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The combustion of coal for power generation is accompanied by the production of large amounts of pollutants and greenhouse gases. Therefore, the development of new green power generation methods for coal is of great significance. Hydrovoltaic power generation technology is a novel type of power generation mode that utilizes the interaction between materials and fluid interfaces to generate electrical energy. Increasing interests have been devoted into this area in recent years due to its economical and low-cost merits. This paper presents a novel coal powders (CP) based hydrovoltaic power generator. By regulating the oxygen-containing groups on the surface of the coal powder through oxidation modification, the interactions between coal powder and water molecules can be effectively improved. Combining with a filtration method, modified coal powder/filter paper composite was prepared to assemble a steam-based hydrovoltaic power generator. When the device is immersed in the solution, the water would flow through the bottom of the coal powder/filter paper composite membrane, driven by the effects of evaporation and capillary force. During which, water molecules dissociate continuously within the channels formed by the stacked oxidized coal powders. These negatively charged coal powders lead to the repulsion of anions while attracting cations inside the solution. As a consequence, an electrical double layer is formed on the surface of the coal powder-water flow interfaces. The directed flow of water causes a discrepancy in the migration rate between anions and cations, thereby generating continuous streaming potential. The oxygen functional groups on the surface of the coal powder were characterized using Fourier transform infrared spectrometer and a nanosize particle analyzer. The microstructure of the composite material was observed using scanning electron microscope. The power generation performance of the device was tested using a digital source meter. With the combination of asymmetric electrodes, it can generate a voltage of up to 0.72 V and an output current of 0.4 μA in pure water, with a maximum output power of 29.28 μW/m2. The power generator made from modified coal powder also overcomes the problem of decreased power generation performance in traditional hydrovoltaic generators in high-concentration salt solutions. It can still maintain a stable output voltage of 0.9 V in a 1 mol/L NaCl solution. By connecting multiple hydrovoltaic power generation devices in series, it can directly drive low-power devices, demonstrating its promising potentials.

As a global geo-environmental issue, land subsidence poses a severe challenge to urban safety and sustainable development. Traditional methods for land subsidence analysis face challenges in terms of speed and accuracy in big data processing and monitoring; it thus requires new approaches. Artificial intelligence (AI) technology, as a representative of new quality productive forces, offers advantages in data preprocessing, model construction, and trend forecasting. This paper aims to further integrate AI into the study of land subsidence through a literature review. Initially, the paper provided a background introduction to AI and analyzed its current application in the field of land subsidence. The application of AI in land subsidence from the perspectives of monitoring and early warning systems, as well as macroscopic and microscopic mechanism studies was then prospected, highlighting the potential of AI in improving efficiency and accuracy. Finally, this review analyzed the limitations of AI and proposed suggestions in the future. It states that the study on land subsidence requires further assistance from AI technology. A deeper integration of AI technology into land subsidence analysis will not only improve data processing capabilities but also provide new insights into the early warning and effective control of land subsidence, contributing to the advancement and development of the field of land subsidence.

The water dynamics of barrier lakes in high mountain areas are crucial for risk assessment, disaster prediction, safety management, and decision-making. Objective and Methods To accurately and efficiently extract the water boundaries of mountainous barrier lakes, this paper focuses on the Attabad barrier lake along the Karakoram Highway, proposing a water extraction method based on decision tree classification. This method incorporates slope information into six conventional water extraction methods for decision tree classification. The effectiveness of these six methods was compared for extracting water from barrier lakes in the experimental area. The best-performing methods suitable for barrier lakes in high-altitude areas were applied to extract the water body range of the Attabad barrier lake.Accuracy was assessed using a confusion matrix, and classification post-processing was performed to refine the water boundary extraction. Results The research results indicate that (1) among the six models, the CWI model demonstrates the best performance, effectively distinguishing between slope, water, and shadow water, leading to a highly accurate outline of the barrier lake. However, a limitation of this model is the presence of a few mountain shadows in the middle of the slope. (2) The decision tree classification method based on slope achieved an overall accuracy of 89.31% and a kappa coefficient of 0.84. It effectively extracts the actual water range, excluding slope shoreline and mountain shadows, and provides a clearer lake boundary. Nevertheless, black fragments observed in the lower area of the barrier lake, likely due to landslides and mountain shadows, remained challenging to classify. Overall, the decision tree classification-based method proved effective in identifying water bodies, particularly in areas with rugged terrain and numerous shadows. Conclusion This paper proposes a method for extracting water bodies from barrier lakes in high mountain areas using decision tree classification. By incorporating slope information into conventional water body extraction methods, this approach accurately extracts the water boundary, effectively eliminates shadows from steep slopes, retain shadowed water on gentler slopes, and improves extraction efficiently. The simplicity and high extraction efficiency of this method make it a practical solution for widespread application.

Significance To analyze the research trends and frontiers in the field of groundwater-lake interaction, we conducted a comprehensive review the relevant papers from the Web of Science (WOS) database. Using VOSviewer software, we mapped the developmental trajectory of research topics in the field. Core papers from both WOS and the China National Knowledge Infrastructure (CNKI) were analyzed to systematically summarize prominent topics, research tools, and existing gaps. Based on the historical development of the field, future trends were also predicted. Progress Our analysis identified three successive developmental stages in this field, including the individualism stage, the reductionism stage, and the holism stage. Current hot research topics focus on water exchange, solute transport, and ecosystem mutual feedback mechanisms. Several key challenges remain, such as the spatiotemporal heterogeneity of groundwater-lake interactions, biogeochemical processes at the groundwater-lake interface, and the delayed impact of aquifers on lake ecological restoration. The primary research methods are stable isotopes, radioisotopes, temperature tracing, remote sensing, and numerical modelling. However, variations in data accuracy and spatial coverage continue to pose challenges for the practical application of these techniques. Conclusions and Prospects In the future, this field will enter a fourth stage characterized by big data. At this stage, it is essential to integrate diverse technological approaches, with an emphasis on using big data for high-precision monitoring to improve the characterization of dynamic groundwater-lake interactions. Additionally, multidimensional inversion models of element migration should be developed, and enhanced data mining techniques should be applied at the interface to more accurately quantify solute transport flux across the groundwater-lake interface. Finally, fostering interdisciplinary collaboration and establishing a digital ecological framework will be essential to support research on the reciprocal interactions between groundwater and lake ecosystems, promoting sustainable development and environmental protection.

Flowback and early production of shale reservoirs usually show obvious characteristics of oil-water co-production after large-scale volume fracturing. Quantitative analysis of dynamic oil-water flowback and production has become a new method to explain fracture and reservoir parameters. However， the interpretation model and application of dynamic oil-water phase flowback and production are still insufficient at present. Based on the hypothesis of fracturing fluid occurrence after fracturing in shale reservoirs， this paper first established the flow equations of the water phase and oil phase considering fractures and then deduced the analytical solution and characteristic solution of the dynamic oil phase and water phase interpretation models by introducing pseudo-time and pseudo-pressure to linearize the equations. Finally， the paper developed a dynamic flowback and production interpretation method combining oil phase chart fitting and water phase linear analysis. The results show that in the log-log diagnostic curve， the oil phase flow exhibits linear flow in the stimulated zone with a slope of 1/2 and controlled flow at the stimulated zone boundary with a slope of 1， while the water phase flow exhibits linear flow in the fracture with a slope of 1/2 and controlled flow at the fracture boundary with a slope of 1. The established interpretation model of dynamic oil-water flowback and production can well explain the fracture and reservoir parameters. The half-length of fracture of the fracturing well， fracture conductivity， width and permeability of stimulated zones are well inversed based on the reservoir， fracturing， and dynamic data of a shale block in western China. Among them， the half-length of the fracture is in the range of 50-130 m； the fracture conductivity is in the range of 20-80 mD·m； the permeability of the stimulated zones is in the range of 0.01-0.05 mD； the width of the stimulated zones is in the range of 24-27 m. According to the inversion of fracture and stimulated zone parameters， the numerical simulation model of fractured horizontal well flowback and production is established. Moreover， the simulated output based on the interpretation results is in good agreement with the actual value， and the later predicted value is reasonable. The interpretation model of dynamic flowback and production established in this paper improves the dynamic analysis method of shale reservoirs and provides a basis for quantitative analysis of flowback and production characteristics of shale reservoirs， evaluation of fracturing effect， and formulation of efficient development countermeasures.

The fracturability of reservoirs is an essential parameter for selecting perforation stages and predicting hydraulic fracturing effects， but fracturability evaluation for tight sandstone reservoirs lacks unified methods and standards. This paper studies Chang 6 tight sandstone reservoir in an oilfield in the southeastern part of Ordos Basin and optimizes the characterization model of rock mechanics parameters based on the conventional logging data. The paper analyzes the relationships among reservoir rock brittleness， fracture toughness， in-situ stress difference coefficient， and daily fluid production， establishes the fracturability evaluation model and evaluation standard for tight sandstone reservoirs， and obtains fracture quality factor curves corresponding to logging curves. As a result， a high-precision logging evaluation method for the fracturability of tight sandstone reservoirs was developed. The results indicate as follows： ① The brittleness index is positively correlated with the fracturability， and the fracture toughness and in-situ stress difference coefficient are negatively correlated with the fracturability. ② The fracturing quality factor is greater than 25 for Class I reservoirs， indicating the best fracturability； it is easy to form a complex fracture network during fracturing and belongs to high-quality tight sandstone reservoirs. The fracturing quality factor ranges from 14 to 25 for Class II reservoirs， indicating medium fracturability； it is necessary to use fracturing fluid with low viscosity or keep high net pressure in fractures to form a better fracture network. The fracturing quality factor is less than 14 for class III reservoirs， indicating poor fracturability； an ideal fracture network is usually not formed during fracturing， and fractures are easy to close after fracturing. ③ Higher fracturing quality factors of tight sandstone reservoirs indicate better characteristics of artificial fracture morphologies and higher production capacity after fracturing. The evaluation results by the established model are more than 80% consistent with the microseismic fracture monitoring results and production testing results.

China is one of the countries in the world with the most frequent occurrence of continental earthquakes and the greatest impacts of earthquake disasters. In particular, the Qinghai-Tibet Plateau is a region characterized by a wide spatial distribution of continental earthquakes, shallow epicenters, complex seismic origins, and significant disaster losses, making it highly susceptible to seismic events. The need for seismic geological survey is becoming increasingly urgent in this area. Based on regional geological eological data，high-precision satellite remote sensing images and DEM elevation data，this paper interprets the active faults in the region of Xigaze. The results show that the active faults in the Xigaze area are mainly concentrated in the rift valleys and their periphery, with tectonic activity varying spatially. The tectonic activity of active faults in the eastern rift is stronger than that in the western rifts. Additionally，the tectonic activity of active faults in each rift also shows a clear segmentation feature. At the same time, this paper comprehensively considers the characteristics of active faults, topography and geomorphology and stratigraphic lithology in the Xigaze area. It preliminarily evaluates the potential risk of earthquake disasters in 204 towns under its jurisdiction. The results show that there are 57 towns with “extremely high risk” “high risk” and “high-medium risk” of earthquake disasters, accounting for about 28% of the total number of towns in the region.

Coal constitutes a pivotal element of China’s energy consumption structure. Xinjiang, which boasts considerable coal deposits, is a crucial energy succession zone and strategic reserve area within China. The coal resources in Xinjiang, particularly the Zhundong variety, typically exhibit elevated concentrations of alkali metals and alkaline earth metals (AAEMs), which are typical high-alkali coal well-suited for prolonged utilisation. The large-scale mining and utilisation of coal resources in Xinjiang has resulted in significant challenges, particularly in the form of slagging, staining and corrosion of high-alkali coal during combustion. These issues have severely limited the large-scale and efficient utilisation of this coal resource. The objective of achieving 100% clean combustion of high-alkali coal represents a significant challenge in the field of high-alkali coal utilisation. However, the primary obstacle lies in the resolution of the ash issue inherent to the clean combustion process. In this paper, about 4401 literatures in the field of high-alkali coal research in the past 20 years were obtained by using CiteSpace software. These literatures were subjected to literature clustering analysis, keyword highlighting analysis and time-series analysis. In addition, the peak interval of the heat of research in different periods was systematically analysed. It is highlighted that the future research in this field should prioritise the investigations into the existence form and migration characteristics of AAEMs, the low-temperature eutectic formation mechanism, and the development of combustion-efficient utilisation regulation measures. Based on a representative high-alkali coal, a summary of the fundamental physicochemical properties was presented, with a particular focus on the impact of the alkaline component of coal ash on the melting temperature of coal ash and the existence form of AAEMs. This study investigates the research progress of two core aspects, namely, AAEMs and low-temperature eutectics, with the objective of exploring the migration characteristics of AAEMs and the generation mechanism of low-temperature eutectics. This is of great significance for the clean and efficient utilisation of coal with low carbon. Subsequently, the regulatory measures for the efficient utilisation of high-alkali coal combustion are categorised into three principal groups: the reduction of AAEMs content, the increase of acidic components, and the optimisation of reactor operation and structure. The principles and effects of the utilisation measures on the mitigation of slagging and staining of high-alkali coals are then analysed, and the shortcomings of the corresponding methods are identified. Furthermore, it is proposed that the coal dust purification-combustion efficient utilisation technology may prove an effective means of solving the problem of efficient utilisation of high-alkali coal combustion. Ultimately, the dual-carbon context underscores the necessity for thermal power units to enhance their variable load regulation capabilities, thereby ensuring a stable power output. This paper puts forward suggestions and proposes avenues for future research in order to achieve the efficient utilisation of high-alkali coal combustion. It is essential that these are combined with local diversified resource advantages and that an overall plan is formulated in order to accurately control the problems of slagging, staining and corrosion throughout the entire process. This will enable the clean, efficient and low-carbon utilisation of the resource to be achieved.

In recent years, the global photovoltaic industry has been booming, and the installed capacity of photovoltaic has climbed rapidly. The carbon emission of photovoltaic power generation is only 10% compared with that of traditional fossil fuel power generation. However, the service life of solar photovoltaic panels is only 20 to 25 years, and as the first batch of photovoltaic modules reach their life limit, the world will successively usher in the "retirement tide" of photovoltaic modules. To realize the harmless and green disposal of retired photovoltaic modules and recycle the secondary energy in photovoltaic modules is the key link of the sustainable development of photovoltaic industry. At present, the mainstream crystalline silicon photovoltaic modules are composed of photovoltaic glass, EVA (ethylene-vinyl acetate copolymer) film, crystalline silicon cell sheet and fluorine backplane. The complete photovoltaic glass and crystalline silicon cell have high economic value, so how to selectively remove EVA film and fluoride backplate is an important step in the recycling of retired photovoltaic modules. Based on this, this paper first introduces the structure and application of each part of crystalline silicon photovoltaic module. Then according to the physicochemical characteristics of each part, the advantages and disadvantages of various processes including thermal disposal, physical separation and chemical dissociation are analyzed in detail from the perspective of the integrity of photovoltaic module recovery. Existing studies have shown that the difficulties in the recovery of retired crystalline silicon photovoltaic modules are mainly in the following three aspects: the removal of EVA film with high efficiency, low pollution and low energy consumption, the harmless disposal of fluorine-containing substances in the backplane, and the removal of pyrolysis carbon residues on crystalline silicon cells. In view of the above difficulties, this paper outlooks the future development trend of recycling technology for decommissioned photovoltaic module, and puts forward some reasonable suggestions on the research and design of recycling technology for decommissioned photovoltaic module in China. This paper will provide an important technical guidance for the efficient green recycling of decommissioned photovoltaic modules.

Overheating and the resultant tube failures of boiler high temperature heating surfaces such as waterwall is one of the sore major problems affecting the safe operation of coal-fired power generating units. Boiler tube overheating generally occurs at some localized areas of boiler heating surfaces. To alleviate tube overheating and avoid the resultant tube failures, it’s necessary to monitor the tube temperature distribution in real-time to make preventive boiler operation adjustment. Due to the limitation of measurement method and the huge time cost of numerical method, currently there are still lack of methods that can realize the real-time prediction of waterwall tube temperature distribution during boiler operation. Therefore, this paper integrated the coupled heat transfer model with neural network and established a typical database of a 350 MW supercritical boiler using the coupled model, which contains 220 different typical boiler operating cases generated by adjusting 46 key operating parameters. Then, 4 400 expansion cases were derived at extremely time cost by the quick expansion method proposed in this paper. The deep neural network model was then constructed with 46 boiler operating parameters and waterwall coordinates as the model input and the tube temperature at the corresponding locations as the output. The DNN model was trained based on the comprehensive database containing 220 typical cases and 4 400 expansion cases. The MSE of the DNN model on validation set was only 0.005 3, the AUC5 was 0.988 and the calculation time was within 0.1 s. It illustrates that the data-driven model realized the real-time prediction of the waterwall tube temperature distribution over the entire boiler operating conditions by means of generalizing the numerical simulation results of finite cases. In addition, a quick database expansion method was proposed to address the problem that the heat transfer deterioration is difficult to be accurately predicted due to the insufficient data of the heat deterioration, and the prediction accuracy of the heat deterioration problem was significantly improved. Both the accuracy and the response speed of the model meet the demand of coal-fired plants for a real-time monitoring of tube temperature distribution.

Based on the insufficient intelligent perception capability of coal mine heading face in China, this paper proposes a three-dimensional spatial mapping method of coal mine roadways based on multi-sensor fusion. This method utilizes 3D sensors such as LiDAR to capture and preview the environmental information of the coal mine roadways, and constructs a real-time autonomous mapping model to provide spatial perception information for large-scale coal mine heading equipment. By optimizing the Extended Kalman Filter algorithm based on the attitude perception theory and implementing the multi-sensor fusion technology, the method achieves fast updates of global maps and high-precision mapping in the geometrically degraded mine heading environment. The main contribution of this study lies in the fusion of multiple sensor data to construct a high-precision underground three-dimensional map and improve the intelligent perception capability and autonomous operation level in the mine heading environment. Firstly, some advanced LiDAR sensors are used to capture point cloud data within the mine heading face, extract point cloud features, and establish inter-frame feature mapping models to create a centimeter-level underground three-dimensional map. Meanwhile, by fusing data from LiDAR with inertial navigation using an iterated error state Kalman filter, the robustness of the system is improved, ensuring the accuracy and stability of the underground three-dimensional map. Additionally, this paper considers the influence of factors such as underground dust and water mist on the accuracy of three-dimensional spatial mapping of mine roadways. The Kalman filter gain is optimized to adjust the weight of LiDAR odometry, enhancing the environmental adaptability of three-dimensional spatial mapping under low dust concentration conditions. Experimental results show that comparing to the LeGO-LOAM and LINS, the proposed three-dimensional spatial mapping method outperforms in terms of trajectory estimation accuracy, point cloud quantity, and point cloud density in mapping the environment. The method presented in this paper can be utilized to achieve high-precision and fast-updating three-dimensional maps for autonomous mine heading equipment, thus improving the intelligence level of coal mine heading face and providing a data support for the intelligent perception and autonomous operation in the mine heading environment.

Reservoir numerical simulation technology is an important means of reservoir analysis， and it is a powerful tool for oilfield developers to design development schemes， proceed with dynamic tracking adjustment， and enhance oil recovery of reservoirs. In order to clarify the future development directions of reservoir numerical simulation technology in Shengli Oilfield， this paper reviewed the development process of reservoir numerical simulation application technology and independent intellectual property software in Shengli Oilfield over the past 60 years and summarized the innovative progress in numerical simulation application technology in many fields since the “13th Five-Year Plan in 2011-2015” period， which is applicable to current development and geological characteristics of Shengli Oilfield. The fields covered fine reservoir description in ultra-high water-cut stage， pressure flooding development in low-permeability reservoirs， heterogeneous combination flooding， multiple thermal combination flooding in heavy oil reservoirs， high-pressure CO2 miscible flooding， and integrated development of shale oil by large-scale fracturing. Then， this paper introduced the development and application of several reservoir numerical simulation software with Shengli characteristics， involving water flooding， chemical flooding， and micro and intelligent simulation. Finally， it was pointed out that under the current development situation of Shengli Oilfield， the reservoir numerical simulation is facing great challenges in terms of refinement， scale， efficiency， and collaboration approach， and the numerical simulation of reservoirs should be further developed towards integration， parallelization， and intelligence， so as to provide technical support for improving the quality and efficiency of Shengli Oilfield development.

The prevention and control of old kiln water in historical mines is a challenging problem in mine water management. In this paper, the typical manganese mining area in the manganese triangle area of China is selected as a case study. Objective In order to identify the sources of old kiln water and the causes of water pollution, Methods the technical approaches such as mine hydrogeological survey, hydrological analysis, hydrochemistry and isotope tracing are used to identify the source and characteristic pollution of old kiln water, and the causes of water pollution in the mining area is analyzed. Results Results show that, the hydrological response of old kiln water in the study is sensitive to rainfall events. The old kiln water mainly comes from the rainfall collected by the roadway, dominant runoff channel and groundwater in the aquifer. The characteristic pollutants of mine water and roadway water are manganese and sulfate, and the characteristic pollutants of mine drainage are sodium and sulfate. Manganese and sulfate are mainly formed by the oxidation of pyrite and the dissolution of rhodochrosite. The leaching and infiltration of mine solid waste and the mixing of old kiln water are main causes of groundwater pollution, while the surface water is mainly affected by pollution of leaching and confluence from mine solid waste, roadway drainage and mine drainage. Conclusion The research results of this paper provide a scientific basis for water quantity formation and water quality evolution for mine water environment management.

Convolutional neural network (CNN) models are widely used in landslide susceptibility assessment due to their powerful feature extraction capabilities, and traditional CNN is no longer able to meet the requirements. Therefore, this paper proposes a multi-scale convolutional neural networks (MSCNN) model that can take into account deep and shallow features. By increasing the depth of the model and expanding the receptive field of samples, the MSCNN can tap deeper and more stable features to improve the reliability of landslide susceptibility assessment in complex scenarios. In this study, Shenzhen City is selected as the research area, and 12 landslide conditioning factors of landslides in Shenzhen City were selected based on systematic and representative principles. A multi-scale convolutional neural network landslide susceptibility assessment model is constructed and compared with methods such as multilayer perceptron (MLP), support vector machine (SVM), and random forest (RF). The results show that the AUC value (0.99) of the MSCNN model constructed in this paper is higher than that of MLP (0.97), SVM (0.91), and RF (0.85), which proves that the proposed MSCNN model has excellent prediction ability. The area of extremely high susceptibility in Shenzhen City is approximately 105.3 km², accounting for 4.98% of the total area of the study area, mainly distributed in Longgang District with steep slopes, sparse vegetation cover, and frequent human engineering activities. Slope, surface roughness, and surface relief are identified as the main conditioning factors affecting landslides in Shenzhen City. The landslide susceptibility mapping implemented in this paper reflects the current distribution of landslide disasters in Shenzhen City, providing data support and key technical support for future landslide disaster prevention and control in Shenzhen City.

With the development of arid and semi-arid regions in China, the hazards posed by collapsible sands to engineering construction have become increasingly significant. In order to investigate the collapsibility regularity and its influencing factors of sand soils, this paper focuses on the wind-blown sands at the southern edge of the Maowusu Desert. Initially, by controlling the single factor laboratory compression tests, the collapsibility regularity of wind-blown sand under different working conditions was investigated. Subsequently, using PFC3D (three-dimensional particle flow software) for numerical simulation of the laboratory compression tests on wind-blown sands, the paper explores the effects of different porosities and particle compositions on the collapsibility of sandy soils. The research results indicate that the collapsibility coefficient of sandy soils shows a trend of first increasing and then decreasing with pressure, reaching its maximum value at 150 kPa. With the increase in dry density or moisture content, the collapsibility coefficient of sand decreases. Compared to moisture content, dry density has a greater impact on the collapsibility of sandy soils. There is a positive correlation between the collapsibility coefficient of wind-blown sand and its porosity. The initial porosity of the collapsibility of the wind-blown sand on the southern edge of the Maowusu Desert is 0.425. When the ratio of particle content between 0.075～0.25 mm and 0.25～0.5 mm is 0.35∶0.65, the collapsibility of sandy soils is maximized. The research results comprehensively describe the entire process of laboratory compression tests on sand from macro to micro levels, revealing the collapsibility regularity and its influencing factors on wind-blown sand from multiple scales. This can provide a reference for engineering construction in the Maowusu Desert and provide certain ideas and basis for the research on particle flow numerical simulation of sand.

This paper presents a preliminary investigation of the instability and landslide of a road subgrade slope that occurred on May 1, 2024 along Mei–Da Expressway. The investigation method is on the basis of past investigation results and findings about instability and landslide of road subgrade slopes in Hong Kong. The Mei–Da Expressway subgrade was constructed by cutting and filling on mountainous slopes. The landslide occurred at a fill slope along a gully. The fill soil was excavated from local soil of completely decomposed granite (CDG). The paper tests the particle size distribution and liquid and plastic limits of the three CDG soil samples that were excavated from adjacent natural slopes. It then examines the stability of the fill slope with a simplified geological slope model. It further investigates the catchments before and after the road construction. It then presents a possible mechanism for the slope instability and landslide. The field observations by others can confirm this mechanism. The cutting and filling of the hillside slopes significantly changed the runoff paths of the three natural catchments above the road. The road can intercept the runoff along the three gullies and direct all the runoff into the fill slope. The large volume of rainfall water can erode and liquefy the fills, which can cause the instability and landslide of the road subgrade slope. There is an urgent need to further investigate this mode of road subgrade instability and landslide since it is not uncommon.

The situation of coal as the stabilizer guarantee the energy safety in China cannot be changed in the short term, and it will continue to face the problems of coal resource protection and the low utilization rate of coal-based solid waste. Through innovative mining methods, improving the recovery rate of coal resources and the large-scale disposal of coal-based solid waste, a new path is being paved for the green and sustainable development of the coal industry. Based on the in-depth research on the development status of coal mining technology, a new roadway excavation method of “excavation-backfill-retention” is proposed. This paper systematically discusses the scientific problems and key technologies of the “excavation-backfill-retention” construction method from three aspects: rapid excavation, continuous and efficient backfilling and safe construction of large-section roadways. The research results show that ① aiming at the engineering problems such as the fast excavation of large section roadway and the stability control of surrounding rock of heading face, three scientific problems are summarized: the matching mechanism between coal and rock characteristics and cutting parameters of roadway boring machine, the spatial transfer mechanism of overburden load and the deformation mechanism of surrounding rock, the interaction relationship between anchor/cable roof and support mechanism. The technology system has been built, which is based on the real-time sensing of the geological environment in the excavation area, the intelligent cooperative operation of the multi-process of falling, loading and transporting coal, the aging control of surrounding rock of the drilling anchor support together with excavation, the anti-leakage and ventilation optimization of the large section roadway. ② The scientific problems of continuous and efficient backfilling are summarized from the two aspects of timely construction of large section roadway bearing system and its bearing performance regulation, including the co-bearing mechanism of background coal anchor/cable, the hydration consolidation mechanism of multi-component solid waste base backfill materials, and the space-time evolution law of physical and mechanical characteristics of backfill are clarified. A continuous and efficient backfill key technology system with the core of safe and efficient backfill space construction, backfill material performance control and backfill material flow-consolidation perception has been established. The breakthrough of relevant theories and technologies can provide a theoretical basis for raw material selection and ratio design of backfill materials, additive development/selection and working performance control, excavation rate and backfill step optimization design, consolidation monitoring of backfill body, etc. ③ Based on the key problems of roadway safety and surrounding rock easy to break, sheet and damage in the whole life cycle, the paper elaborates three scientific problems: the spatial and temporal distribution characteristics of stress field of roadway surrounding rock, the evolution mechanism of roadway deformation and damage, the engineering quality monitoring and stability regulation theory of roadway surrounding rock. The key technology system is formed with the intelligent stability warning of the rock surrounding the roadway and the deformation control of the rock surrounding the roadway as the core. It is of great significance to conduct the scientific research and technical demonstration of the “excavation-backfill-retention” construction method in coal mines, and to realize the synergy of large-scale solid waste disposal, efficient coal pillar section recovery and rapid roadway excavation, which can promote the green and low-carbon transformation and development of the coal industry.

In order to systematically understand the various types of water hazards and standardize the management of water prevention and control work in coal mines, the National Mine Safety Administration in June 2022 extended the “three zones” management methodology for old goaf water prevention and control to more types of water hazards, such as roof water, floor water, and structural water. However, in the process of dividing the “three zones” of water prevention and control in coal mines, it is revealed that the water damage causing factors and water damage management situation are not closely linked with the division standard, and that technically different divisions are not made for different coal seams and mining areas, and there are inconsistencies in the scope of the division area, and the standardization and timeliness of the division results. Accordingly, combined with the purpose of water hazard prevention and control “three zones” division, compared the similarities and differences between the new and old “three zones” division work, this paper clarifies the degree of hydrogeological conditions survey, water hazard analysis, water hazard management as elements of the division principles, and determines the technical path of the division of the “three zones”. Combining the characteristics of five common types of water hazards in coal mines, the paper puts forward the division method of different types of water hazards, that is: surface water hazard should be divided according to the distribution and development characteristics of surface water bodies in the mining area and the degree of influence of atmospheric precipitation, landslides and other geological disasters in mining. The roof water hazard should be divided according to whether there is a strong water-rich aquifer, a medium water-rich but hydrostatic reservoir-rich aquifer, a loose aquifer. The floor water hazard should be divided according to the relationship between the thickness of the floor water barrier and the depth of the floor mine pressure damage zone in the coal seam pressure mining area, as well as the size of the floor water inrush coefficient. The old goaf water hazard should be divided according to the distribution range and amount of water in the mine and the surrounding mines. The structural water hazards should be divided according to the water-richness, water content, and water source conduction of geological structures and bad geological bodies such as faults, trap columns and caves in the mining area. The key points and difficulties of the division work include the clear division of time and space scope, the comprehensive analysis of division standards, the clear management responsibilities for the “three zones”, and the dynamic transformation of division results. On this basis, typical coal mines with various types of water hazards and complex hydrogeological conditions are selected as case studies. Following the principle of division, according to the division standard, the mineable zone, the slow mining zone and no-mining zone are divided by the method of separating coal seams and mining areas, and detailed explanations are given. The significance of carrying out the division of the “three zones” for water hazard prevention and control is clarified, which can enhance the comprehensive detection level, strengthen the prediction ability, and identify the direction of water hazard management in order to guide and standardize the division of the “three zones” for water prevention and control in the coal mines of China.

Land subsidence is a worldwide geological hazard. Differential land subsidence has posed the major threat to urban infrastructure, linear rail transit and underground space development and utilization, and also restricted the sustainable development of the economy and society. This paper systematically elaborates on the research progresses on land deformation acquisition, evolution mechanism and simulation of land subsidence, and focuses on the land deformation acquisition technology based on InSAR monitoring and multi-source deformation data fusion, as well as the correlation analysis, statistical analysis, machine learning and other methods to analyze the relationship between the evolution of land subsidence and various influencing factors based on geotechnical experiment and long time series observation data. On this basis, the advantages and disadvantages of land subsidence simulation models such as groundwater flow field-land deformation model, mathematical statistical model and machine learning model are explored. It is found that multi-source deformation data fusion can improve the spatiotemporal resolution of land deformation. The differences in geological structure, lithology, groundwater exploitation, and dynamic and static loads are factors contributing to the differential evolution of land subsidence. The difficulty in balancing the computational efficiency and interpretability of mathematical models for land subsidence is the main problem in simulation. According to the literature review, the current researches mainly focus on land subsidence caused by groundwater over-exploitation. This paper further proposes the future research directions for land subsidence, under the background of climate change, new hydrological condition and dataset, and based on the fusion of data through remote sensing and field observations, integrating the latest progress of InSAR, GeoAI, cloud platform and other technologies to reveal the evolution mechanism of land subsidence considering the climate change and anthropic activities and provide technical support for regional land subsidence prevention and urban safety.

Significance The micromigration of shale oil refers to the phenomenon in which oil is generated in organic-rich layers and expelled at short distances to adjacent, preferable porous and permeable, organic-lean layers in shale systems. Micromigration can effectively improve the oil content and quality of organic-lean layers, even surpassing some organic-rich shale layers based on the exploration practices. Therefore, it is necessary to conduct a systematic study on the micromigration phenomenon of shale oil. Progress Based on the current research progress, this paper first identifies the main tracers of shale oil micromigration, which include rock pyrolysis parameters, hydrocarbon components, biomarkers, NSO compounds, as well as isotopes. The fundamental principle relies on fractionation between migrated hydrocarbons and retained hydrocarbons based on their geochemical properties. Analysis revealed that micromigration can lead to a dispersed distribution of hydrocarbon generation activation energy in organic-lean shale layers, resulting in an earlier hydrocarbon generation threshold. Moreover, the accumulation of light hydrocarbons in a free state in organic-lean layers can further increase the difference of hydrocarbon components between generative units and in-source reservoirs, thereby affecting the oil-bearing and mobility characteristics of shale. Based on the effects of petroleum migration and geological zonation, this paper reveals that micromigration occurs throughout the entire process of hydrocarbon generation, expulsion, and retention. It serves as a bridge connecting all elements of petroleum accumulation within shale systems, influencing the differential enrichment of shale oil. Conclusions and Prospects Comprehensive geochemical and geophysical methods are effective ways to identify micromigration in shale systems and will provide a new perspective for revealing the dynamic differential enrichment of lacustrine shale oil.

Early detection and distinguish of mine fires can avoid or reduce casualties, property damage, and secondary accidents. There are no natural light sources such as sunlight, moonlight, starlight, and lightning underground, and the main factor affecting the recognition of mine fire images is the mine light source. Circularity can eliminate interference from circular light sources, but it is difficult to exclude interference from non-circular light sources. Rectangularity can eliminate interference from rectangular light sources, but it is difficult to exclude interference from non-rectangular light sources. In engineering practice, due to the different shooting angles of the camera, the image of the mine light source may deform and cannot present an ideal regular shape. It is difficult to eliminate the interference of the mine light source using circularity and rectangularity algorithms. It has been revealed that the area of the external connection graphic area of the flame image is significantly larger than the actual area of the image, and the external connection graphic area of the actual light source image of the mine, such as circular lamps, rectangular lamps, and square lamps, is approximately equal to the actual area of the light source image. In this study, a mine fire recognition and anti-interference method is proposed based on the internal concavity of image, the ratio of the target image area to the external connection graphic area of the image (i.e. internal concavity of image) is calculated, and the flames and mine light sources are distinguished based on the small concavity value in the flame image and the large concavity value in the mine light source image. The internal concavity method proposed in this paper is not affected by the distance from the camera to the detection target and the size of the image, the installation position and angle of the camera to capture the detection target, and the shape of the mine light source. It has strong adaptability and high recognition accuracy. The experiment shows that the internal concave recognition method calculates the maximum average difference between the mine interference light source and the flame image, with the smallest fluctuation and the best discrimination. It is also least affected by the camera’s shooting angle and distance, and has the strongest anti-interference ability, with an accuracy of 91.6%. The rectangular recognition method calculates the average difference between the mine interference light source and the flame image, with small fluctuations and good discrimination. It is less affected by the camera’s shooting angle and distance, and has average anti-interference ability, with an accuracy rate of 72.5%. The roundness recognition method calculates the minimum average difference between the mine interference light source and the flame image, with the highest fluctuation and the worst discrimination. It is less affected by the camera shooting distance and more affected by the camera shooting angle, and has the worst anti-interference ability, with an accuracy of 12.0%. Therefore, the internal concave recognition method proposed in this paper is superior to rectangular and circular degrees, with the best discrimination, minimal influence from camera shooting angle and distance, and the strongest anti-interference ability.

In order to further improve the intelligent control level of fully mechanized mining equipment in coal mines and achieve the normalized operation of intelligent mining face, this paper proposes the related concepts and system architecture of intelligent mining face driving control based on digital twin. The digital twin system of intelligent mining face is composed of physical equipment, virtual twin and virtual and real interaction model. The virtual model mapped with physical equipment is established by digital method to achieve the purpose of virtual and real interaction, intelligent decision, accurate control and dynamic evolution in fully mechanized mining equipment during operation. The paper expounds the normal operation requirements of intelligent mining face and related control difficulties of shearer, hydraulic support and scraper conveyor, and proposes the single-machine digital twin driving control architecture of smart mining face, including mechanism model, control model, twin data model and digital twin model synchronization and evolution. The method of digital twin virtual-real interaction is described, the Cyber-Physical System is used to guarantee the information interaction ability, and the knowledge model is used to solve the data congestion problem, which provides a real-time virtual-real interaction for the digital twin control system of intelligent mining face. A three-machine cooperative control method driven by the digital twin of intelligent mining face is proposed, including three-machine correlation, intelligent coal mining control, intelligent support control and intelligent transportation control. Finally, taking the practical application of digital twin in mines as an example, the intelligent control of digital twin is verified by establishing the relevant model and designing the relevant experiment scheme. By carrying out theoretical research on digital twin intelligent control architecture and mode, the paper aims to solve the current problems of low environmental perception, poor equipment prediction accuracy and high manual intervention intensity in fully mechanized mining face, realize an adaptive control and human-computer interaction of equipment under complex environmental conditions, and provide a reference for the intelligent construction of coal mines.

Jiyang Depression， as one of the mature exploration areas in Bohai Bay Basin， has been explored and developed for over 60 years. It is urgent to solve the theoretical understanding problems such as oil and gas resource potential， exploration direction， and accumulation law to realize the sustainable development of oil and gas exploration. The evolution process of hydrocarbon generation and hydrocarbon generation potential of different types of source rocks were compared based on the analysis and testing of the sedimentary environment and organic geochemical characteristics of a large number of source rock samples in the primary hydrocarbon-generating strata and the hydrocarbon generation simulation experiment. It is found that the source rocks in the saline environment have the characteristics of high ancient productivity and low activation energy， and a “saline and hydrocarbon-rich” of hydrocarbon generation and expulsion mode was established in the continental lake basin. It breaks through the traditional understanding that source rock in freshwater environments is the primary source of oil and gas. It is pointed out that “strong cementation in early stage and strong dissolution in late stage” are the essential reasons for the formation of a large number of secondary dissolution pores in the deep reservoirs by analyzing the relationship between porosity and acid-base properties of formation fluid during diagenetic evolution of deep reservoirs. The genetic problem of effective reservoirs of deep clastic rocks under a high geothermal background is solved. The paper summarizes and puts forward the orderly distribution of lithology， structure-lithology， lithology-structure， and tectonic reservoirs from subsag to slope zones based on the exploration practice in Jiyang Depression. Therefore， the theoretical understanding of refined oil and gas exploration in mature exploration areas of “saline and hydrocarbon-rich， acid-base control， and orderly accumulation” has been innovated， and the potential of remaining resources has been defined. The direction of deep exploration has been pointed out， so oil and gas exploration has changed from passive transfer to active exploration. The division and optimization method of the “exploration layer unit” suitable for the refined exploration stage is innovatively established， and a “seven-step” refined exploration and evaluation process is formed for mature exploration areas. The paper points out the critical exploration directions and fields with increasing reserves in the future， which provide essential guarantees for the long-term benefit and sustainable development of the oilfield based on the new geological understanding of Jiyang Depression and the results of the latest round of oil and gas resource evaluation.

In response to the strong multi-solution problem of conventional seismic exploration methods in geological sweet spot prediction of shale， this paper fully explored one-dimensional whole rock analysis data and well logging data， two-dimensional geological data， three-dimensional post-stack seismic data， and five-dimensional offset vector tile （OVT） orientation information. In addition， the paper researched geological sweet spot identification technology of shale based on fuzzy fusion prediction to improve the accuracy of geological sweet spot prediction of shale. Firstly， the approximate distribution direction of faults in the study area and the distribution area of favorable shale lithofacies were statistically analyzed， and the sensitive azimuthal section was selected to stack the OVT data based on azimuth. Then， the fractures on the plane were analyzed based on pre-stack preferred azimuth， and the two-dimensional prediction of favorable shale lithofacies was carried out using a feedforward neural network. Finally， a fuzzy fusion technology based on an improved Sigmoid and Takagi-Sugeno （TS） function was developed， which could weigh the significance of controlling factors in geological sweet spot identification of shale according to their degree of influence and effectively integrate the predicted results of azimuthal anisotropy fractures on the plane with those of neural network-based shale lithofacies， so as to realize decision-making integration for identifying geological sweet spots of shale. This technology has been applied in the classification and grading evaluation of geological sweet spots of shale in the Lower Submember of the 3rd Member of Shahejie formation （Es3U） in Bonan Depression. Areas with poorly developed fractures and unfavorable lithofacies that could interfere with the analysis of geological sweet spots of shale were filtered out. Based on the predictions of fractures and lithofacies， The geological sweet spots of shale in the study area were categorized into three classes. The areas characterized by the superposition of developed fractures and favorable lithofacies were classified as sweet spots of Class I， which showed a high degree of consistency with actual drilling results and achieved notable application effects. The research results indicate that the classification and grading evaluation can be achieved using the geological sweet spot identification technology of shale based on fuzzy fusion prediction， which improves prediction reliability and provides reliable technical support for shale oil exploration.

Pulverized fuel ash (PFA) is a by-product from coal-fired power plants. The generation of PFA is huge and increases yearly. A large amount of untreated PFA is harmful to the environment, and it is also a waste of resources. Recycling PFA as construction materials would improve resource utilization efficiency, reduce environmental risks, conform to the demand for high-efficient and low-carbon utilization of solid waste and help to achieve the national strategy goals of carbon peak and carbon neutrality. The utilization efficiency of PFA as construction materials could be improved by optimizing production processes and developing new technologies, which would promote its large-scale and high-value utilization. In this paper, the general situation and physical and chemical properties of PFA are summarized. Various value-added utilization technologies of PFA as construction materials, including raw materials for cement production, supplementary cementitious materials, bricks and blocks, artificial aggregates, glass-ceramic materials, fire-resistant insulation materials, and new intelligent construction materials are comprehensively reviewed. This paper also introduces the research status of the utilization of PFA in construction materials, analyzes the applicability of different technologies, summarizes the latest technologies for preparing the PFA-based green construction materials and challenges faced in future research, provides detailed introductions to the mechanism of PFA application, and proposes thoughts on the problems existing in the utilization of PFA as construction materials. Finally, the further perspectives of the development of the PFA-derived low-carbon construction materials are highlighted. The study suggests that the “traditional large-scale consumption of PFA” and “high-value utilization of PFA” should be researched in parallel, and theoretical research and engineering practice should support each other, which would provide some scientific references for the sustainable management of PFA.

Surface mining is an important way of mining mineral resources. The state and local governments have put forward higher requirements for surface mining in China. Therefore, it is particularly urgent to take surface mining as a science to carry out systematic research, reveal the laws of mining process and phenomenon occurred, and make scientific explanations. First of all, the major technical achievements in the field of surface mining of solid mineral resources in China in the past 40 years were summarized from three aspects: the basic theory of surface mining, the development of key complete sets of equipment and blasting engineering technology. Then, the modern scientific metrology and information metrology technologies were used to conduct a multivariate dynamic analysis of 7128 papers and reports in the past 40 years, and a multi-dimensional quantitative description of the development and evolution process of the main research topics, including the time dimension, was carried out by the cluster analysis. It is found that the evolution of research topics is the result of the coupling effect of many factors, such as technological development, mining status, policy environment, etc. Based on the sorting of the existing major scientific and technological achievements and the objective literature measurement results, it is pointed out that the goal of the future surface mining science is to form a systematic and comprehensive safe, green, efficient and intelligent surface mining technology system, and the realization path is given, that is, to form a hot research topic of surface mining technology system and major equipment, and to strengthen the deep cross integration between the existing hot research and surface mining technology system and major equipment. It also provides some useful suggestions on how to jointly tackle major scientific and technological problems with the advantageous resources of various themes inside and outside the industry to achieve a substantial collaborative innovation among multiple themes. Finally, from the perspective of energy and ecology, the paper looks forward to the development direction of major basic theories and technologies of the future surface mining science from seven aspects: mining area planning theory, intelligent mining design principle, intelligent cluster scheduling theory, safe and efficient mining technology of coal mining in spontaneous combustion prone extra thick coal seams, high slope stability control technology, efficient belt conveyor transportation technology under complex working conditions, and intelligent surface mine system engineering. The development direction of the future surface mining equipment is prospected from five aspects: high efficiency mobile crushing equipment, modular semi-fixed crushing equipment, continuous mining process system equipment, large inclination transportation equipment and large dump machine. It is expected that the study can be used as a reference for scientists and engineers in the surface mining field.

Intelligent recognition technology for underground safety violations in coal mines has become the primary means of safety management and information acquisition. However, the accuracy of intelligent recognition is reduced by factors such as low illumination, point light sources, and high dust in the underground spatial environment. To overcome those problems, this paper proposes a multi-weight fusion image enhancement method, which achieves the fusion enhancement of image brightness and illumination balance. The monitoring image brightness is increased by using the Gamma algorithm. Based on the brightness enhancement, the HSV spatial transformation is carried out to keep the hue component and saturation component unchanged, the illumination component is extracted by using a multi-scale Gaussian function, and then the regions where the illumination component is too strong and too weak are adjusted by using an improved two-dimensional gamma function to achieve an illumination equalization. Combining the three weights of Laplacian contrast, luminance, and saturation and fusing the luminance-enhanced and illuminance-balanced images by Gaussian and Laplacian pyramids, the intelligent surveillance image enhancement is achieved. Through the experimental verification of the intelligent recognition of helmets in mine monitoring, the image enhancement method proposed in this paper and the MSR, MSRCP, MSRCR, and AMSRCR algorithms are evaluated in terms of image evaluation indexes such as standard deviation, peak signal-to-noise ratio, and information entropy, and the peak signal-to-noise ratio is improved by 32.44% on average compared with other algorithms, the standard deviation is improved by 115.38% on average compared with the original image, and the average improvement in standard deviation is 115.38% compared with the original image and 47.30% compared with other algorithms, and the accuracy of helmet recognition reaches 86.7%, an average improvement of 47.52% compared with other algorithms. The results show that the algorithm in this paper can effectively improve the contrast and clarity of mine images, reduce the halo phenomenon, and significantly improve the accuracy of target recognition in intelligent mine monitoring. It can lay a solid foundation for the intelligent identification of safety violations in underground coal mines.

Objective In geothermal exploration, a clay cap is a typical hydrothermal geothermal system, and its depth and distribution range can provide crucial information for delineating the scope of geothermal resources and determining the location of geothermal drilling. Clay caps are usually composed of a clay layer formed through hydrothermal reactions and are characterized by low resistance. The low-resistivity cap can be effectively imaged using the audio-frequency magnetotelluric method. To obtain uncertainty information about the distribution of clay cap layers and imaging results, this paper employs the 1D trans-dimensional Bayesian inversion method to investigate the detection capabilities of low-resistance cap layers in geothermal areas through audio electromagnetic data. Methods In this paper, a model test is first carried out to establish a geoelectric model of a typical geothermal system.Subsequently, a 1D trans-dimensional Bayesian algorithm is used to invert the synthetic data to obtain the uncertainty information of the subsurface electrical structure and interface position. Then, the method was applied to the processing of measured audio frequency magnetotelluric data in the Yanggao geothermal area of Shanxi Province. Results This method has relatively accurate identification ability for low-resistivity clay caps, and the obtained uncertainty analysis results of the upper and lower interfaces of low-resistivity caps are also relatively reliable according to numerical tests. It was found that this method has a good ability to identify shallow low-resistivity caps and can provide an uncertainty evaluation of the clay cap interface position via field data tests. The 2D inversion results of this survey line verify the reliability of the 1D inversion. Conclusion This method has relatively accurate imaging capabilities and uncertainty analysis capabilities for shallow geothermal clay caprocks and has strong application prospects in geothermal detection.

With the extension of coal mining in China, fault water inrush has become one of major disasters threatening the safety of coal mine production. Based on the research results related to the mining-induced fault water inrush, this paper proposes a conceptual model of water inrush caused by the erosion synergy of mining-induced rock mass damage rupture and fractured rock mass (fault), derives the permeability evolution equation of the two media, and systematically constructs the cooperative disaster causing mechanism model between mining failure and particle erosion inside faults. The numerical simulation is conducted to study the deformation and failure of rock mass, the particle transport in faults and the evolution characteristics of seepage channel, and systematically explain the temporal and spatial evolution mechanism of seepage catastrophe caused by mining-induced fault inrush. The results show that: ① With the continuous advancement of working face, the damage field of mine floor rock mass is connected with the fault erosion fracture, forming a seepage path of aquifer-fault-mining fracture-working face, and with the increase of erosion time, it finally develops into several dominant water diversion channels, resulting in a sharp increase in water inflow at the working face and a lagging water inrush. ② With the increase of seepage time, the water inflow and fracture opening degree inside faults all show three stages: slow change, sudden increase and stable, and the erosion particle concentration shows a trend of first increasing and then decreasing. ③ Under the geological conditions of the mining area studied in this paper, in order to prevent the occurrence of fault water inrush, the methods such as advanced grouting or leaving water prevention coal pillars can be adopted, and the advance grouting time should be before the bottom plate fracture zone connects faults, if grouting is not applied, the width of the reasonable water prevention coal pillar should not be less than 20 m.

This paper briefly summarizes the importance, current situation and existing problems of earthquake science popularization in primary and secondary schools, and focuses on the development path of earthquake science popularization based on STEAM education concept. On the basis of clarifying the main purpose, service target group of earthquake science popularization education, and effective popular science content and form, this paper applies the concept of STEAM education to propose the effective path of earthquake science popularization in primary and secondary schools. Taking the junior high school section as an example to make a specific case analysis, this paper suggests to build an earthquake science popularization ecosystem from the perspective of STEAM education. STEAM education is an interdisciplinary education concept that integrates science, technology, engineering, arts and mathematics, emphasizing the integration of disciplines. It is a new form of learning in which taking projects as the main line, teachers as the lead, and students as the main body. This study argues that STEAM education needs to be integrated into the earthquake science popularization, and a high-quality science education system should be constructed, covering both on- and off-campus educational activities and active learning ability, so as to create an ecosystem suitable for the development of science popularization education.

With the continuous increase of coal mining depth, the occurrence and prevention of deep rockburst in China have become normalized. In order to improve the effectiveness of deep rockburst prevention and control technology, starting from the technical difficulties of deep rockburst prevention and control in on-site engineering, combined with practical data statistics of disaster prevention and control engineering, this study demonstrates that the deep rockburst in China is due to its high geological stress and large range of human mining disturbance. The stress recovery of surrounding rock is fast after rock stress unloading during the disaster prevention and control process. The low effectiveness of rockburst prevention and control can be attributed to the new requirements of “three highs and one low” prevention and control technology in deep mining compared to that in shallow mining, including high-strength large-sized drilling to relieve pressure, in order to solve the collapse prone problem of thick and hard coal seams; small spacing high-density drilling to solve the problem of disconnected pressure relief range in drilling; multiple rounds of repeated high-frequency construction to solve the problem of rapid stress recovery after unloading pressure in deep coal seams; and the mining face is advancing at a low speed to solve the problem of high mining disturbance intensity. In response to the new requirements of “three highs and one low” prevention and control mode for deep rockburst, in order to further improve the safety and reliability of rockburst prevention and control, and based on the limitations of optimizing development and mining deployment for conventional source rockburst prevention and control, this paper proposes the technology of actively regulating the structure and load of overlying rock layers in the deep rockburst prevention and control areas, and presents some further scientific problems that need to be solved. Against the background of several typical rockburst accidents in recent years with the problem of “missed targets” in the prevention and control plans, a local targeted prevention and control technology for deep rockburst mining space has been developed, and the scientific challenges that need to be solved in the future have been pointed out. Against the background of the difficulty in evaluating safety issues after the implementation of coal mine rockburst prevention and control measures, a deep rockburst prevention and control unloading standard evaluation technology is proposed, and the scientific difficulties that need to be solved in the future are pointed out. The coal industry vigorously promotes intelligent mining, but the disaster control still relies on manual labor and personnel to operate in a high-risk environment. This paper also explores the emerging research direction and scientific challenges of intelligent mining and intelligent prevention and control of deep rockburst. Finally, it is objectively pointed out that the prevention and control of rockburst is not purely a theoretical and technical issue, and the human understanding of technical issues is also one of the important reasons for rockburst accidents. Combining with the on-site engineering practice, this paper discusses the concept and mechanism of rockburst, whether rockburst can be predicted, whether rockburst can be prevented and controlled, and how to deal with rockburst mines and other industry focused technical issues. It is pointed out that the problem of rockburst engineering is a struggle between humans and nature, which requires practitioners to objectively understand, objectively accept, and conduct in-depth research. The current achievement is of significance.

In order to improve the production of coalbed methane vertical wells in the central and northern Zhengzhuang block, southern Qinshui Basin, Shanxi, China, this paper analyzes the reasons for the poor stimulation effect of medium-deep coalbed methane vertical wells, based on the ground stress test data and fracturing monitoring data of these evaluation wells in the study area, proposes targeted stimulation techniques, designs and carries out field comparative pilot studies and analyzes their results. The results show that there are three main reasons for the low production of these vertical wells in the study area. Firstly, the vertical fracture is dominant, resulting in the shorter length of hydraulic fractures. With the increase of burial depth, the length and width of fractures decreases at the same fracturing scale. Secondly, with the increase of burial depth, the embedment depth of proppants into coal rock increases and the closure of hydraulic fractures speeds up. As a result, the stable production time is short, and the main form of gas production curve is “single peak” type. Thirdly, after the initial fracturing, the coal body structure is much more broken, and new fractures are easy to enter the initial fractures, which increases the difficulty of creating new fractures, resulting in poor stimulation effect. In view of the above reasons, the paper proposes an innovative technology of pre-plug, large-scale and remote-support re-fracturing. Pre-plug means that relatively low displacement, sand ratio and scale are first used to fill initial fractures, and then large-scale re-fracturing is carried out to create new fractures. Large-scale fracturing refers to the fracturing with large displacement, large fluid volume and high sand ratio. In order to improve the stimulation effect of middle-deep reservoirs, the fracturing fluid volume is increased from 600−800 m3 to more than 1 300−2 000 m3, the displacement is increased from 6−8 m3/min to more than 10−14 m3/min, and a low viscosity fracturing fluid system combined with low density proppants is used to increase the sand ratio from 7%−8% to more than 10%−15%. Remote-support is a combination of self-suspended proppants and large displacement to increase proppants migration distance and increase the proportion of the propped fractures. The average daily production of a single well reached 1 380 m3, which was 1 190 m3 higher than that before, and nearly 1 000 m3 higher than the stable gas production of adjacent wells, realizing the production breakthrough of vertical wells in the low-production area of the middle-deep reservoir in the north of Zhengzhuang block. Results of the comparative pilot studies showed that the average net construction pressure increased by 3.3 MPa after pre-plug, compared with the initial fracturing, which means that new fractures were formed and resulted in the production increase by 1 000 m3 compared with that of the wells without the Pre-plug. The pilot results show that, in general, the larger the technical parameters of pre-plug, large-scale and remote-support re-fracturing, the better the production performance.

Coal-rock interface recognition technology is one of the key technologies for intelligent mining in coal mines. Based on high-frequency radar wave detection technology, high-precision detection of coal-rock interfaces can be achieved with mining, but there are still safety risks for equipment caused by rib spalling and roof caving in ultra-high mining heights (≥6 m) in mines, as well as spatial restrictions on equipment passing through during sudden changes in mining height (mining height ≤2 m). Based on previous work, this paper proposes a rapid dynamic detection system and method for coal-rock interfaces in mines using nodal GPR. The main contents include: ① Explaining the principle of the nodal GPR observation system in mines, designing a coal-rock interface recognition observation system plan and radar antenna sensor installation method based on the actual environment of the mine working face; ② Studying and proposing a nodal acquisition control system and information interaction transmission design plan to achieve dynamic data acquisition, control, and storage; ③ Studying and proposing enhanced processing methods for sensor detection data and coal-rock interface recognition algorithms based on nodal acquisition methods and radar reflection echo characteristics of coal-rock interfaces, which can effectively achieve intelligent recognition and tracking of coal-rock interfaces, as well as calculation of coal seam thickness and spatial coordinates. To verify the feasibility of this method, multiple geological radar antenna sensors with a center frequency of 1.5 GHz were used for physical model verification experiments, and a comparative analysis of nodal data acquisition and continuous data acquisition results was conducted. The experimental results show that both nodal and continuous acquisition methods can effectively identify coal-rock interfaces. Compared with continuous acquisition methods, the nodal detection method proposed in this paper can achieve rapid and dynamic repetitive data acquisition, with a single acquisition time controlled within 10 seconds, an average error of 1.07 cm for coal seam thickness detection results, a maximum error of 1.47 cm, and an average error percentage of 7.64%. This method provides technical support for dynamic high-precision detection of coal-rock interfaces in intelligent mining in mines.

Objective Thrust faults and their associated folds are important structures of continental tectonic deformation, widely distributed at plate boundaries and within plates. The activity of these thrust faults can trigger severe seismic disasters, such as the 1999 Chi-Chi earthquake in Taiwan and the 2008 Wenchuan earthquake. However, research on surface ruptures and associated disasters caused by thrust faulting is relatively limited, mainly due to the complexity of their fault propagation processes. Studying thrust faults and their associated folds could enhance the capability of seismic hazard risk assessment and better predict earthquakes and potential secondary disasters. Methods This paper first introduces the meanings of fold-related faults and fold scarps and explains the impacts of surface uplift and lateral extension deformations on topography. Taking the Tian Shan active fold zone as an example, the paper focuses on analyzing the structural characteristics and landform deformation patterns of the Hejing thrust-and-fold belt in the northern margin of the Yanchi Basin and the Mingyaole anticline in the southern piedmont of the Tian Shan. It also discusses various types of structures, such as thrust faults, fold-related faults (flexural faults, flexural slip faults, and conjugate shear faults), and their effects on landforms. Based on this, the paper explores the relationship between the growth process of active folds and the formation of seismic geological disasters. Results and Conclusion It is believed that in a compressive tectonic environment, the growth of active folds and the formation of fault-related folds cause building displacement, tilting, and damage, thereby generating geological disasters. In particular, it emphasizes that the tilting of the ground on both sides and the footwall of active anticlines during the process of crustal shortening, vertical uplift, and lateral expansion poses a threat to the safe operation of major engineering structures. Simultaneously, the bending deformation caused by regional crustal shortening presents potential seismic risks and triggers geological hazards for significant linear engineering projects spanning active anticlines, warranting attention.

This paper collected the data of death and loss of contact in Luding MS6.8 earthquake, quantitatively analyzed the characteristics of the number of deaths and loss of contacts over time, and compared with typical destructive earthquakes in recent 10 years. Combing the actual emergency rescue work, this paper sort out and summarized the main reasons, systematically analyzed the impact of geological disasters on personnel mortality and loss of connection rate, discussed the characteristics of earthquake disasters and disaster relief in mountainous areas. At the same time, we propose suggestions for the verification and submission capabilities of earthquake disaster information and the improvement of personnel search and rescue capabilities in complex mountainous environments.

During the coal mining process, the change in the floor stress state of coal seam will produce deformation and failure. The seam floor failure in different coal mining processes has a certain law. At present, the water disaster monitoring of coal seam floors based on the DC resistivity method mainly focuses on the resistivity response characteristics of floor deformation and damage. To investigate the temporal changes in the electrical properties of the coal seam floor during mining, this study employs the inter-hole DC perspective observation system and the time-lapse resistivity reflection coefficient method. Through numerical simulation and field tests, the study uncovers the temporal variation law of the resistivity of coal seam floor induced by mining activities. First, this paper compares the results of individual inversion and time-lapse resistivity change rates for a typical geoelectric model to validate the reliability of the inter-hole DC perspective time-lapse method. Next, considering the mining-induced damage to the coal seam floor, this paper analyzes the electrical response patterns and charac-teristics of the rise of confined water and the damage zone in the floor during the mining process. It also discusses the feasibility of using a time-lapse resistivity reflection coefficient to assess the depth of coal seam floor damage, offering a theoretical basis for field construction. Finally, , the on-site monitoring tests reveal the electrical change characteristics of coal seam floor during the coal mining process. The time-lapse resistivity reflection coefficient R is utilized to determine the damage depth of the rock layer of the working face floor, which is found to be 15 m. The study results demonstrate that the time-lapse characteristics of the resistivity of coal seam floor mining damage obtained by the inter-hole DC perspective method can mitigate the influence of formation factors and random noise in the monitoring data to a certain extent. Additionally, the time-lapse resistivity reflection coefficient can be utilized to determine the depth of coal seam floor failure. This method transforms the detection target from the single study of geological anomalies to the full life cycle dynamic monitoring of the floor damage of the working face in the process of coal mining and then realizes the detailed depiction of structural damage to the working surface floor.

Coal has made important contributions to the industrialization process of human society, and has played a key supporting role in ensuring China’s energy security and stable economic development. Since the mid-19th century, the coal-based fuel of coal, kerosene, gas and coal electricity has gradually entered the era of large-scale use. However, the traditional use of coal produces high carbon emissions, which has become a major problem in energy transition. Facing the development of ecological civilization society, the clean and efficient use of coal is imminent, and the innovation of modern coal-based energy technology is imperative. This paper proposes the definition and connotation of modern coal-based energy technology system, which is defined as the production of low-carbon energy products such as coal-based gas, coal-based oil, coal-based hydrogen and coal-based electricity, and the in-situ absorption of carbon dioxide in mining areas to form a clean and low-carbon energy production system with carbon neutrality. Its technical connotation includes coal-based gas, coal-based oil, coal-based hydrogen, coal-based electricity and dynamic carbon neutrality in mining areas, with a total of 5 technical modules, 19 technical units and 61 key technologies. The modern coal-based energy technology system will play an important role of “one main body, three supports and one breakthrough” in the future new energy system. Coal-based electricity provides the main body of electricity system stability. Coal-based oil supports the China’s oil safety. Coal-based gas supports the China’s gas safety. Coal-based hydrogen plays a supporting role in the development of hydrogen energy in China. The major breakthrough is the dynamic carbon neutral technology of coal-based energy. The paper supposes that when the ratio of non-fossil energy and low-carbon coal-based energy is maintained in the range of 2.5−3.0, coal-based energy, oil and gas and wind, water, nuclear energy can be reasonably integrated to form a new quality energy system with strong complementarity, high reliability and low carbon emissions. Based on the major breakthrough and practical application of modern coal-based energy technology, it is predicted that China’s low-carbon coal-based energy production will reach 1.02 billion −1.46 billion tons of standard coal equivalent (tce) in 2060, equivalent to 18%−24% of the national energy demand, and carbon dioxide emissions will be controlled below 500 million tons. Compared with the current energy transformation planning path based on “de coal” planning, the share of coal in our energy system can increase from 10% to more than 20%, and carbon dioxide emissions will reduce by 50%. At that time, the modern coal-based energy system has great technological innovation significance for China’s energy security and carbon dioxide emission reduction, and helps China to become a country with independent energy supply.

Based on the green development trend and requirements of China’s coal industry, this paper analyzed the factors that coal mines consider in choosing filling mining methods and the constraints that affect the promotion of filling mining technology. According to the geographical distribution characteristics of different mining areas and the differences in filling demands, four types of priority principles of “protecting the ecological environment, protecting surface buildings, addressing coal gangue and solid waste, and improving economic efficiency” for coal mine filling mining were defined. The ecological mining goal of “building the whole process holographic intelligent ecological mine by adopting filling mining as a regulation tool to protect the ecological environment in coal mines” was put forward. Based on the finite deformation mechanical model of the roof in filling mining, the factors affecting the subsidence of target rocks in filling mining were expounded, and the supporting strength calculation and overburden deformation control equations under three filling engineering modes such as ecological environment protection, ground building protection and gangue treatment were established. In addition, the paper introduced the development status and direction of universal filling technology in coal mines in China, including solid filling of raw gangue waste, modified solid filling, gangue concrete filling, integrated mining-filling-charging, large amount of gangue filling, filling method in thin coal seam, filling method for regional protection, filling method in continuous mining roadway and other filling technologies that meet various needs of coal mines. The material preparation and transportation of different filling technologies, the characteristics of filling process and the adaptive filling equipment were described in detail. In order to realize the intelligent filling of coal mines, a comprehensive data perception system was established, which realized the intelligent process from unit to whole filling working face through spatial planning and filling effect judgment. The sensor network and artificial intelligence algorithm were combined to monitor and control the solid filling process of coal mine in real time, and improve the filling quality and filling efficiency. Coal mine filling mining will play a more important role in the long-term planning of China’s green mine construction. Strengthening the scientific and technological research of the whole process of coal mine production based on active filling, the construction of universal filling technology and process system, the development of new solid filling materials, and the research of intelligent filling mining, will help the filling mining technologies in China’s coal mines have a very broad prospect.

The MILD combustion is a combustion mode that occurs in a moderate or extremely low oxygen environment, combining the advantages of high combustion heat utilization and very low NOx emissions, and is considered by the international combustion field to be one of the cleaner combustion technologies with great potential for application. Since the relevant research began around 1990, the technology for achieving a MILD combustion of gas fuels has been relatively mature, while the research on the MILD combustion mechanism and implementation conditions of solid fuels such as coal powder and biomass is still relatively lacking. Based on the high momentum oxidizer jet, internal recirculation is achieved, eliminating the need for external high-temperature preheating to establish MILD combustion, greatly expanding the application range of MILD combustion. This paper provides an overview of the basic characteristics of MILD powder fuel combustion from the aspects of particle dispersion, heating, ignition, combustion, and pollutants. Due to the uneven dispersion and reaction of particles, the MILD combustion process of carbon-based solid fuels such as coal powder is more complex than that of gas fuels. High speed jet MILD combustion not only increases ignition delay but also expands ignition and reaction zones, requiring systematic research on the characteristics and mechanisms of each combustion stage. This paper introduces the research achievements in the theoretical design and equipment development of solid fuel MILD combustion. It is recommended to improve the existing coal-fired boiler burner, adjust the process parameters to match the MILD combustion mode, increase the residence time of coke particles to improve combustion efficiency, improve combustion stability, and suppress various pollutant emissions, including fine particulate matter, through high-precision numerical simulation. Based on the overall approach of interconnected energy systems, the coupling research between MILD combustion and various new combustion technologies should be promoted, especially strengthening the research on the co-combustion characteristics of coal powder, biomass and hydrogen, ammonia and other combustible gases, and assisting in energy transformation. Exploring the characteristics of turbulent two-phase flow, turbulent interphase heat transfer, and turbulent chemical coupling in the powder MILD combustion is crucial for deepening the understanding of powder MILD combustion. It involves multivariate analysis and high-precision simulation, which will be the focus and difficulty of future research.

The safe, green, efficient and low-carbon coal mining is the common goal of surface coal mines around the world. The development intensity and ecological carrying capacity of surface coal mine resources in China show the reverse development characteristics, and the vulnerable ecological environment areas in northwest China have become the main surface coal production areas, which makes surface coal mining and ecological environment protection become important scientific problems, ecological problems and development problems to be solved urgently. On the basis of the development situation, natural conditions and main influencing factors of surface coal mines, the connotation characteristics and overall structure of realizing the safe-green-efficiency-low-carbon mining of surface coal mines were explained. Aiming at the characteristics of the whole life cycle of pre-mining, mid-mining and post-mining of surface coal mines, in terms of four levels: safe mining technology, green mining technology, efficient mining technology and low-carbon mining technology, this paper puts forward eight key technologies including the time-limited slope control technology, the intelligent early warning decision-making technology, the new mode of transportation link, the ecological construction of mining area, the coordinated mining of adjacent mines, the intelligent mining design, the application of electric mining trucks and the ecological damage reduction at mining sources. The key work and direction of safe-green-high efficiency-low carbon cooperative mining in surface coal mines are clarified. In terms of the measures of safety-green-efficiency-low carbon co-development, regarding strengthening a top-level design, accelerating the distributed implementation, enhancing key researches, promoting personnel training, and improving standards and regulations, the paper proposes the target tasks to be accomplished in different stages in 2025, 2030 and 2035. In the new era, surface coal mines should firmly follow the development path of safe-green-high efficiency-low carbon, and realizes the high-quality development goal of surface coal mines.

Coal mining machine is the core equipment of completely automated working face, and the research and development of intelligent coal mining robot is crucial for achieving the intellectualization of fully mechanized working face. This paper comprehensively analyzes the current research status of sensing detection, position and attitude control, speed control, cutting trajectory planning, and tracking control in the coal mining machine roboticization process, and proposes five key technologies that must be solved in the development of intelligent shearer robots, including sensing and detection, pose control, velocity control, cutting trajectory planning and tracking control. Aiming at the problem of intelligent perception, this paper proposes the construction thought of a coal mining robot intelligent perception system, as well as the architecture of a coal mining robot intelligent per-ception system. The architecture of the intelligent perception system for coal mining robots is outlined, enabling a comprehensive sensing of running state, posture, environment, and so on, thereby ensuring the safe and reliable operation of intelligent coal mining robots. In terms of the position and attitude control problem of intelligent coal mining robots, the intelligent PID position and attitude control thought is proposed, along with an improved genetic algorithm-based PID pose control method, enabling precise pose control for the coal mining robot. As to the problem of velocity control, the thought of cutting load measurement based on the fusion of “force-electricity” heterogeneous data is proposed. Additionally, a neural network-based algorithm for cutting load measurement is presented, achieving an accurate load measurement. Furthermore, a traction and cutting speed adaptive control approach is proposed, including an artificial intelligence-based decision-making method for traction and cutting speed and a sliding mode control method for traction and cutting speed with disturbance rejection. This approach enables a precise and adaptive speed control for the coal mining robot. Regarding the problem of cutting trajectory planning and tracking control, the precise cutting trajectory planning thought is proposed, incorporating geological data and historical cutting data into a cutting trajectory planning model. The precise cutting trajectory tracking control thought is proposed, and an intelligent interpolation algorithm-based cutting trajectory tracking control method is given, achieving a high-precision trajectory planning and accurate tracking control for the coal mining robot. Considering the “position-attitude-velocity” collaborative control problem, the intelligent optimization idea of "position-attitude-velocity" collaborative control parameters is proposed, which utilizes an improved particle swarm optimization method based on multi-system constraints to optimize the coordinated control parameters, resulting in intelligent and efficient operation of the coal mining robot. The in-depth investigation of these five key technologies for intelligent coal mining robot provides some valuable insights for accelerating the development of high-performance, efficient, and reliable intelligent coal mining robot.

In view of the intelligentization of coal mine roadway excavation, this paper discusses the current development status of four major categories of intelligent fast excavation equipment, including continuous mining machine, excavation and anchor machine, full-section excavation system, and anchor excavation machine, analyzes the applicability of the four major categories of intelligent fast excavation equipment with the geological conditions, proposes some key technological issues for the realization of intelligent coal mine excavation which need to be resolved, and also explores the information transmission and intelligent analysis technology, intelligent perception technology, precise positioning and navigation technology, autonomous stereotyped directional cutting technology, remote and autonomous cutting control technology of road-header and multi-level and multi-process intelligent cooperative control technology, as they are the basis for the realization of intelligent roadway excavation. Based on the key technological issues needed to be solved in the mine roadway excavation under the complex geological conditions, the paper puts forward the design method of systematic analysis, modular design and optimal combination of functions, according to the functional requirements of the excavation operation and the requirements of the excavation process. A multi-level digital twin architecture of virtual control and virtual-reality combination is studied based on the multi-dimensional information reproduction of heading equipment, environment, and geological structure to realize the remote control of road-heading machine. A control method that integrates single-machine intelligence, system synergism, and synergism of underground intelligent control and surface remote monitoring is proposed. A new type of flexible advance support technology without repetitive crushing, multi-stage telescopic cutting technology of cutting section, and multi-rig parallel operation technology of intelligent anchoring unit have been developed, and a new type of combined unit for rapid roadway heading operation with a parallel operation of excavating, supporting, anchoring, transporting, and exploring processes has been also developed, and a flexible parallel operation technology of excavation robot, advance support robot, anchoring robot, and auxiliary transportation robot group has been proposed. A data-driven multi-machine, multi-process collaborative control behavior planning and decision-making method is proposed. In addition, it is proposed to construct a complete coal mine underground cross-system full-temporal-spatial information digital sensing system, build a data sensing intelligent monitoring platform with multi-parameter, multi-scale and full-temporal-spatial characteristics, that integrates the production state of underground site, spatial information of roadway, state of heading equipment, and risk information, etc., and realize a real-time communication between virtual system and actual tunneling system, so as to realize the intelligent and less-manned heading through data-driven planning and analysis.

The safety in the coal-producing mines in China is continuously improving, but coal and gas outburst accidents still occur. The prediction of coal and gas outbursts allows the scientific application of outburst prevention measures, which can ensure the safe coal mining to a certain extent. Machine learning is an interdisciplinary field involving probability theory, statistics, and computer science, which can explore the nonlinear relationship between outburst accidents and its associated indicators. The application of machine learning in coal and gas outburst prediction has received relatively widespread attention, and with the rapid progress of artificial intelligence and computer technology, it will play a greater role in the field of outburst prediction. Therefore, this paper provides a comprehensive review of the research on machine learning in coal and gas outburst prediction, analyzes the difficulties in outburst prediction and prospects its development direction. Firstly, the paper provides a brief overview of the research status on the hypothesis, occurrence mechanism, and prediction index selection of coal and gas outbursts. Then, it summarizes the research progress in the field of outburst prediction, including the application of support vector machines, neural networks, extreme learning machines, and ensemble learning algorithms. In addition, it also points out the existing problems in the current research, such as imbalanced samples, missing data indicators, and small sample sizes. Finally, the paper gives an outlook on the developments of coal and gas outburst prediction based on machine learning, including improving algorithm performance, optimizing feature engineering, and increasing sample size. With the continuous improvement of computer performance, more powerful models may be proposed, which can further improve the prediction accuracy of outburst accidents.

The fragile ecological environment in the western coal mining areas of China, compounded by intensive mining activities, has led to water and soil erosion, soil degradation, and damaged root systems. With a low plant water use efficiency, the ecological restoration becomes challenging, making the improvement of water use efficiency a key aspect in the ecological restoration or reconstruction of western mining areas. Soil water is a critical factor limiting the ecological restoration of arid and semi-arid coal mining areas, as it connects atmospheric water, surface water, groundwater, and vegetation growth, serving as an important carrier for water circulation and nutrient transport. Efficient and rational utilization of soil water is crucial to the success of ecological restoration. Therefore, investigating plant root water utilization strategies plays a significant role in the ecological restoration of western coal mining areas. This paper analyzes the main research methods of plant water use at home and abroad, compares the advantages and disadvantages of different methods, and reviews the corresponding research progress. In the damaged ecological environments of arid and semi-arid coal mining areas, the application of plant-microbe combined microbial remediation technology can improve plant water use efficiency and enhance plant water use strategies. At the same time, the microbial inoculation reduces the proportion of water absorption by plants from shallow soil layers, effectively increasing the absorption and utilization of water from deep soil layers by plants, thereby enhancing plant water use efficiency. This enables the inoculated plants to exhibit a higher ecological adaptability in the arid and semi-arid coal mining areas. This paper analyzes the current research progress and existing problems of plant water use in the western coal mining areas, discusses the improvement of water use strategies through microbial remediation in mining areas, and proposes the impact of different plant combinations on water use strategies and their research focuses in the ecological restoration of western arid coal mining areas. This lays a solid foundation for achieving green, sustainable, and high-quality development in the arid and semi-arid coal mining areas, and has important ecological application value.

Objective Black carbon is a carbonaceous mixture formed by the incomplete combustion of biomass and fossil fuels. Since black carbon has a high carbon content and an aromatized molecular structure, it can persist in the natural environment, suggesting that black carbon is an important component of the global carbon cycle. Although pioneering studies have advanced the understanding of nature, circulation fluxes, and reserves of black carbon in the geosphere, it is still necessary to further clarify the source-sink processes of black carbon and explore the importance of black carbon in the global carbon cycle. Methods Here, this study reviews the available data on pathways, fluxes, and time scales of the global black carbon cycle and analyses and summarizes the migration mechanisms and constraints in the source-sink process of marine black carbon. Results This paper concludes that marine sediments serve as a large reservoir for black carbon, with a reserve of 569-1 380 Pg. Black carbon can persist over millennia in marine sediments, which is associated with a long turnover time as an "effective carbon sink" in the context of "carbon neutrality". Moreover, black carbon exerts a negative feedback effect on global warming due to its longer turnover cycle time than biomass carbon. The deposition of black carbon into the sea is an effective means to enhance carbon sequestration in the ocean and could be an effective way to implement the carbon capture, utilization, and storage (CCUS) strategy. Conclusion In this paper, we propose that human-induced production of black carbon from biogenic combustion may be actively regulated and that the deposition pathways and burial areas of black carbon into the sea should also be optimized given the premise of ecological and environmental friendliness based on a summary and assessment of the strategic value and climate significance of black carbon in marine sediments in the context of "carbon neutrality". Therefore, the positive role of black carbon in "negative ocean carbon emissions" can provide a basic theoretical framework for achieving the goals of "carbon neutrality".

Objective Palaeomagnetic methods can be used to quantitatively constrain the Early Palaeozoic palaeo-position of the North China Block (NCB), which provides a crucial scientific basis for researching the evolution of the Proto-Tethyan Orogeny and the affinity of the NCB for Gondwana. However, the NCB has undergone considerable tectonic activity since the Early Palaeozoic, and the Ordos Basin in the western part of the NCB is rich in hydrocarbon resources. Late tectonic activity and the migration of hydrocarbon resources may have caused remagnetization of Early Palaeozoic strata. Methods Thus, in this paper, to determine the main magnetic minerals in various rocks and their ability to record the primary remanent magnetization, we carry out a series of detailed petrography, rock magnetism and stepwise demagnetization experiments on the limestone and tuff samples of the Upper Ordovician Zhaolaoyu Formation in the Fuping area of the southern Ordos Basin, including optical microscope identification, scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), saturated isothermal remanent magnetization (SIRM) acquisition curve, three-axis isothermal thermal demagnetization test, κ-T curve test, hysteresis loop experiment, first-order reversal curve (FORC), and thermal demagnetization and hybrid (TD+AF) demagnetization. Results The results indicate that the main magnetic minerals in the limestone and tuff samples are magnetite, pyrrhotite and/or greigite, and some samples also contain a tiny quantity of haematite with impurities and goethite. Mineral particles possess single domains (SDs) as well as multiple domains (MDs) within their magnetic domains. Combining petrographic and demagnetization data, this paper suggests that the main magnetic minerals in the samples are likely secondary minerals associated with later fluid alteration (maturation and migration of organic matter). Conclusion The remanent magnetic signals conveyed by these rocks cannot be directly used to constrain the Early Palaeozoic palaeoposition of the NCB but may be used to constrain hydrocarbon migration and accumulation in the Lower Palaeozoic strata of the southern Ordos Basin.

Objective Machine learning has been widely applied in the fields of collapse, landslide and debris flow susceptibility analysis. The selection of nonhazard samples is a key issue in landslide susceptibility analysis. Traditional random sampling and manual labelling methods may involve randomness and subjectivity. Methods In view of the potential randomness and representativeness of noncollapse samples, this paper considered soil collapse susceptibility evaluation a positive-unlabelled (PU) learning problem and proposes a two-step convolutional neural network framework (ISpy-CNN) that combines an information value model and the Spy technique. First, 15 collapse-related factors were selected for modelling based on the geomorphological, geological, hydrological, and artificial environmental conditions of the study area. Low-information-value samples that were able to map the distribution structure of noncollapsing samples were screened by the information value model. Then, through the Spy technique and training the CNN model, negative samples with high confidence were identified from low-information-value samples that were classified as noncollapsed samples. Finally, based on the framework and traditional random sampling, we used support vector machine (SVM) and random forest (RF) models to compare and verify the reliability, prediction accuracy and data sensitivity of the proposed learning framework and other models. Results The results illustrate that the proposed ISpy-CNN method can improve the accuracy, F1 value, sensitivity and specificity on the validation set by 6.82%, 6.82%, 6.82%, 8.23%, respectively compared to random sampling and 2.86%, 2.89%, 2.86%, 2.31%, respectively compared to the traditional Spy technique. The prediction accuracy of step 2 in PU learning using the CNN model is higher than that of the RF and SVM models. The sample set screened by the ISpy-CNN framework exhibited greater stability, prediction accuracy and growth rate than those screened by the traditional Spy technique by adding the same number of training samples. Conclusion The ISpy-CNN framework proposed in this paper can better assist in the selection of nonhazard samples and real collapse spatial distribution maps, and the results of the framework are more consistent with the actual collapse distributions.

Under the dual carbon goal， the focus and difficulty of the petroleum and petrochemical industry transition lie in exploring low-cost transition development paths. This needs to conduct systematic research on the development foundation and potential of various transition technologies， coordinate the development and application timing of these technologies， and thus form a technology portfolio and comprehensive plan supporting the optimal transition path. Carbon capture， utilization， and storage （CCUS） has high technological maturity and sound coupling with the petroleum and petrochemical industry and is a key technology for petroleum and petrochemical transition. However， the high cost remains the main obstacle to large-scale development. Analyzing the economy and development mode of CCUS plays an important role in determining the future development layout of the CCUS industry， and studying the potential of CCUS for the petroleum and petrochemical industry transition. To conduct an in-depth analysis on the economy of future CCUS technology and its potential in the transition of the petroleum and petrochemical industry， this paper focuses on CCUS with enhanced oil recovery （CCUS-EOR） and proposes a new analytical approach. Firstly， by comprehensively reviewing the entire process of CCUS-EOR， the costs including carbon capture， transportation， oil displacement， and storage are analyzed in detail， with the cost reduction of each in the future evaluated. Secondly， by the prediction of future oil prices and carbon prices， the economic benefits brought by oil displacement and carbon emission reduction are analyzed， and a cost-benefit comparison is conducted. Based on the cost-benefit analysis results， this paper further carries out a comprehensive economic evaluation of CCUS-EOR projects under different modes in China， which covers different carbon capture technologies， transportation modes， and storage strategies， revealing the profitability and sustainable development potential of CCUS-EOR projects under different scenarios. The results show that the CCUS-EOR economy is deeply affected by multiple factors such as carbon price， oil price， and oil displacement efficiency. In the medium and long term， carbon price changes have a greater influence on future CCUS-EOR returns. Under the high level of both carbon price and oil price， the profitability of CCUS-EOR projects is greater and more attractive. Meanwhile， the improvement of oil displacement efficiency can significantly increase the economic benefits of the projects. Currently， there are significant differences in the economy of various projects in China， which cannot fully guarantee significant profits. However， there is great room for improving the future economy. For the future CCUS-EOR development in China， it is necessary to break through the technological bottleneck in carbon capture links and focus on developing and applying pre-combustion capture technology to reduce capture costs and improve capture efficiency. Additionally， it is necessary to optimize the industrial layout to form a source-sink matching industrial cluster and thus achieve a synergistic effect in the industrial chain. At the same time， it is important to promote the development of the carbon trading market， guide carbon emission reduction behavior via the market mechanism， and create a favorable external environment for the promotion and application of CCUS-EOR technology in the petroleum and petrochemical industry.

Glutenite reservoirs in the north region of Lijin， Dongying Sag have complex mineral components， resulting in the low accuracy of the interpretation of physical parameters and the difficulty of defining the boundary of oil and dry layers. Based on the data of logging， mud logging， production test， and analysis testing， this paper combined crossplot chart identification with radar pattern recognition mode to effectively distinguish glutenite lithology in the area. Based on the lithology identification， oil-bearing occurrence analysis， and testing data analysis， this paper established the lower limits of physical and electrical properties of effective conglomerate and carbonate reservoirs. Combining with the production test data， this paper constructed the interpretation chart of classification and evaluation standard of the effective reservoir of glutenite in the north region of Lijin， Dongying Sag， and built the porosity and permeability parameter models of conglomerate and carbonate reservoirs， respectively， which provided a quantitative evaluation method for complex glutenite reservoirs in the north region of Lijin， Dongying Sag. The application has verified the research in the production wells of glutenite reservoirs in the north region of Lijin， Dongying Sag， and the results are promising.

Shale oil reservoir is a typical unconventional oil and gas resource that plays an essential role in the international energy supply market. Due to the complex pore structure and crude oil composition of shale oil reservoirs， the flow of crude oil in organic-rich shales has a certain complexity， and its flow behavior still needs to be further studied. Based on the stochastic simulation method， the flow characteristics of fluid in mixed-wet nanopores were considered， and an apparent oil permeability （AOP） model of shale oil reservoirs was established in this paper. The results show that the AOP of shale oil reservoirs is directly related to the molecular structure of alkanes， and its influence decreases with the increase of pore radius. The organic matter can improve the flow capacity of crude oil when the boundary slip length is large， and its AOP is about ten times the absolute permeability. At the same time， the pore radius reduction and wetting reversal effect triggered by adsorbed organic matter significantly impact the flow capacity of alkane molecules， and these effects cannot be ignored. The AOP model of shale oil reservoirs considering mixed-wet nanopores established in this paper helps understand the fluid flow mechanism of shale oil reservoirs and can provide theoretical support for productivity evaluation， dynamic analysis， and production system optimization of shale oil reservoirs.