved water inrush coefficients comprehensively consider multiple factors, including the water yield property of aquifers, the lengths and dip angles of faults, the depth of the hydraulically conductive fractured zone in the coal seam floor, the thickness of the relative aquiclude, and the width of waterproof coal (rock) pillars, enhancing the scientific rigor and accuracy of the risk assessment of floor water inrushes in areas with faults. Compared to the original water inrush coefficient, the water inrush coefficients corresponding to non-penetrating faults increased by approximately 50%, with the high-risk zones identified proving highly consistent with actual water inrush locations. The water inrush coefficients corresponding to penetrating faults increased by approximately 158%, with the water inrush zones determined through assessment aligning with numerical simulation results. Overall, the improved water inrush coefficients allow for more rational and accurate risk assessment of floor water inrushes in areas with faults, providing a theoretical basis and technical reference for the prevention and control of water hazards in mines with similar geological conditions.
BackgroundIn China, low-yield coalbed methane (CBM) wells represent a high proportion of approximately 57% (over 12400 wells), generally encountering challenges such as low pressure, dry reservoirs, and near-wellbore formation damage and blockage. Conventional hydraulic fracturing is prone to induce water blocking damage, while treatments such as acidification offer only limited blockage-removing radii. Therefore, existing techniques are insufficient to achieve blockage removal and permeability enhancement while avoiding reservoir damage. Exploring efficient waterless stimulation technologies suitable for these low-yield wells is of great significance for increasing CBM production and advancing the CBM industry. MethodsThis study investigated directional wells PXC-03 and PZC-15 in the Panzhuang block of the Qinshui Basin. First, using velocity sensitivity event analysis, combined with production performance data, this study determined the causes and types of the low productivity of both wells. Then, innovatively employing CO2 waterless dynamic-load fracturing technology, this study conducted field engineering tests of multi-interval fracturing stimulation in the two wells. Finally, the water and gas production performance of the two wells before and after stimulation was compared, followed by a comprehensive evaluation of stimulation effects. ResultsThe calculation results of velocity sensitivity coefficients indicate that wells PXC-03 and PZC-15 experienced multiple velocity sensitivity events over 133 and 110 days of production, respectively. As a result, the reservoir permeability and gas production potential of the two wells were severely impaired, leading to a sharp decline in production. The two wells were classified as low-yield wells characterized by velocity sensitivity-induced near-wellbore blockage, both exhibiting low pressure and dry reservoirs. After fracturing stimulation, a large volume of gas-water mixture gushed out from well PXC-03, indicating that blockers were effectively removed through the scouring action. Concurrently, bottomhole flow pressure was restored, and stable water production was achieved. These findings confirm the effective removal of near-wellbore blockage and the successful reconstruction of seepage pathways in well PXC-03. Over subsequent 528 days of continuous production, the average daily gas production of this well increased from 318 m3 before stimulation to 1977 m3, and the peak daily gas production increased from 552 m3 to 3015 m3, representing 5.2- and 4.5-fold increases, respectively. Consequently, the cumulative gas production of well PXC-03 reached up to 1.044 × 106 m3. For well PZC-15, a low-permeability well with more complex geological conditions, the average daily gas production increased by 3.0 times after stimulation. These results demonstrate that the CO2 fracturing technology exhibits significant stimulation effects for distinct types of reservoirs.ConclusionsThe CO2 waterless dynamic-load fracturing technology employs CO2 as the sole working medium throughout the fracturing operation. Through dynamic-load fracture creation and the scouring action of high-pressure gas wedges, this technology can effectively reconstruct the near-wellbore fracture network and remove pulverized coal blockage while fundamentally avoiding water blocking damage in dry reservoirs. Therefore, this technology represents an effective approach to the efficient stimulation and production growth of low-yield wells characterized by low pressure, dry reservoirs, and near-wellbore blockage. Most especially, this technology holds broad prospects for widespread application in low-pressure and low-permeability CBM wells.
ObjectiveCantilever roadheaders represent roadway tunnelling equipment that integrates the deep coupling of mechanical, electrical, and hydraulic systems, and their control accuracy directly determines the forming quality of roadways.MethodsCantilever roadheaders involve nonlinear mechanical motion, hydraulic control, and cutting load, rendering it challenging to establish accurate control models. Using the philosophy of digital twin modeling, this study developed a method for optimizing the digital twin model of the mechanical-electro-hydraulic system of cantilever roadheaders based on virtual-physical consistency evaluation. Specifically, a digital twin model of the mechanical-electro-hydraulic system was developed using multi-domain co-simulation between AMESim and Simulink. This model allows the coupling properties and nonlinear dynamic behavior of the mechanical-electro-hydraulic system to be accurately expressed in the digital space. By establishing an evaluation system for the consistency between virtual and physical control behaviors in roadway cutting, the evolutionary mechanisms of the deviations between the digital twin model and the physical control system were explored. Based on the evaluation results, the iterative calibration of key physical parameters in the digital twin model was conducted using the particle swarm optimization algorithm. By minimizing the deviations between virtual and physical control behaviors, the digital twin model’s ability to reproduce the physical cutting process of roadways was enhanced. Results and Conclusions The proposed optimization method for the digital twin model was verified using an experimental platform. The verification results indicate that after model optimization with cylinder displacement as a benchmark, the deviation between virtual and physical control behaviors was reduced by 84.5%, with the root mean square error (RMSE) and the mean absolute error (MAE) both decreased by up to 70% and the maximum absolute error decreased by 60%. After model optimization with cylinder pressures under normal and abnormal load operating conditions as benchmarks, the deviations decreased by 83.57% and 81.98%, respectively. These findings suggest that the model optimization can effectively reduce the deviation between virtual and physical behaviors under complex operating conditions. Overall, the optimization method proposed in this study provides an efficient and feasible solution for digital twin-based precise modeling and virtual-physical interactions of mining and tunneling equipment under complex underground operating conditions.
Objective With the continuous advancement in the exploration and exploitation of coalbed methane (CBM), the focus of research and practices is gradually shifting from shallow to deep parts. Deep CBM, an important unconventional natural gas resource, has become a strategic replacement to ensure energy security and prompt industrial development in China. However, deep coal reservoirs exhibit strong heterogeneities, posing a core geological challenge to their efficient exploration and development. Methods This study investigated the deep No. 8 coal seam in the northern part of the eastern margin of the Ordos Basin. By integrating multiple technical methods, including geostatistics, spatial interpolation, substantial core tests, and numerical simulation, this study systematically examined the multi-scale heterogeneities of reservoirs in the No. 8 coal seam in the lateral and vertical directions. Furthermore, the controlling effects of reservoir heterogeneities on CBM productivity were quantitatively assessed. Results and Conclusions The results indicate that deep coal reservoirs in the northern part of the eastern margin of the Ordos Basin exhibit a representative heterogeneous mode characterized by a homogeneous geological background but differential key parameters. The burial depth, vitrinite reflectance (Rmax), and vitrinite content of the reservoirs show coefficients of variation (CVs) of less than 0.15, suggesting the high stability of the regional tectonic setting, thermal evolution history, and coal-forming environments. In contrast, the Langmuir volume, gas content, and adsorbed gas saturation of the reservoirs exhibit CVs ranging from 0.27 to 0.33, implying moderate heterogeneities. Furthermore, the spatial differentiations of these parameters are governed by the coupling effects of local factors. Based on these findings, three CBM enrichment patterns were identified in the study area. Specifically, the southeastern part exhibits gas generation-dominated CBM enrichment, which is driven by thermal anomalies of concealed rock masses and features high Rmax and gas content. The southwestern part manifests a CBM enrichment pattern characterized by great burial depth and high saturation. This enrichment pattern can be attributed to both weak adsorption effects under high temperatures due to deep burial and favorable preservation conditions, which jointly contribute to the formation of a free gas enrichment area with high adsorbed gas saturation. The northern part displays low hydrocarbon generation and weak preservation conditions, identified as an area with poor gas-bearing properties. Based on two representative wells, this study revealed the binary control mechanisms behind the vertical heterogeneity of gas-bearing properties in the No. 8 coal seam. Under the geological setting of poor preservation conditions, the intralayer sealing effect predominates, with gas-bearing properties tending to be higher in the middle part and lower in the upper and lower parts vertically. In this case, sweet spot intervals are situated in the middle part of the coal seam. In areas with favorable preservation conditions, the vertical distribution of gas-bearing properties is primarily governed by the static differentiation of original coal-forming materials. Numerical simulations corroborate that the heterogeneous distributions of vertical gas-bearing properties exert significant impacts on CBM productivity. The 10-year cumulative gas production of the scheme with precise perforation in a sweet spot interval was 4.1 times higher than that of the scheme with perforation arranged in an interval with poor gas-bearing properties. Integrating research on the vertical heterogeneity of coal reservoirs into the precise positioning of sweet spot intervals and the optimization of perforation schemes is key to the fine-scale and efficient exploitation of deep CBM. The results of this study are of great significance for gaining deep insights into the enrichment patterns of deep CBM and for guiding the exploration and exploitation practices of deep CBM under similar geological conditions.
[Objective]Compressed air energy storage(CAES)in a lined hard rock cavern holds great prospects.However,the load sharing mechanisms of the cavern's composite structure,comprising a sealing layer,lining,and sur-rounding rocks,remain poorly understood.[Methods]Based on the elastic analytical solutions of stress fields,this first study derived the radial load equilibrium equations for the composite structure of a lined hard rock cavern for CAES.Accordingly,a novel method for calculating the load sharing ratios of the composite structure was developed.Then,an analysis scheme for the load sharing ratios was designed.Using this scheme,this study investigated the variation pat-terns of the load sharing ratios of the composite structure under the influence of different factors.Finally,key factors in-fluencing the load sharing ratios were determined through parameter sensitivity analysis.[Results and Conclusions]The results indicate that in the composite structure of a lined hard rock cavern for CAES,surrounding rocks represent the primary bearer of the high pressure load for gas storage(80％-90％).In contrast,the sealing layer shares a small propor-tion of the load(1％5％),while the load sharing ratio of the concrete lining is significantly affected by design parameters,varying from 5％to 20％under the proposed parameter combinations.The load sharing ratios of various structural lay-ers exhibit nonlinear relationships with the cavern radius,the elastic modulus of surrounding rocks,and the gas storage pressure,while showing approximately linear relationships with other parameters.In terms of parameter sensitivity,the elastic modulus of surrounding rocks exerts the most significant influence on the load sharing ratios of the composite structure,followed by the elastic modulus of concrete lining,gas storage pressure,cavern radius,lining thickness,in situ stress,and thickness of the steel sealing layer sequentially.The joint load bearing design for the composite structure should account for the load sharing function of the lining.Appropriately increasing the lining thickness can effectively increase the load sharing ratio of the lining while also improving the circumferential tensile stress conditions of the com-posite structure.In contrast,raising the concrete grade,despite slightly increasing the lining's load sharing ratio,tends to increase the circumferential tensile stress,thereby increasing the risk of lining cracking.The results of this study can provide certain theoretical guidance for gaining insights into the load-bearing mechanisms and optimizing the design of the composite structure of a lined hard rock cavern for CAES.
[Objective]Significant breakthroughs have been achieved in the exploration and exploitation of coalbed methane(CBM)in the deep No.8 coal seam within the east-central Ordos Basin.However,a comprehensive quantitat-ive evaluation system at the regional scale is yet to be established for reservoirs in the No.8 coal seam.[Methods]Based on logs,coal quality,and measured physical property data from over 270 wells in the east-central Ordos Basin,this study developed a comprehensive evaluation system for deep coal reservoirs using the fuzzy analytic hierarchy process com-bined with the entropy weight method.Specifically,the evaluation system consisted of nine key indicators(i.e.,burial depth,minimum horizontal principal stress gradient,vitrinite reflectance(Rmax),coal thickness,total proportion of bright and semi-bright coals,gangue proportion,ash content,porosity,and permeability)of three aspects,namely occurrence conditions,coal seam characteristics,and reservoir physical properties.Accordingly,this study conducted a quantitative evaluation of high-quality deep coal reservoirs and further determined their developmental characteristics and distribu-tion patterns.[Resultsand Conclusions]The high-quality reservoirs in the No.8 coal seam within the east-central Or-dos Basin exhibit a range of distinct characteristics,including coal seam thicknesses of greater than 6 m,total propor-tions of bright and semi-bright coals exceeding 85％,gangue proportions of less than 5％,and ash content of below 10％.The reservoirs manifest coal seam burial depths ranging between 1 800 m and 3 000 m,minimum horizontal principal stress gradients of less than 1.65 MPa/hm,and Rmax values varying from 1.3％to 2.5％,suggesting medium-to high-rank coals.Additionally,their porosity and permeability exceed 5％and 0.1 × 10-3 μm2,respectively,indicating high gas storage and fluid flow capacities.The comprehensive evaluation system reveals that the No.8 coal seam can be divided into classes Ⅰ,Ⅱ,and Ⅲ zones.Among these,class Ⅰ zones,with comprehensive evaluation index(Ⅰ)values of＞0.65,ac-count for approximately 50％-60％,primarily distributed in the Shenmu-Jiaxian-Yulin and Mizhi-Suide-Zizhou areas.Class Ⅱ zones,with 0.45 ≤ I ≤ 0.65,account for 30％-35％and are principally identified in the north-central and southwestern parts of the study area.In this class of zones,the No.8 coal seam exhibits relatively high ash content,large burial depths,and poor physical properties.Class Ⅲ zones,with I＜0.45,represent approximately 10％of the total area of the No.8 coal seam,primarily distributed in the Yimeng uplift and the southern Jingbian area.
[Background]Underground coal gasification(UCG)represents an in situ conversion technology used to con-vert solid coals into gaseous fuel.However,the reaction process during UCG exhibits significant time delays.Such a limitation will reduce the response capability of the UCG system and is prone to induce overshoot and oscillation,thereby increasing the system's control difficulty and reducing its stability and dynamic performance.[Method]To ad-dress these issues,this study proposed an enhanced Smith predictor control algorithm based on a genetic algorithm and established a semi-physical experimental platform integrating a physical distributed control system DCS-Matlab for modeling.Using the platform,experiments on the enhanced Smith predictor control algorithm were carried out under time delays ranging from 500 s to 2000 s and CO2 volume fractions varying between 25％and 40％.[Results]The res-ults indicate that the time delay emerged as a key factor influencing the UCG control performance.Compared to propor-tional-integral-derivative(PID)control and Smith predictor control,the proposed enhanced Smith predictor control al-gorithm performed the best in dealing with long time delays.Specifically,under PID control,the time required for CO2 concentration to stabilize increased by 30.77 times in the case of a prolonged time delay of 1 500 s.Under model match(τ=1 500 s),Smith predictor control reduced the time from approximately 400 min to 38 min compared to PID control,representing a 90.5％improvement.However,in the case of 40％model mismatch,Smith predictor control increased the time by 4.37 times,suggesting limited robustness.In contrast,under identical conditions of model mismatch,the en-hanced Smith predictor control algorithm reduced the time by 36％-59％and demonstrated smoother responses and a lower percentage overshoot than the Smith predictor control.[Conclusions]The results of this study demonstrate the ef-fectiveness of the proposed enhanced Smith predictor control algorithm,which exhibits high adaptability to UCG sys-tems with long time delays under model uncertainty.This study provides a theoretical and practical engineering refer-ence for UCG with long time delays.
ObjectiveIn coal mines, harsh environments and complex geological conditions underground lead to frequent failures of tunnel drilling rigs. However, conventional techniques for failure diagnosis and early warning suffer from limitations in diagnostic accuracy, real-time performance, and interpretability. Therefore, these techniques are insufficient for both the rapid identification of the anomalous status of tunnel drilling rigs and the early warning of their potential failures. MethodsConsidering the complex underground environments in coal mines, this study developed an intelligent failure diagnosis and early warning system for tunnel drilling rigs in coal mines, placing a particular emphasis on key technologies for failure diagnosis and early warning. For failure diagnosis, the coupling relationships among variables were quantitatively characterized by combining the operating mechanisms of key circuits and cross-correlation function (CCF) analysis. Accordingly, the failure propagation patterns were revealed, and a diagnosis strategy based on node characteristics was established. For early warning of potential failures, the operational status of drilling rigs was quantified using time domain features such as mean and standard deviation. Then, a health index was constructed using principal component analysis (PCA). Finally, a hierarchical early warning mechanism was established in combination with Z-scores and the three-sigma rule. Based on these, an intelligent failure diagnosis and early warning system for tunnel drilling rigs was established through software development based on the Qt platform and the MySQL database.Results and ConclusionsUsing field tests at the Zhashui test base, the performance of the developed system was verified. The results indicate that the developed system achieved an accuracy of 96.8% and a recall of 90.5% for failure diagnosis. For early warning, this system yielded a failure detection rate of 94.6% and a false alarm rate of 1.5%, indicating a small number of false alarms. Compared to conventional passive protection technologies, the intelligent failure diagnosis and early warning system for tunnel drilling rigs developed in this study can accurately identify the operational status of tunnel drilling rigs and assess their health degrees in real time, thereby enabling timely early warning of potential faults. This study provides a theoretical basis and engineering solution for the stable operation and predictive maintenance of tunnel drilling rigs.
[Background]Deep coalbed methane(CBM)reservoirs are characterized by well-developed microstructures and natural fractures,along with highly heterogeneous rock mechanical properties and in-situ stress field distribution.The CBM production of the reservoirs tends to cause constantly evolving formation pressure and in-situ stress within the control ranges of CBM wells,further enhancing the complexity of stress distribution.Additionally,severe fracturing channeling can be observed between new and old wells.This phenomenon is primarily triggered by in-situ stress vari-ations induced by large-scale fracturing and CBM production.Therefore,accurately assessing the dynamic evolutionary patterns of in-situ stresses in reservoirs after fracturing and during CBM production holds great significance for new well placement,fracturing design optimization,and anti-channeling during fracturing.[Methods]This study investigated the Daning-Jixian block in the Ordos Basin as an example.Based on the geological characteristics of the study area,this study established a model for predicting the evolution of four-dimensional in-situ stresses in deep CBM reservoirs dur-ing long-term CBM production.Specifically,models for initial three-dimensional geomechanical characteristics,post-fracturing stress fields,and production-induced stress fields were established first,collectively enabling the dynamic,fine-scale characterization of stress fields from the initial stage to long-term CBEM production.The accuracy of the pro-posed four-dimensional model was verified using data from field microseismic and production monitoring.[Results and Conclusions]In the target well block,the difference between the maximum and minimum principal stresses decreased after fracturing and then gradually increased as CBM production proceeded.Over 24 months of CBM production,the minimum horizontal in situ stress in the vicinity of the well group decreased by 2.10-5.75 MPa,accompanied by signi-ficant variation in the in-situ stress direction(average:4.12°).A greater stress drop corresponded to higher connectivity of the fracture network,a larger range of formation energy supply,and greater production potential.The simulation res-ults indicate that the optimal reservoir stimulation performance can be obtained under angles between the horizontal well trajectory direction and the maximum principal stress direction measuring from 70° to 110°,combined with a well spa-cing of 400 m.This helps maximize the estimated ultimate recovery(EUR).The construction approaches for zipper frac-turing are determined.For zipper fracturing of two adjacent wells in zones with imbalanced stresses,the well in the low-stress zone should be fractured first.After the post-fracturing stress balance,the well in the high-stress zone should be fractured.This approach facilitates the adequate coalescence of the fracture network.For zipper fracturing in three wells,for instance,in zones with similar stress levels,two lateral wells should be fractured first to allow the stress differences on both sides of the middle well to vary consistently,contributing to stress balance.Then,the fracturing parameters of the middle well should be optimized to achieve adequate coalescence of the fracture network.Additionally,a method for fine-scale division of fracturing stages and perforation clusters is proposed based on stress magnitudes,providing robust technical support for the fracturing and development of deep CBM wells.
ObjectiveCO2 displacing coalbed methane (CBM) provides substantial environmental and energy benefits. However, differences in coal structures represent a key geological factor influencing the effectiveness of this technique. Constrained by the complex geological conditions for CBM occurrence and the impacts of multiple factors on the log responses of coal structures, traditional log-based methods for coal structure identification face challenges such as much human intervention, complex feature engineering, and poor adaptability. This study aims to achieve effective identification of complex coal structures within a single coal seam. MethodsAn asymmetric convolution kernel-based convolutional neural network (CNN) model for coal structure identification was proposed in this study. When constructing feature matrices for the model, a feature weighting mechanism based on mutual information values was incorporated to underline sensitive log curves. Meanwhile, a Gaussian weighting strategy was integrated along the depth direction to highlight the log information from central points. Using two asymmetric convolution kernels of sizes 3×1 and 3×2, the CNN model enabled differential feature extraction from the log data in the vertical and lateral directions. Vertically, the weights of the contributions of various log values to feature extraction were adaptively adjusted based on the differences in the coverage times of the convolution kernels across different lines of depth. Laterally, the synergistic variation characteristics among multiple log curves were fully preserved. ResultsThe design of asymmetric convolution kernels allows for the effective utilization of the spatial structural characteristics of log data. Accordingly, complex nonlinear mapping relationships between log responses and coal structures are established. Experiments were conducted on log data from primary coal seams in the CBM exploration area at the periphery of the Panji coal mine, Huainan mining area, Anhui Province. The experimental results reveal that the CNN model yielded an accuracy of up to 82.64% on the test set, significantly outperforming the multilayer perceptron (MLP, 78.13%), support vector machine (SVM, 73.67%), and K-means clustering (64.42%) models. ConclusionThe integration of priori geological knowledge with deep learning can effectively enhance the accuracy of log-based coal structure identification. This finding provides a novel technical approach to the high-accuracy identification of coal structures in structurally complex areas, holding great practical value for efficient CBM production.
[Background]Data from previous exploration and studies indicate that the Lutang coal-based graphite min-ing area in Hunan Province falls within the Lutang-Shatian synclinorium in terms of tectonic location,with coal-bearing strata dominated by the upper member of the Upper Permian Longtan Formation.Influenced by the intrusion of granites,coal seams adjacent to the Qitianling pluton on the eastern flank of the mining area have undergone contact metamorph-ism,forming coal-based graphite.Previous exploration results suggest that the Qitianling pluton has a maximum burial depth measured at an elevation of 0 m or less.However,with constant underground exposure in mines,previous insights into the structures and ore layer distribution in the mining area have largely changed,failing to meet the current produc-tion demands.[Methods]This study developed a new understanding of structural traces in the mining area through in-depth mining of available geological data.Using a range of methods,including surface reconnaissance,logging of mine roadways,sample collection and tests,and mapping,this study investigated the geometric,kinematic,and dynamic char-acteristics of gravitational gliding structures in the mining area.Through a series of analyses and comprehensive examin-ations,it proposed innovative inferences and insights regarding gravitational gliding structures in the mining area.[Res-ults and Conclusions]Inferences reveal that a gravitational gliding structure(F1)sliding from east to west occurs on the eastern flank of the mining area.The overlying system of F,is a synclinorium confirmed through years of exploration and development,while its underlying system is the concealed area of the Lutang-Shatian synclinorium.The concealed area hosts large-scale coal-based graphite deposits,representing a gap in previous exploration and studies.The ore pro-specting and exploration efforts in 2024 provide more definite insights into the structural characteristics of F1,the con-cealed area of the Lutang-Shatian synclinorium,and the ore-hosting properties of the synclinorium.The results reveal that F,is a gravitational gliding structure that resembles a klippe in the planar view and appears as a spoon with an end lifted on the cross-section.The concealed area emerges as an asymmetric tight syncline with a steep western limb and a gentle eastern limb,where thick,numerous,and high-quality coal-based graphite deposits show maximum burial depths exceeding an elevation of-400 m.Overall,this study presents a summary of the developmental characteristics of the Lutang gravitational gliding structure,corrects the structural distribution patterns in southern Hunan,and analyzes mech-anisms underlying the formation of the gliding structure.Furthermore,it establishes spoon-shaped ore-controlling styles of gravitational gliding structures and predicts the resources of coal-based graphite in the concealed area.The novel in-sights obtained in this study provide a valuable guide for geological prospecting while also holding great strategic signi-ficance for the exploration and development of mines in their depletion periods.
BackgroundBedrock weathering zones exhibit distinct vertical gradational characteristics. Accurately identifying the degrees of fracture development in the zones is critical to the safe production of mines in shallowly buried coal seams covered by thick water-bearing unconsolidated layers. MethodsFocusing on the Qinan coal mine in Anhui Province, this study proposed a hybrid convolutional neural network (CNN) model, which enabled feature extraction using a synergistic architecture consisting of conventional convolutional layers and inception modules. Specifically, based on conventional log data and calculated shale content and fracture development index, combined with core observations, this study constructed a dataset containing labels that indicated four degrees of fracture development: fractured, high, medium, and low degrees. The synergistic architecture was then designed, in which conventional convolutional layers and inception modules were employed to extract local subtle features and conduct multi-scale feature fusion, respectively. Subsequently, hyperparameters, including the sequence length and learning rate, were optimized through grid search. Finally, the CNN model was trained to determine the degrees of fracture development intelligently. Results and Conclusions Compared to the random forest (RF), XGBoost, and support vector machine (SVM) models, as well as other CNN models, the hybrid CNN model demonstrated superior performance, with an accuracy reaching 92.71% and a weighted average F1 score of up to 93% on the test set. Furthermore, the proposed model can accurately capture the log response characteristics of fracture development in rocks, significantly enhancing the efficiency and continuity of log-based fracture assessment. The hybrid CNN model was applied to 25 boreholes in a certain mining area of the study area. Accordingly, a 3D geological model of weathered zones in the mining area was created. With an average root mean square error (RMSE) of 8.9 m in the prediction of the top boundary depths of various weathering zones, the geological model clearly exhibits the spatial distribution patterns of completely, strongly, and moderately weathered zones, together with slightly weathered to unweathered zones, thereby providing a quantitative geological basis for grouting engineering, along with the prevention and control of roof water hazards, in the coal mine.
[Background]Depressurization through dewatering using inclined wells arranged at the aquifer bottom rep-resents a crucial technical approach to the prevention and control of water-sand inrush disasters during coal mining be-neath aquifers.However,the mechanisms underlying seepage-pressure interactions and water-preserved depressuriza-tion remain poorly understood.[Methods]Based on the water-yield properties of confined aquifers and the distribution characteristics of inclined wells for dewatering,this study developed a fan-shaped sand tank experimental system for simulating dewatering and seepage from confined aquifers.Using the experimental system,this study carried out seep-age experiments using a partially penetrating well at the bottom of a confined aquifer under varying well radii,well lengths,and dewatering pressures.Furthermore,the dynamic response characteristics of seepage and pressure were sys-tematically analyzed.[Results and Conclusions]Under the influence of the elastic water release characteristics of the confined aquifer,pressure heads at various monitoring points exhibited short response and stabilization times after the dewatering pressure changed,with a pressure reduction zone formed near the inclined well at the aquifer bottom.In the case where the well length and radius were set at 40-300 mm and 40-100 mm,respectively,and the outlet of the drain-age pipe remained full of water,negative pressure was formed within the well when the water level in the well was lower than the well head.The absolute value of the negative pressure rose as the well length and radius increased,with the neg-ative pressure effect enlarging the pressure reduction zone at the aquifer bottom.Increasing the well length significantly enhanced the dewatering rate,provided that the well length was less than the critical value(250 mm).Increasing the well radius,despite also enhancing the dewatering rate,is difficult to implement in engineering practices.Besides,the negat-ive pressure suction effect could also increase the dewatering rate.In the initial stage of dewatering,water released from the aquifer was dominated by stored static water.Then,the released water quickly transitioned into boundary dynamic recharge following a first-order exponential law.Based on the specific pressure distribution pattern formed using dewa-tering wells at the aquifer bottom,this study proposed a novel hydrogeological model that enables the effective preven-tion and control of water-sand inrush disasters while also mitigating the drop in the total water level of an aquifer.This model offers a novel,feasible approach to water-preserved coal mining that balances mining safety and ecosystem con-servation.
Objective In the monitoring of coal seam mining-induced deformation and failure of surrounding rocks, the borehole resistivity method stands out due to its capacity for dynamic, three-dimensional (3D) full-space measurements. However, conventional resistivity inversion for the method is generally carried out using the least squares algorithm, leading to limited accuracy in practical engineering. In recent years, neural network-based inversion has demonstrated the potential for addressing this challenge, while its performance is yet to be further improved. MethodsIn this context, inversion imaging based on a back propagation-Kolmogorov-Arnold network (BP-KAN) was proposed for the borehole resistivity method, aiming to accurately monitor the range and depth of mining-induced deformation and failure of a coal seam floor. First, based on representative geological conditions of coal mines, this study constructed geoelectric models for mining-induced deformation and failure of a coal seam floor under varying advancement distances of a mining face. Forward modeling was then conducted to establish training and test datasets for the BP-KAN neural network. Subsequently, the inversion imaging results derived using the BP-KAN neural network were compared with those determined using the KAN and BP neural networks and the least squares method. Finally, in combination with the measured data derived using the borehole resistivity method from the coal seam floor of mining face 3303 in a coal mine of Shanxi Province, the inversion imaging performance of the BP-KAN neural network in engineering application was validated.Results and Conclusions The BP-KAN-based inversion imaging for the borehole resistivity method enables accurate characterization of the ranges, boundary morphologies, and resistivity variations of the mining-induced failure zone in the coal seam floor, thereby improving the inversion imaging accuracy of the borehole resistivity method. In the engineering application, the proposed BP-KAN-based inversion imaging revealed a floor failure depth of 15.5 m, with an absolute error of merely 0.5 m against the failure depth (15 m) derived in the field through the segmented water injection with double-end sealing using a borehole. Besides, the proposed inversion imaging method outperformed the inversion using a traditional BP neural network, which yielded a failure depth of 19 m. Furthermore, the failure range revealed by the proposed inversion imaging method was consistent with the actual evolution patterns of mining-induced failure. Therefore, the BP-KAN-based inversion imaging for the borehole resistivity method features high monitoring accuracy and reliability, offering a novel approach for the precise monitoring of the deformation and failure of coal seam floors.
[Objective]Significant breakthroughs have been achieved in the exploration of bauxite gas reservoirs in the Taiyuan Formation,Longdong area,Ordos Basin.Bauxites are generally considered to hold great helium generation po-tential due to their relatively high uranium(U)and thorium(Th)contents.However,there remains a lack of quantitative studies on their actual contribution to helium abundance in natural gas in the area.[Methods]To determine dominant he-lium source rocks and mechanisms behind helium enrichment,this study investigated the bauxite gas reservoirs within the Taiyuan Formation in the Longdong area.Through analyses of the composition,carbon isotopes,and noble gas iso-topes of helium-bearing natural gas,the origins of natural gas and helium in the reservoirs were identified.Based on the conventional genetic approach,this study developed a quantitative method for calculating the contribution of sediment-ary effective helium source rocks to relative helium abundance in bauxite gas reservoirs.Accordingly,the contributions of bauxite reservoirs and hydrocarbon source rocks to helium abundance were assessed,and the mechanisms underlying helium enrichment in the reservoirs were explored.[Results]In the Longdong area,natural gas in bauxite gas reservoirs exhibits helium volume fractions ranging from 0.06％to 0.25％(average:0.12％)and 3He/4He ratios varying from 2.27× 10-8 to 3.86× 10-8,indicating a typical crustal origin of helium.Theoretical calculations indicate that bauxite reser-voirs and the Upper Paleozoic coal-measure hydrocarbon source rocks contribute relative helium abundance(280-801)× 10-6 and 75×10-6,respectively to natural gas.In the case where sedimentary effective helium source rocks serve as the only helium source,the maximum helium content in natural gas was calculated at 876× 10-6,which is lower than the threshold for helium-rich natural gas(He content＞0.1％).Therefore,bauxite reservoirs and coal-measure hydrocarbon source rocks possess a limited helium supply capacity,failing to form helium-rich natural gas independently.In contrast,basement granites exhibit huge volumes and can release large amounts of helium under geological conditions such as tectonic uplift,thereby serving as major helium source rocks in the Longdong area.[Conclusions]In the Longdong area,helium enrichment in bauxite gas reservoirs is collectively controlled by multiple factors,including tectonic activity,fault development,and the natural gas accumulation process.The helium enrichment pattern of the reservoirs is charac-terized by a multi-source helium supply predominated by basement granites and supplemented by sedimentary effective helium source rocks.
[Background]The Huanghuai mining area represents an important coal base in eastern China.However,the Cenozoic calcareous clay in the area exhibits high plasticity,low permeability,and potential expansion and deformation during freezing,leading to unstable freezing performance.Consequently,artificial ground freezing(AGF)in the area generally faces a risk of cost surge or out of control due to the excessive thickness or limited strength of frozen walls.[Methods]This study investigated calcareous clay remolded based on soil samples from the Huanghuai mining area.Us-ing a low-field nuclear magnetic resonance(LF-NMR)spectrometer and a high-pressure triaxial system,this study sys-tematically explored the variation patterns of unfrozen water content during freezing under temperatures ranging from 20℃ to-20℃,confining pressures from 1 MPa to 4 MPa,and initial water contents of 17.5％,22.5％,and 31.5％.Ac-cordingly,the impacts of these different factors on the triaxial strength of the frozen calcareous clay were determined.[Results and Conclusions]The results indicate that during the freezing of the remolded calcareous clay,unfrozen water content in the clay evolved through three stages-rapid decline,slow decline,and stabilization,sequentially,with a higher initial water content corresponding to a more distinct rapid decline stage.Accordingly,a modified power func-tion of unfrozen water content(wu)and freezing temperature(t)was developed,with a fitting accuracy(R2)of greater than 0.97.Triaxial test results reveal that the failure stress of the frozen calcareous clay increased significantly with de-creasing freezing temperature.In contrast,the stress increased nonlinearly with initial water content,while the increased amplitude decreased gradually.In the case where the confining pressure exceeded 3 MPa,the strength reversal phe-nomenon occurred due to both pressure-induced ice crystal melting and pore water lubrication at interparticle contacts,with the critical pressure interval determined at 2.5-3.5 MPa.By innovatively introducing the concept of coupling between unfrozen water content and cementation area into the Mohr-Coulomb failure criterion,this study created a mod-el enabling the strength of frozen calcareous clay to be predicted based on merely three parameters:freezing temperature,initial water content,and confining pressure.The correlation coefficient(R2)and average relative error between the mod-el-calculated and measured strength were determined at＞0.95 and＜5％,respectively.From the perspective of thermo-mechanical coupling,the prediction model established in this study allows for the quantitative characterization of the nonlinear and critical evolutionary patterns of calcareous clay strength with temperature,initial water content,and con-fining pressure during freezing.This model provides a theoretical basis and data support for analyzing the mechanical re-sponses of calcareous clay in low-temperature and high-pressure environments.
BackgroundWith the comprehensive advancement in intelligent coal mine construction, creating high-precision, transparent geological models of coal seams and their surrounding strata has emerged as a prerequisite for intelligent coal mining. The accurate identification of concealed geological anomalies, such as folds and faults, within coal seams represents a key challenge in safe coal mining. In-seam seismic exploration has become an important approach to detecting underground concealed structures owing to its advantages, including a considerable detection distance along coal seams, high precision, pronounced frequency dispersion effects, and facilitating the identification of waveform signatures. However, conventional methods for seam wave simulation are prone to errors when used to characterize undulating coal seam interfaces, producing negative impacts on the accurate identification of structures such as folds and faults. Objectives and Methods To investigate the propagation patterns and frequency dispersion characteristics of in-seam waves in complex coal seams more effectively, this study conducted 3D forward modeling of channel waves using the finite difference method on curvilinear grids. Based on the accurate characterization of the undulating coal seam interfaces using body-fitted grids, the spatial and temporal partial derivative terms were approximated using the DRP/opt MacCormack scheme and the fourth-order Runge-Kutta algorithm, respectively. Finally, the dispersion curves of the Rayleigh- and Love-type seam waves were extracted using the phase-shift method and were then compared with theoretical dispersion curves. Results and Conclusions Test results on the curved coal seam models bearing a fold or a fault demonstrate that, compared to the conventional finite difference method on regular grids, the finite difference method on curvilinear grids yielded in-seam waves with more continuous waveforms in simulation. Furthermore, the proposed method effectively suppressed the spurious scattering induced by the staircase approximation of undulating interfaces. All these enhanced the accuracy of the simulation results. Comparison indicates that the dispersion energy from simulation using curvilinear grids agreed better with theoretical dispersion curves and exhibited more continuous morphologies and smaller oscillations compared to that from simulation using Cartesian grids. These characteristics facilitate the accurate picking of dispersion curves. The finite difference method on curvilinear grids can significantly enhance the simulation accuracy of in-seam waves in undulating coal seams, providing a reliable foundation for forward modelling in practical in-seam seismic exploration.
ObjectiveMulti-layered fully mechanized top-coal caving mining represents a primary method for exploiting extremely thick coal seams. Quantitatively characterizing the damage patterns and fracture field evolution characteristics of the overburden in stopes subjected to high-intensity layered mining is critical to the safe production of coal mines. MethodsThe extremely thick B1 coal seam (average thickness: 53.59 m) in the No. 2 mine of the Dajing mining area in the Zhundong coalfield was selected as the engineering background. By integrating physical simulation using similar materials and numerical simulation, this study revealed the geometric and fractal characteristics of damage to the overburden during the multi-layered fully mechanized top-coal caving mining of the B1 coal seam. Furthermore, this study predicted and verified the height of the hydraulically conductive fracture zone in the overburden during the mining of various coal layers.Results and ConclusionsThe simulation results indicate that during the mining of coal seam B1, high-intensity mining in a super-large space induced significant breaking damage to the overburden. The controlling effect of key strata on fracture development gradually weakened with the mining of the upper coal layer, and fracture evolution differed significantly during the mining of varying layers. The fractal characteristics of fractures in the overburden were determined using the fractal theory. Specifically, fracture propagation in the overburden predominantly occurred during the mining of the upper and middle coal layers, while the fracture field tended to stabilize during the mining of the lower coal layer. The fractal dimension of fractures in the overburden increased, decreased, and stabilized sequentially. The fracture field in the upper coal layer exhibited a staged development trend, while those in the middle and lower coal layers showed nonlinearly decelerating growth trends. A backpropagation (BP) neural network-based multi-parameter prediction model was established to predict the height of the hydraulically conductive fracture zone. Consequently, the predicted height of this zone was 176.3 m, 294.5 m, and 340 m under the mining of the three coal layers, highly consistent with physical simulation results. The results of this study provide an effective reference for subsequent mining face design of the B1 coal seam, as well as the safety management and control of relevant stopes.
