Abstract:Deep coal seams are commonly characterized by high burial depth,dense coal-rock structures and relatively un-developed natural fractures,which together restrict permeability enhancement and efficient coalbed methane(CBM)ex-traction.Under such conditions effectiveness of conventional hydraulic fracturing is constrained by its tendency to gener-ate predominantly planar fractures.In contrast,supercritical CO2(ScCO2),owing to its small molecular size,low viscosity,and strong penetration capability can interact with coal micro-and nano scale pores and fractures in coal,thereby promot-ing the development of more complex fracture networks which facilitate additional pathways for gas permeation and mi-gration.This study integrates micro-computed tomography(micro-CT),acoustic emission instrument and morphology scanning to investigate the spatial distribution and propagation behavior of micro-fractures in deep coal from the Yan'an block following ScCO2 fracturing.Fracture spatial distribution characteristics under different stress constraints are system-atically examined.The controlling mechanism of fracture initiation and propagation associated with coal structure,in-situ stress conditions and ScCO2 characteristics in fracture initiation and propagation were analyzed.In addition,fracture mor-phology and heterogeneity are quantitatively characterized providing insight into governing mechanisms of fracture propagation and spatial distribution.The results indicate that the vertical stress difference coefficient(Kv)exerts a strong control on fracture initiation pressure.When Kv=0.4(sample 1-3),fracture pressures are approximately 25 MPa,whereas at is Kv=0.6(sample 4),the fracture pressure decreased to 16 MPa,indicating the increased Kv facilitates to the fracture ini-tiation.Following ScCO2 fracturing,extensive micro-fractures develop in coal,with complex geometries and enhanced connectivity,which is conducive to gas migration.ScCO2 preferentially accesses coal through relatively large pore-frac-ture channels and subsequently penetrates micro-nano scale pores and fractures.With increasing injected gas volume,the compressive effect of ScCO2 on the coal intensifies,leading initially to micro-fracturing;as ScCO2 accumulation pressure increases,fractures are progressively opened and coalesce into macroscopic failure.Owing to the ability of ScCO2 to pen-etrate coal across multiple scales and its relatively uniform distribution,the resulting fractures exhibit a wide spatial distri-bution.The fractal dimension of fracture surface roughness for samples 1-4 are 1.915,1.828,1.814 and 1.797 respectively.This indicates that the higher fracture pressures are associated with increased fracture surface complexity and stronger het-erogeneity.The coal structure,in-situ stresses and ScCO2 properties are the primary factors controlling fracture develop-ment and distribution in deep coal.These findings provide guidance for permeability enhancement for deep coal seams and coalbed methane reservoir transformation using ScCO2 fracturing.

Abstract:There are a lot of difficult coal resources in the residual mining areas in China.The shallow residual coal re-serves are considerable and have great mining value.Safe recovery can help the continuous supply of coal resources in China.Moreover,the long-term retention of residual coal is easy to spontaneous combustion,which threatens environ-mental safety and is difficult to dispose of.Consequently,adhering closely to the academic ideas of green mining and sci-entific mining,integrating backfilling mining with underground coal gasification(UCG),a technical approach is proposed for the critical domains backfilling synergistic UCG for remining shallow difficult residual coals.Through the critical do-mains whole process identification,backfill materials optimization and structural design,UCG space reconstruction,UCG for residual coal resources,and remining area monitoring as well as backfill comprehensive control,the safe,low-carbon,and efficient extraction of residual coal resources can be achieved by the technology system.Four key scientific issues re-quire resolution in critical domains backfilling synergistic UCG for remining shallow difficult residual coals:the instabil-ity and failure characteristics of coal and rocks in the residual coal occurrence space and the discrimination principle of critical domains,the thermal damage and high temperature resistance mechanism of backfill materials,the instability mechanism and bearing-seepage features of the coal,rock,and backfill in UCG,and backfill structure design and paramet-er optimization criteria.Four key technologies faced by critical domains backfilling synergistic UCG for remining shallow difficult residual coals include the multi-parameter identification technology for critical domains in the residual mining areas,the optimization technology of backfill materials,the chain catastrophe simulation technology of combustion cavity,and the parameter control technology of"backfill-gasification"in critical domains.The research contents of critical do-mains backfilling synergistic UCG for remining shallow difficult residual coals are as follows:the precise identification of critical domains and the scientific determination of backfill positions,the backfill material optimization and structural design,the instability characteristics and catastrophe mechanism of the distributed combustion cavity,and the rock strata stability control method of critical domains backfilling synergistic UCG.This technology is anticipated to realize the re-covery of shallow difficult residual coals and the reuse of mine solid waste simultaneously.This integrated approach can not only facilitate the advancement of UCG and rock strata control technologies but also ensures energy supply security for the nation.

Abstract:The phenomenon of coal spontaneous combustion necessitates a comprehensive investigation across multiple scales,where the significance of the individual coal particle as a crucial intermediary bridging micro mechanisms and macroscopic attributes is underscored.While existing research has extensively explored both micro and macro scales,a notable gap remains in the quantitative analysis and evaluation of the impact of particle-scale effects on coal spontaneous combustion.Firstly,governing equations were formulated to depict the internal temperature and oxygen concentration dif-fusion within individual coal particles,employing an equivalent spherical symmetry model and coal oxidation reaction equation under the third type of boundary conditions.By dimensionless processing of the mathematical model,analytical solutions for the dimensionless oxygen concentration and temperature distribution inside single coal particles were ob-tained,and mathematical expressions for the effectiveness factor used to determine the strength of particle scale effects were defined and derived.Furthermore,by comparing the results obtained from numerical methods with those derived from analytical solutions,the correctness of the analytical solutions has been validated.Subsequently,the influence of sev-eral key dimensionless criterion numbers on the internal dimensionless oxygen concentration distribution,temperature dis-tribution,and effectiveness factor of particles was analyzed.The findings revealed that the dimensionless oxygen concen-tration distribution is intricately linked to two dimensionless criterion numbers,namely the Thiele modulus and the mass transfer Biot number,while the dimensionless temperature distribution involves four dimensionless criterion numbers:the Thiele modulus,the mass transfer Biot number,the heat transfer Biot number,and the newly obtained criterion number.Notably,the effectiveness factor is solely contingent on the Thiele modulus and the mass transfer Biot number.When the Thiele modulus is less than 0.1 and the mass transfer Biot number is greater than 0.1,the effectiveness factor approaches 1.0,and the particle effect can be ignored.When the Thiele modulus is greater than 2.0,the effectiveness factor remains below 0.8,and the influence of particle effects should be considered.Engineers can leverage the proposed effectiveness factor formula to assess the relevance of particle-scale effects.These research outcomes form the cornerstone for a quantit-ative examination of the influence of micro characteristics of single coal particles on macro characterization,paving the way for the development of subsequent multi-scale simulation models.

Abstract:Diesel-powered vehicles,blasting operations,spontaneous coal combustion,external fires,and gas or coal-dust explosions are the primary sources of carbon monoxide(CO)in underground mines.These sources frequently trigger CO concentration over-limit alarms,posing serious threats to underground mines safety.At present,respiratory protection and mechanical ventilation are the main approaches for CO control.However,they merely isolate personnel from CO or dilute their volume fraction rather than actively removing it.As a result,their emergency removal efficiency and response capab-ility are limited,making it difficult to achieve intrinsic elimination of CO hazards.Since 2017,our research team has pion-eered a novel chemical CO removal method for underground mines,achieving a series of breakthroughs in material devel-opment,theoretical modelling,equipment design and engineering applications.Based on the previous research results,the connotation of the"source-based governance and environmental adaptation"technology for the CO chemical removal technology in underground mines is systematically presented.Three key performance metrics,namely CO removal effi-ciency,CO removal rate,and total CO removal amount,are proposed to quantify the performance of CO chemical remov-al technology.Based on the physical characteristics of filtration-type and spraying-type CO removal processes,combined with the CO oxidation reaction mechanism on the surface of the removal material,the theoretical models describing the dynamic evolution of the mine CO chemical removal process are established,achieving the quantitative description of the CO chemical removal laws.The CO removal tests for the exhaust gas of trackless rubber-tired vehicles and high-temperat-ure chambers are carried out.With 8.03 liters of removal material,the CO emission volume fraction during idle operation could be reduced to below 23×10-6.With a spraying amount of 100 grams of removal material,the CO volume fraction in the 200 ℃ chamber could be decreased from 2.5％to 0.09％within 60 seconds.The CO removal efficiencies all exceed 93％,confirming the effectiveness of the CO chemical removal method.Furthermore,the predicted evolution curves of CO volume fraction,CO removal efficiency,CO removal rate and total CO removal amount by the constructed theoretical model are in good agreement with the experimental results,with errors within 20％.Overall,the chemical removal meth-od for CO in mines has a promising application prospect.This work provides a theoretical basis for the proactive mitiga-tion of CO-induced disaster risks and the practical application of disaster emergency disposal.

Abstract:Against the backdrop of escalating global energy crises and driven by the national strategic imperative to en-hance domestic oil and gas supply,in-situ pyrolysis technology for oil-rich coal has garnered unprecedented attention in China due to its advantages of lower pollution,minimal geological disturbance,and high potential for large-scale deploy-ment.Nevertheless,the inherent challenges of drilling-based in-situ pyrolysis including non-visualized processes,person-nel inaccessibility,and complex subsurface reaction conditions,pose significant safety risks to coal production,constitut-ing critical constraints for large-scale technological deployment.A comprehensive understanding of oil/gas production characteristics and their combustion/explosion hazards,the regulation mechanisms of the in-situ pyrolysis reactions,the fracture propagation laws during pyrolysis,the oil/gas migration mechanisms,as well as the environmental impacts and corresponding prevention/control technologies,forms the essential foundation for ensuring stable operation and safety risk mitigation in in-situ pyrolysis of oil-rich coal.Nevertheless,key knowledge gaps persist:The characteristics of oil/gas pro-duction and their associated combustion/explosion risks remain unclear;The heat transfer laws and transport models with-in the pyrolysis zone are inadequate;and the migration patterns of oil/gas products under multi-field coupling effects are not yet fully elucidated.Building upon the refinement of these fundamental theories,the development of fracture-sealing materials capable of simultaneously preventing gas escape and stabilizing overlying strata,the exploration of sealing tech-niques for discontinuous fracture spaces,the invention of shielding/isolation technologies for pyrolysis reaction chambers,the advancement of an integrated air-space-ground multi-dimensional monitoring system with efficient data collection and processing,and the establishment of an intelligent and automated control system for the in-situ pyrolysis reaction are cru-cial for providing safety assurances for the technology's promotion.Although relevant theoretical,technological,and equipment research has been conducted globally,it has not yet fully addressed the pre-control safety requirements of the in-situ pyrolysis process for oil-rich coal.

Abstract:With the rapid advancement of intelligent mining in the coal industry,traditional water hazard prevention tech-nologies have proven inadequate due to low efficiency and insufficient precision,failing to meet the precise control re-quirements under complex geological conditions.To address these challenges,an intelligent water hazard prevention sys-tem for intelligent mining was proposed.The proposed framework establishes a closed-loop management system covering the entire process from data perception,model construction,dynamic evaluation,integrated governance to emergency re-sponse,significantly enhancing both proactive measures and reliability in water hazard prevention.Firstly,through intelli-gent geophysical exploration(including"long-digging and long-probing"technology),dynamic seismic detection during drilling,and a multi-source monitoring network integrating electrical,microseismic,and hydrological parameters across the"well-ground-hole"triad,the accuracy of anomaly boundary identification was significantly improved.Combined with real-time data processing and dynamic imaging,this enables precise detection of water-conducting structures ahead of working faces.Secondly,leveraging intelligent exploration and monitoring achievements,multi-attribute high-precision modeling technology was developed.By integrating borehole data,seismic information,and real-time drilling data,com-bined with regional stratigraphic analysis,segmented LiDAR scanning,global calibration algorithms,implicit iterative in-terpolation algorithms,and TIN-GTP grid modeling techniques,critical hazards like aquifers and collapse columns through parametric modeling was mapped.This resulted in centimeter-level 3D roadway models and comprehensive multi-attribute hydrogeological models,supporting spatial correlation analysis of water hazard risks and enabling dynamic up-dates to static geological models with transparency.Thirdly,utilizing attribute information such as water-bearing/interme-diate layers thickness,elevation,and hydrological monitoring data from the integrated mine hydrogeological model,we employed LSTM-GCN hybrid networks and Bayesian models.Through spatiotemporal information coupling algorithms,we evaluated flood risk assessment,achieved real-time prediction of mine water inflow sources,and conducted dynamic risk analysis via thermal maps of mine roof and floor water hazards.A dynamic evaluation system for mine water hazard risks was established.Subsequently,three innovative algorithms:A 3D geological model-based intelligent drilling traject-ory design algorithm,an AI-powered video-driven intelligent identification algorithm for water probing and drainage drill rods,and a natural language report template generation algorithm were developed.A digital hydrogeological information management system and a smart control system for disaster-causing water discharge and grouting were also established.Through spatial overlay analysis of 3D trajectories with coal seam structures,multi-objective optimization models,and ad-aptive control algorithms,integrated autonomous drilling trajectory generation,remote monitoring and trajectory optimiza-tion was achieved,as well as automated dynamic updates of design reports.The efficiency of water hazard prevention and control engineering was significantly improved.Finally,by implementing a dual real-time analysis feedback mechanism for geological and hydrogeological data in water hazard management projects,information updates drived by synchronize-ing mining engineering geology and hydrogeological data.Combining personnel positioning with dynamic tunnel model simulations of water surge propagation,a multi-constraint path dynamic optimization algorithm to rapidly generate dis-aster scenario simulations and rescue plans was utilized.Future research will focus on intelligent control platform for In-ternet of things and comprehensive smart systems,advancing water hazard prevention toward autonomous"sensing-ana-lysis-decision"processes to provide core support for coal mine safety production and intelligent construction.

Abstract:As shallow energy resources on Earth are progressively depleted,enhancing the capability to extract deep coal resources has become an inevitable trend in global scientific frontiers and technological development,as well as a stra-tegic choice to ensure China's long-term energy security.The solid fossil resource nature and inherent energy attribute of coal endowment.Coal-fluidized mining is a disruptive technology that aims to break through the depth limits of solid min-eral resource extraction.Its key lies in establishing a new theoretical and technical foundation for deep engineering sci-ence that can account for the influence of the in-situ occurrence environment in solid-mineral-resource-fluidized mining.Existing rock mechanics theories and methods struggle to incorporate the effects of the deep in-situ environment(current strength criteria,constitutive equations,etc.,are depth-independent and unrelated to the deep in-situ environment),mak-ing them inadequate for effectively guiding the development of fluidized mining technologies and disaster prevention and control.There is an urgent need to develop new theories and methods for in-situ rock mass mechanics that consider the multi-physics and multi-phase environmental influences in fluidized mining of deep coal resources.Establishing a theory of in-situ multi-physics and multi-phase rock mass mechanics is fundamental to achieving solid-mineral-resource-fluid-ized mining.Regarding the new theoretical system of rock mechanics that accounts for the influence of the in-situ occur-rence environment in fluidized mining of deep coal resources,four key scientific issues have been identified:① The dif-ferential laws of the intrinsic parameters of the occurrence environment at different depths in solid-mineral-resource-fluid-ized mining and the physical-mechanical behavior of rock masses;② In-situ rock mass mechanics theory that considers the multi-physics and multi-phase environmental influences in solid-mineral-resource-fluidized mining;③ Mechanisms of surrounding rock stability and strata control,as well as the genesis of dynamic disasters in solid-mineral-resource-fluid-ized mining;④ Topological structure and construction of negative-carbon backfill materials in solid-mineral-resource-flu-idized mining.Complementarily,five key technological issues are proposed:① Technology for acquiring intrinsic inform-ation on the in-situ multi-physics and multi-phase occurrence environment at different depths in solid-mineral-resource-fluidized mining;② Synchronous multi-parameter testing technology for rock mass deformation under reconstructed flu-idized mining environments of solid mineral resources;③ Intelligent numerical simulation technology for the multi-phys-ics coupled failure of surrounding rock in fluidized mining of solid mineral resource;④ Modification and performance regulation technology of negative-carbon backfill materials for solid-mineral-resource-fluidized mining;⑤ Negative-car-bon efficient backfilling technology for solid-mineral-resource-fluidized mining.Finally,based on the scientific and tech-nological issues,seven main research topics are delineated:① Principles and technology for in-situ testing of rock mass mechanical behavior at different depths in solid-mineral-resource-fluidized mining;② Methods and technology for syn-chronously testing multi-field and multi-phase rock mass deformation under reconstructed fluidized mining environments of solid mineral resource;③ In-situ rock mass mechanics theory and disaster prediction methods for solid-mineral-re-source-fluidized mining;④ Technologies for surrounding rock stability and safety evaluation methods in solid-mineral-re-source-fluidized mining;⑤ Fine acoustic wave detection technology for disaster sources ahead of roadways during excav-ation in solid-mineral-resource-fluidized mining;⑥ Negative-carbon backfilling and strata control technology in solid-mineral-resource-fluidized mining;⑦ Methods for preventing and controlling dynamic disasters in deep mining and en-gineering demonstrations.Based on the above,a theoretical framework of in-situ multi-physics and multi-phase rock mass mechanics for solid-mineral-resource-fluidized mining will be constructed,providing a theoretical foundation and techno-logical support for solid-mineral-resource-fluidized mining in the future.

Abstract:Circulating fluidized bed(CFB)boiler with low load operation is facing technical challenges,including high coal consumption amount,low main steam temperature,and extremely difficult satisfaction to ultra-low NOx emission reg-ulation of 50 mg/m3,which all severely limited the industrial application of the deep peak-shaving technology of CFB boiler.A new technological route was proposed and adopted in a 240 t/h CFB boiler,with two fluidized self-preheaters(heat capacity:24 MW)installed in the left side wall and right side wall,respectively.By coupling particle coal supplied into the main furnace of the CFB and pulverized coal supplied into the preheater,the upper temperature of the main fur-nace was increased,the reduction efficiency of NOx with preheated fuel was enforced,and the technical problems was ex-pected to be solved for CFB boiler with low load combustion.The investigation results show that the self-preheating tem-perature of pulverized coal in the preheater is higher than 800 ℃,and the stable operations separately in 25％load and 20％load were achieved.Also only with NH3 injection into the furnace,the NOx emission were 38.2 mg/m3 in 25％load and 47.5 mg/m3 in 20％load,satisfying the regulation of ultra-low NOx emissions.With the ultra-low load,the temperat-ure in the dense zone of the main furnace is over 750 ℃,creating a beneficial condition for high-efficient combustion of coal particles supplied into the CFB.When the boiler load being 25％,the outlet temperature of the main furnace is over 670 ℃,forming a technical scheme of stable,high-efficient,and clean combustion with ultra-low load.The experimental results provide important support for research development and industrial application on the deep and flexible peak-shav-ing of CFB boiler.

Abstract:In response to the challenges posed by complex surrounding rock conditions,high mining intensity,and signi-ficant strata pressure in coal mine mining-induced roadways-which often result in dynamic pressure phenomena such as roof collapse and large deformations-the mechanism of roof collapse has been systematically investigated.The direct causes and the mechanical essence underlying roof failures in such environments are revealed.Scenario-based models of roadway roof disasters have been developed,encompassing fractured hazardous rock falls,loose rock mass collapses,weakly bonded composite roof failures,and butterfly leaf-type roof collapses in severely deformed roadways.These mod-els clarify two primary categories of roof collapse:inherent defect type and mining-induced type.Guided by these find-ings,a suite of key technologies and equipment-each with independent intellectual property rights-has been designed to control roof collapse throughout the entire service cycle of coal mine roadways.These include a grading and positioning investigation method for roof disaster hazards,intelligent perception technology for roadway surrounding rock conditions and an intelligent decision-making system for support design,and a comprehensive hydraulic temporary support system for excavation,equipped with clustered frame-mounted bolt drilling rigs.Additionally,a novel"three-machine"coordina-tion model has been developed for excavation working faces,integrating a boom-type roadheader,a comprehensive excav-ation shield support,and a frame-mounted rail-bound bolt drilling rig.Further advancements include irregular variable-aperture drilling for enhanced anchorage,large-deformation impact-resistant tough anchor cables,and foldable non-re-dundant advance supports.Their research and development background,core innovations,and successful applications are further detailed.Collectively,these innovations address key issues such as the mechanisms of roof collapse under com-plex geological conditions,the positioning and early warning of potential roof hazards,and the implementation of full-cycle roof safety support.The resulting system enables visual and intelligent analysis of roof collapse risks and differenti-ated support design for various roadway conditions.This work holds substantial significance and broad application pro-spects for eliminating roof collapse hazards at their source,enhancing coal mine disaster prevention and control capabilit-ies in China,and safeguarding national energy security.

Abstract:Underground mining of coal resources induces movement and deformation in the overlying strata,significantly impacting the operation and maintenance of industrial square structures,mining area planning,and mine safety production.Revealing the differences in movement and deformation among bedrock,loose layers,and the surface,as well as their ver-tical deformation transfer characteristics,holds important practical significance for safe mining and subsidence control in mining areas.The Xinji mining area in the Huainan-Huaibei coalfield is selected as the research area.A distributed optic-al fiber sensing(DOFS)system was employed to construct a full-strata monitoring system.By combining three-dimen-sional physical similarity model tests with in-situ engineering measurements,strain characterization data were used to in-vestigate the vertical movement process,deformation distribution,and evolutionary characteristics of the entire strata dur-ing coal seam mining.The research reveals that the movement and deformation of bedrock,loose layers,and the surface exhibit non-integrated and discontinuous characteristics,with internal deformation in bedrock and loose layers displaying typical segmentation.The temporal deformation patterns vary significantly,the bedrock follows a"rapid-gradual-stable"subsidence pattern with fast deformation transfer;the loose layers display a"gradual-rapid-gradual-stable"response gov-erned by aquifer-aquitard interactions;while the surface subsidence shows a"slow-gradual-stable"subsidence pattern with non-uniform velocity.Further analysis indicates that the deformation transfer rate in the bedrock section is 4.8 times that of the loose layer section,while the deformation transfer time in the bedrock section is only 0.27 times that of the loose layer section.Field monitoring results show that in the total strata subsidence composition,the bedrock section contributes 78.4％,whereas the loose layer section contributes 21.6％.During coal seam extraction,the overlying strata are influenced by both layered sedimentary structures and dewatering effects.Tensile deformation within the strata is mainly concen-trated in the bed separation zones above the goaf and near the goaf boundaries,while compressive deformation is concen-trated in the abutment pressure-affected zones ahead of the coal wall.The findings enhance the understanding of the de-formation transfer mechanism in overburden strata under thick loose layers during coal mining.They provide data support and scientific guidance for transitioning from passive subsidence control to active subsidence and damage mitigation dur-ing mining operations.

Abstract:Deep coalbed methane(also known as coalrock gas)has become a crucial growth driver for increasing natural gas production in China.Practical experience has proven that high-yield production of deep coalbed methane requires large-scale hydraulic fracturing,and its extraction dynamics and development characteristics differ significantly from those of shallow coalbed methane.However,the key gas generation mechanisms and quantitative extraction threshold in-dicators remain unclear.Compared to shallow and intermediate coalbed methane,the research proposed that deep coalbed methane wells highlights three key differences in development geology-fracturing stimulation intensity and resource util-ization scope,imbibition and displacement effects,and production methods—due to the geological uniqueness of deep coalbed methane wells.Through physical modeling experiments,numerical simulations,mechanistic analysis,and field trials,it is the first to reveal the intrinsic mechanisms of post-fracturing soaking and controlled pressure production in deep coalbed methane.The research establishes critical quantitative indicators and optimization strategies for scientifically de-termining soaking duration,flowback,and post-commissioning control measures.A"five steps-six stages"regulatory sys-tem and development model for deep coalbed methane wells were developed and validated with significant field results.The research results indicate:① The scientific development concept of deep coalbed methane is to fully utilize the"permeation displacement displacement"effect of fracturing fluid through"reasonable well soaking,pressure control pro-duction,maintaining gas-liquid two-phase flow,and extending the self injection period",ensuring efficient use of re-sources within the SRV transformation range,maximizing the synergistic and efficient production of gas-liquid two-phase within the drainage volume(DRV),and ultimately achieving the highest estimated ultimate recovery(EUR).② During the fracturing and soaking process of deep coal seams,a significant gas-water displacement effect occurs.Based on imbibition-displacement NMR experiments,long-core pressure transmission experiments,and field-scale numerical simulations,the lower and upper limits of fracturing fluid soaking time were estimated to be 2.5 days and 15 days,respectively.Combin-ing Daji field practice,the reasonable soaking time for deep coalbed methane wells was comprehensively determined to be 3 to 11 days.③ Both microfluidic experiments and online NMR experiments demonstrate that during the flowback phase,the gas phase readily channels through dominant large pathways(gas channeling),leading to significant water phase reten-tion in secondary fractures.Higher effective stress increases water retention and reduces drainage efficiency,subsequently blocking gas flow pathways from matrix pores connected to these secondary fractures.Compared to rapid depressuriza-tion,stepwise pressure reduction establishes a virtuous cycle of"desorption replenishment from the adsorbed state-con-tinuous supply and production from the free state",nearly doubling the CBM recovery factor(from 41.6％to 80.7％).④ The conductivity of both self-propped and propped fractures decreases exponentially(by over 94％)within the effect-ive stress range of 5-20 MPa.Furthermore,once flow velocity exceeds a critical threshold,the conductivity of propped fractures suffers severe damage due to coal fines migration,proppant embedment,or flowback.This underscores the ne-cessity of controlled-pressure drainage to prevent damage to seepage pathway conductivity.Through a comprehensive analysis of multiple methods,it was determined that the single-layer backflow liquid production for vertical wells during the backflow phase ranges from 20 to 23 m3/d.Extending this to horizontal wells(taking 10 fractured sections as an ex-ample),the maximum daily liquid production should not exceed 230 m3/d.⑤ Through comprehensive numerical simula-tion and dynamic monitoring,the reasonable production system for different production stages has been clarified,and the daily gas production per kilometer(daily allocation production)in Daji field has been quantitatively determined to be 40 000 to 50 000 m3/d.It is recommended to control the pressure drop rate during the backflow stage,production stage,stable production stage,and decline stage within the threshold values of 0.6,0.7,0.04,and 0.07 MPa/d,respectively.⑥ Based on the experimental and simulation results of deep coal rock gas soaking and pressure control extraction,a new"five steps-six stages"full life cycle extraction system with"soaking diffusion to promote desorption,pressure control to stabilize flow and prevent closure,regulation to promote extraction and production,fine control to extend self jetting,lift-ing and unblocking to ensure stable production,and energy replenishment to control decline"as the core was constructed.Application of this system to 31 wells in the Daning Block confirmed that key production indicators-such as liquid pro-duction,gas production,and wellhead pressure-in the test wells were significantly superior to those in wells with almost no active soaking and produced under conventional aggressive methods at similar stages.After soaking time in the well 7-10 days and control method,the wellhead pressure increased from 6.45 MPa to 11.64 MPa,flowback efficiency im-proved from 20％to 30.1％,the predicted stable self-flow production period extended to 400-500 days,and the EUR per well increased by over 30％.The research results can provide important scientific theoretical basis for optimizing the ex-traction system of deep coalbed methane wells,improving single well production,and enhancing recovery efficiency.

Abstract:Lithology identification while drilling is an important geological guarantee means for transparent detection of coal mine geology.The traditional lithology identification method mainly relies on manual judgment,which relies on the accumulation of experience and professional knowledge and is subjectively affected.In recent years,intelligent lithology identification methods have emerged,which use machine learning lithology recognition models to intelligently identify li-thology,and the accuracy of lithology recognition by machine learning is higher than that of manual single drilling para-meters,but there is room for improvement.Based on this,this paper upgrades the comprehensive measurement system while drilling on the basis of the crawler full hydraulic tunnel drilling rig.Rock formations with different lithologic com-binations were tested while drilling.A two-parameter lithology discrimination system combining drilling parameters and natural gamma was established.In view of the shortcomings of traditional algorithms such as support vector machine,such as linear weight matrix,large number of required parameters,and limited feature extraction ability,the KAN network was applied to lithology intelligent identification.The results show that for the four machine learning algorithms,such as SVM,KNN,DT and KAN,the two-parameter discrimination system using drilling parameters and natural gamma can signific-antly improve the accuracy of lithology identification compared with the single-parameter discrimination method of drilling parameters or gamma parameters.In terms of machine learning algorithms,the KAN network improves the accur-acy compared with the other three traditional machine learning methods,which provides an effective method for accur-ately identifying the lithology of coal-bearing strata.

Abstract:Visual measurement is widely used for the position and orientation measurement of roadheaders in coal mines due to its simple system and non-contact nature.However,the accuracy of visual measurement is affected by the calibra-tion precision of camera parameters.The complex working conditions underground,uneven lighting,and hazardous areas lead to low calibration accuracy and difficulties in calibrating the cameras of the visual measurement system for roadhead-er position and orientation.To improve the automation level,calibration accuracy,and calibration speed of the camera cal-ibration in underground roadheader pose visual measurement systems,an online automatic camera calibration method for roadheader pose vision measurement systems is proposed.Using the infrared target of the roadheader pose visual measure-ment system as the calibration target,a virtual point-line feature is constructed on the target plane and its corresponding image plane based on the constraints of the conic pole-polar line and the invariance of the cross ratio in projective trans-formation of straight lines.This allows the mapping of point-line features between the target plane and its corresponding image plane.A camera parameter homography solving model based on point-line dual feature constraints is then estab-lished to solve the linear solution for the camera parameters.Considering the influence of lens distortion,the minimisation of the re-projection error for point features and the line-to-line distance error for line features are introduced.A combined objective function is established,incorporating dynamic weight coefficients and constraints.Using the linear solution for the camera parameters derived from the homography solving model as the initial optimisation value,a nonlinear iterative optimisation algorithm is applied for further refinement,ultimately obtaining the optimised camera calibration results.A simulation analysis was conducted to examine the impact of the number of calibration views and noise on the calibration accuracy of different methods.Compared to other approaches,this method achieves convergence of calibration error with fewer views and demonstrates better noise robustness.An experimental platform for roadheader pose visual measurement was established,and camera calibration experiments were conducted using different methods.This method was applied to complete the pose measurement experiment.The results show that the camera parameters obtained using this method have a small error compared to the true values.The relative errors for fx,fy,u0,v0,k1 and k2 are 1.155%,1.144%,0.463%,0.450%,1.887%,and 4.082%,respectively.The average re-projection error is 0.197 pixel.The pose measurement experi-ment verified the effectiveness of the calibration method and successfully achieved online camera calibration for the un-derground roadheader pose visual measurement system,and provides an important support for high-precision pose visual measurement.

Abstract:The high-precision three-dimensional spatial data required for areal subsidence monitoring in mining areas are provided through the application of airborne Light Detection and Ranging(LiDAR)technology.However,challenges such as densely distributed surface features,abrupt terrain gradients,and high similarity in elevation characteristics between surface objects and ground points in complex mining scenarios significantly degrade the accuracy of existing point cloud filtering methods,severely limiting the precision of ground point extraction and the reliability of subsidence monitoring.To address these issues,an adaptive filtering method based on bending energy optimization is proposed for airborne LiD-AR point clouds in mining areas.It achieves accurate ground point extraction in complex mining scenarios and provides high-precision three-dimensional spatial data support for monitoring areal subsidence in mining regions.Firstly,potential seed ground points are extracted using a one-dimensional discrete smoothing spline method,and residual non-ground points are eliminated through multi-scale morphological opening operations.Secondly,a quantitative relationship between terrain bending energy and rebound ratio is established to develop an adaptive cloth stiffness adjustment method for com-plex terrains,enabling the dynamic generation of high-precision reference terrain.Finally,precise ground point extraction is achieved by determining elevation difference thresholds between points and the reference terrain.In order to verify the effectiveness of the proposed method,multi-scenario experiments are carried out in complex mining areas,and the results show that the proposed method had significantly lower errors than the existing method in terms of class I and class II er-rors,with an average total error of 6.08%,which was 49.04%lower than that of the existing methods.The challenge of high-precision ground point cloud extraction in complex mining scenarios is successfully resolved through this method,enabling reliable data support for safety monitoring tasks including areal subsidence monitoring and slope stability analys-is in mining areas.Technical support is simultaneously provided for establishing an integrated sky-air-ground intelligent monitoring system dedicated to mine safety.

Abstract:In view of the lithology identification technology problems encountered by mine drilling rigs in the process of drilling construction,a lithology identification method based on Ensemble Empirical Mode Decomposition(EEMD)and Product Neural Networks(PNN)optimized by Differential Evolution(DE)algorithm is proposed,which combines the vi-bration signals collected behind the bit when cutting rock.Firstly,Synthesizing drilling simulation signals by using sinus-oidal signals with different amplitude-frequency characteristics,the high-frequency high-energy signal with amplitude of 10 g(g is the acceleration due to gravity,where 1 g ≈ 9.8 m/s2)and frequency of 50 Hz and the low-frequency low-energy signal with amplitude of 5 g and frequency of 20 Hz are respectively selected to represent the rock and coal seam en-countered by drilling.The modal decomposition results of Empirical Mode Decomposition(EMD)and EEMD with mul-tiple Gaussian white noise are compared,verifying the application effect of EEMD in solving modal aliasing;Then,the 1 s-long vibration signals of coal cut,mudstone cut and sandstone cut from a mine in guizhou province,China were decom-posed by EEMD,the spectrum analysis was carried out to obtain the corresponding amplitude-frequency characteristics,The first 7 Intrinsic Mode Function(IMF)components were selected as the characteristic modes,the characteristic vectors of 14 parameters were constructed by normalizing the energy and singular value decomposition.Finally,160 groups of 1 s-long vibration signals of cutting coal,cutting mudstone and cutting sandstone from a mine in guizhou province,China were constructed with characteristic vectors,and the DE-PNN was input for training and verification of identification ef-fect,the optimized neural network has significantly improved the lithology recognition rate of the remaining samples.The results show that the vibration signal of cutting rock can be processed by probability neural network optimized by EEMD decomposition and DE algorithm,and lithology identification can be carried out efficiently,quickly and accurately,providing new reference significance for further lithology identification and better guiding the development of mine drilling.The results show that the vibration signal of cutting rock is processed by EEMD decomposition and probability neural network optimized by DE algorithm,which can identify lithology efficiently,quickly and accurately.It provides a new reference for further lithology identification and better guide the development of mine drilling.

Abstract:When the upper part of coal-bearing strata is covered by the thick unconsolidated layer,the boundary area of the subsidence basin induced by coal mining exhibits a distinctive phenomenon of range expansion and slow convergence.In order to fully understand the evolution characteristics of mining surface subsidence in the outer boundary area of subsid-ence basin,and build the surface subsidence prediction model under the thick unconsolidated layer.Taking the 13121up working face of Gubei Coal Mine as an example,the dynamic evolution process of surface subsidence convergence effect the outer boundary area of subsidence basin and its range expansion are analyzed using the measured data,and the correla-tions between surface subsidence characteristics and geological mining conditions are investigated.On this basis,the influ-ence mechanism of unconsolidated layer thickness on surface subsidence characteristics is revealed.Then,the modified surface subsidence prediction model is proposed by integrating the Logistic function,and the parameters inversion meth-od of the modified prediction model is proposed based on the whale optimization algorithm.Finally,the impact of geolo-gical and mining conditions on the new parameters of the modified model is discussed.The results show that the surface subsidence convergence in the outer boundary area shows a clear segmented nature,and the convergence effect in the fast convergence zone rapidly converges and then slows down as the mining degree increases,the outer boundary area expan-sion undergoes a process of sharp expansion,then steady expansion,and finally slight contraction.The maximum surface subsidence value,the slope of subsidence convergence effect coefficient in the fast convergence zone,and the outer boundary area expansion range are linearly correlated with the buried depth,mining height,mining degree coefficient and the proportion of unconsolidated layer in the overlying rock.The additional subsidence caused by the full compaction of broken rock,the reduction of mining subsidence consumption,the compression of unconsolidated layer medium and the consolidation of aquifer water loss is the main reason for the special subsidence phenomenon of boundary area in the thick unconsolidated layer subsidence basin.The modified surface subsidence prediction model can effectively solve the prob-lem that the predicted results of the probability integral model converge too fast in the outer boundary area while restoring the actual physical significance of the subsidence coefficient q.The new parameters of the modified model gradually de-crease with the increase of unconsolidated layer proportion and burial depth,and fluctuation increase with the increase of mining degree coefficient,but are not significantly affected by the changes of mining height.The application of the modi-fied prediction model to the engineering practice of the 13121up working face of Gubei Coal Mine has achieved good res-ults.These research results will provide a scientific basis for the coal mining design under buildings,water-bodies and rail-ways in the thick unconsolidated layer condition,and promote the coordinated development of resource exploitation and farmland protection in the area where coal and grain coexist in Huainan and Huaibei.

Abstract:Biomass resources are abundant,carbon neutral and a sustainable alternative to fossil fuels.The development and use of biomass resources is an important part of the revolution in energy production and consumption.Low-temperat-ure carbonization is an effective biomass pre-treatment,which can achieve efficient biomass utilization.Corn straw was selected as the experimental raw material,and initially pretreated by hydrothermal carbonization and dry torrefaction in the temperature range of 180-240℃.Subsequently,a comprehensive analysis of alkali metal migration in the raw material and torrefied charcoal was conducted through the use of microwave digestion and chemical fractionation.The findings in-dicated that the total potassium content decreases with increasing torrefaction temperature,accompanied by a shift in the potassium's form from water-soluble to ion-exchangeable.The effect of the baking process on the pulping performance of biomass particles was examined following the mixing of torrefied charcoal with coal for pulping,and the correlation between alkali metal migration and pulping performance was further analysed.The results showed that the multifunction-al slurry,prepared from torrefied charcoal and coal by dry torrefaction,exhibits superior flowability and lower apparent viscosity compared to hydrothermal carbonization.The lowest apparent viscosity of the slurry was observed at 469.31 mPa·s,at a concentration of 56%and a torrefied charcoal blend of 10%.This was due to the reaction of potassi-um in the water-soluble state with the carboxyl functional groups on the surface of the particles,resulting in the formation of potassium carboxylate salts.This phenomenon resulted in a reduction in the number of hydrophilic groups and a relat-ive increase in the hydrophobicity of the particles,which in turn enhanced the fluidity of the slurry and reduced the viscos-ity.

Abstract:Water inrush accidents caused by weakly cemented filling fault fracture zone often occur under mining disturb-ance and groundwater seepage,posing a great threat to deep resource exploitation.The characteristics of cemented filling within the fault fracture zone directly control fluid migration and the formation of seepage channels.Identifying its impact on the seepage characteristics of fault fracture zones is of great importance in revealing the mechanism of water inrush from faults.Therefore,triaxial seepage tests were conducted on fault fracture zones with different Talbot function power exponent n values.CT scanning was used to analyze the microstructural changes of the fault fracture zone before and after seepage,and numerical simulations based on CT scanning data were conducted to study the seepage characteristics within weakly cemented filled fault fracture zones.The research results indicate that confining pressure affects permeability by altering the structure of fault fracture zones.The increase in confining pressure leads to the compression of pores and frac-tures within the fault fracture zone,and the permeability coefficient of weakly cemented filled fault fracture zones de-creases with increasing confining pressure.The internal connectivity and permeability of the fault fracture zone is better and higher with the higher of the Talbot function power exponent n and rock content.Conversely,the porosity and pore connectivity of the fault fracture zone is lower with the lower value of the Talbot function power exponent n.Groundwa-ter seepage will reduce the spherical pores inside the fault fracture zone and increase the flat pores,leading to the gradual formation of seepage channels.Moreover,the changes in the azimuth and inclination angles of pores within the fault frac-ture zone can reflect alterations in the internal seepage pathways.Under the action of groundwater seepage,dominant seepage channels will gradually form between the skeletons of fault fracture zones,leading to the formation of water in-rush channels.The Talbot function power exponent n value has a significant impact on the water inflow of water inrush through the fault fracture zone.The water inflow of water inrush exhibits a trend of first increasing and then decreasing with the increase in the Talbot function power exponent n value.

Abstract:The construction of transparent mines is critical to the implementation of intelligent coal mining in China.Lim-ited by current theories and technologies of geological exploration and multi-field fusion-based identification,the preci-sion,accuracy,and timeliness of existing mine geological hazard risk identification still cannot meet the requirements of transparent mine construction in the new era for the application of multi-source geological information data.On the basis of summarizing the development of techniques such as seismic-electrical joint inversion,borehole-surface joint inversion,multi-wave and multi-attribute joint dynamic inversion,and multi-source,multi-scale,multi-physical-field joint inversion,this paper proposes the concept of a"three-scale-three-resolution-one-model"transparent mine.The three scales refer to the mine area,the mining district(resolution of 3 m),and the working face(resolutions of 0.5 m and 0.1 m),while the"one model"refers to a transparent geological model that is unified in space and time.A multi-source heterogeneous data management scheme is designed,including standardized acquisition,cleaning,annotation,and lakehouse-based integrated management of multi-source and multi-modal mine data,providing highly reliable data support for geological large mod-els.A dynamic identification technical framework for mine geological hazard risks is proposed,comprising five core com-ponents:real-time perception and aggregation of multi-source and multi-field information,comprehensive integration and processing of multi-field geophysical data,multi-field joint inversion,feature construction and dynamic identification,and early warning,model updating and interaction with large models.Through a closed-loop workflow of"data sensing-data processing-multi-field inversion-feature construction-dynamic identification-feedback optimization",the framework en-ables continuous perception and intelligent decision-making for mine geological hazard risks.In addition,the key tech-niques for constructing typical mine geological hazard risk identification models are systematically elaborated,including six types of models:surface geophysical multi-field joint inversion and identification,in-situ while-drilling detection and identification in development roadways,coal-rock layering and structural identification at fully mechanized faces,gas-re-lated geological identification,water-rich geological identification,and dynamic identification of geological structures un-der disturbance conditions.The study provides new theoretical and technical support for building an intelligent,transpar-ent,and reality-based transparent mine geological cloud platform.

Abstract:Coal mine water damage frequently results in severe casualties,significant property losses,and reduced recov-erable mine reserves.It can also precipitate secondary disasters like ground subsidence and collapse,making accurate pre-diction and forecasting of coal mine water hazards a critical area of research for mine water damage prevention and con-trol.Despite recent advancements in coal mine water hazard prediction technology,there remains an urgent need for new detection techniques to meet the requirements of safe,efficient,intelligent,and green mining operations for quantitative and precise water hazard assessments.Magnetic Resonance Sounding(MRS)is the only geophysical method capable of directly and quantitatively detecting water.However,the surface nuclear magnetic resonance method(SNMR)is limited by shallow detection depth,weak anti-interference capabilities,and poor delineation of water-bearing body boundaries.To address these limitations,the surface-tunnel nuclear magnetic resonance method(STNMR)is proposed,based on the SN-MR and incorporating the practical construction methods of underground coal mines.This method involves placing a large-size transmitting loop on the surface and a multi-turn receiving loop underground.Firstly,the theoretical derivation of the STNMR method was conducted.Based on the conventional aquifer model,the response characteristics and the distribu-tion law of the kernel function of the STNMR signal were analyzed.Through numerical computation,the theoretical sig-nal strength and effective detection depth of the STNMR method and the SNMR method were compared and analyzed.The results indicated that in the aquifer with a burial depth exceeding 150 meters,the STNMR method exhibits a higher amplitude response signal,and its detection depth is nearly twice that of the SNMR method.Subsequently,numerical sim-ulation calculations were performed for the water-bearing bodies of the roof of coal seam and the floor of coal seam,em-ploying three data acquisition methods:synchronous data acquisition(SDA),fixed-receiver data acquisition(FRDA),and fixed-transmitter data acquisition(FTDA).The E0 multichannel results were utilized to assess the capacity of different data acquisition methods in delineating the boundaries of the water-bearing bodies.The findings show that the SDA method has a slightly weaker ability to distinguish the center of the water body in the roof of coal seam and the boundary of the water body at the floor of coal seam.In contrast,both the FRDA and FTDA methods demonstrate good performance in identify-ing the center and boundaries of the water bodies in the roof and at the floor of coal seam in the lateral direction.Finally,the 1D inversion of free induction decay signals for various layered models and the proposed Quasi-2D inversion for the water body model of the roof and floor of coal seam were carried out using the 1D Occam's inversion algorithm.The abil-ity of quantitative detection of water content in the rock layer by STNMR is verified.