Construction of water injection seepage model for coal body and microscopic dominant influence law
Coal seam water injection technology plays a vital role in diminishing dust formation in mining operations by humidifying coal masses, thereby minimizing the dispersion of airborne particulate matter. This technique is crucial for managing dust in underground operations. As mining operations reach g...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Science Press
2025-02-01
|
| Series: | 工程科学学报 |
| Subjects: | |
| Online Access: | http://cje.ustb.edu.cn/article/doi/10.13374/j.issn2095-9389.2024.04.28.002 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841561855249612800 |
|---|---|
| author | Enmao WANG Gang WANG Shuliang XIE Hongzhao WEI Jing FENG Handan LIANG |
| author_facet | Enmao WANG Gang WANG Shuliang XIE Hongzhao WEI Jing FENG Handan LIANG |
| author_sort | Enmao WANG |
| collection | DOAJ |
| description | Coal seam water injection technology plays a vital role in diminishing dust formation in mining operations by humidifying coal masses, thereby minimizing the dispersion of airborne particulate matter. This technique is crucial for managing dust in underground operations. As mining operations reach greater depths and face diverse geological challenges, understanding the impact of various factors on coal seam water injection becomes crucial. These factors include the inherent properties of coal bodies and the sizes of pores and fractures. Without this knowledge, predicting the extent of moisture penetration is unfeasible, hindering moisturization. Consequently, to enhance the effectiveness of coal seam water injection, this research investigates the primary factors influencing the process. Initially, we developed a percolation model, incorporating elements such as pore throats, equivalent pore diameter, effective porosity, capillary bundles, tortuosity, and flow paths. Furthermore, an online CT scanning loading percolation system was used to reconstruct three-dimensional visualizations of effective microfracture structures in coal bodies from five mines with varying metamorphic degrees: Inner Mongolia, Tongfuxin, Meihuajing, Dahuang Mountain, and Ciyaogou. The fractal theory was applied to extract parameters for calculating effective connected pores and fractures. In addition, experiments were conducted to measure coal permeability from these five mines, validating the model. Finally, the study introduced “sensitivity” to characterize the impact of various factors on seepage flow. By applying the Morris screening method, we combined numerical analysis with the percolation model to quantitatively screen main controlling factors such as coal body strength coefficient, tortuosity fractal dimension, effective porosity, volume fractal dimension, and pore throat radius. Their influence on water injection capacity was analyzed. The main conclusions were as follows: (1) A percolation model was established, incorporating factors such as coal body strength coefficient, tortuosity fractal dimension, effective porosity, volume fractal dimension, and pore throat radius. Through comparative calculations, this model measures the water injection capacity of coals across different regions such as Inner Mongolia, Tongfuxin, Meihuajing, Dahuang Mountain, and Ciyaogou. (2) The main factors affecting coal seam water injection capacity, ranked from most to least significant, include the coal body strength coefficient, tortuosity fractal dimension, effective porosity, volume fractal dimension, and pore throat radius. The coal body strength coefficient demonstrated the highest sensitivity at 16.765, whereas the pore throat radius had the lowest sensitivity at 0.00117. (3) The study thoroughly evaluated how these key factors affect water injection capacity. The relationship between water injection capacity and strength coefficient follows a sinusoidal function curve distribution. Water injection capacity increases with effective porosity and decreases with higher tortuosity fractal dimension and volume fractal dimensions. The research results provide a solid theoretical basis for further improving coal seam water injection percolation theory, enhancing wetting effects, and preventing mine dust. |
| format | Article |
| id | doaj-art-627d9c4336a9456fb6785a4d26cf45d4 |
| institution | Kabale University |
| issn | 2095-9389 |
| language | zho |
| publishDate | 2025-02-01 |
| publisher | Science Press |
| record_format | Article |
| series | 工程科学学报 |
| spelling | doaj-art-627d9c4336a9456fb6785a4d26cf45d42025-01-03T01:21:00ZzhoScience Press工程科学学报2095-93892025-02-0147227128110.13374/j.issn2095-9389.2024.04.28.002240428-0002Construction of water injection seepage model for coal body and microscopic dominant influence lawEnmao WANG0Gang WANG1Shuliang XIE2Hongzhao WEI3Jing FENG4Handan LIANG5College of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCoal seam water injection technology plays a vital role in diminishing dust formation in mining operations by humidifying coal masses, thereby minimizing the dispersion of airborne particulate matter. This technique is crucial for managing dust in underground operations. As mining operations reach greater depths and face diverse geological challenges, understanding the impact of various factors on coal seam water injection becomes crucial. These factors include the inherent properties of coal bodies and the sizes of pores and fractures. Without this knowledge, predicting the extent of moisture penetration is unfeasible, hindering moisturization. Consequently, to enhance the effectiveness of coal seam water injection, this research investigates the primary factors influencing the process. Initially, we developed a percolation model, incorporating elements such as pore throats, equivalent pore diameter, effective porosity, capillary bundles, tortuosity, and flow paths. Furthermore, an online CT scanning loading percolation system was used to reconstruct three-dimensional visualizations of effective microfracture structures in coal bodies from five mines with varying metamorphic degrees: Inner Mongolia, Tongfuxin, Meihuajing, Dahuang Mountain, and Ciyaogou. The fractal theory was applied to extract parameters for calculating effective connected pores and fractures. In addition, experiments were conducted to measure coal permeability from these five mines, validating the model. Finally, the study introduced “sensitivity” to characterize the impact of various factors on seepage flow. By applying the Morris screening method, we combined numerical analysis with the percolation model to quantitatively screen main controlling factors such as coal body strength coefficient, tortuosity fractal dimension, effective porosity, volume fractal dimension, and pore throat radius. Their influence on water injection capacity was analyzed. The main conclusions were as follows: (1) A percolation model was established, incorporating factors such as coal body strength coefficient, tortuosity fractal dimension, effective porosity, volume fractal dimension, and pore throat radius. Through comparative calculations, this model measures the water injection capacity of coals across different regions such as Inner Mongolia, Tongfuxin, Meihuajing, Dahuang Mountain, and Ciyaogou. (2) The main factors affecting coal seam water injection capacity, ranked from most to least significant, include the coal body strength coefficient, tortuosity fractal dimension, effective porosity, volume fractal dimension, and pore throat radius. The coal body strength coefficient demonstrated the highest sensitivity at 16.765, whereas the pore throat radius had the lowest sensitivity at 0.00117. (3) The study thoroughly evaluated how these key factors affect water injection capacity. The relationship between water injection capacity and strength coefficient follows a sinusoidal function curve distribution. Water injection capacity increases with effective porosity and decreases with higher tortuosity fractal dimension and volume fractal dimensions. The research results provide a solid theoretical basis for further improving coal seam water injection percolation theory, enhancing wetting effects, and preventing mine dust.http://cje.ustb.edu.cn/article/doi/10.13374/j.issn2095-9389.2024.04.28.002coal seam water injectioneffectively connected pore cracksseepage flow modelmain controlling factorscomputed tomography |
| spellingShingle | Enmao WANG Gang WANG Shuliang XIE Hongzhao WEI Jing FENG Handan LIANG Construction of water injection seepage model for coal body and microscopic dominant influence law 工程科学学报 coal seam water injection effectively connected pore cracks seepage flow model main controlling factors computed tomography |
| title | Construction of water injection seepage model for coal body and microscopic dominant influence law |
| title_full | Construction of water injection seepage model for coal body and microscopic dominant influence law |
| title_fullStr | Construction of water injection seepage model for coal body and microscopic dominant influence law |
| title_full_unstemmed | Construction of water injection seepage model for coal body and microscopic dominant influence law |
| title_short | Construction of water injection seepage model for coal body and microscopic dominant influence law |
| title_sort | construction of water injection seepage model for coal body and microscopic dominant influence law |
| topic | coal seam water injection effectively connected pore cracks seepage flow model main controlling factors computed tomography |
| url | http://cje.ustb.edu.cn/article/doi/10.13374/j.issn2095-9389.2024.04.28.002 |
| work_keys_str_mv | AT enmaowang constructionofwaterinjectionseepagemodelforcoalbodyandmicroscopicdominantinfluencelaw AT gangwang constructionofwaterinjectionseepagemodelforcoalbodyandmicroscopicdominantinfluencelaw AT shuliangxie constructionofwaterinjectionseepagemodelforcoalbodyandmicroscopicdominantinfluencelaw AT hongzhaowei constructionofwaterinjectionseepagemodelforcoalbodyandmicroscopicdominantinfluencelaw AT jingfeng constructionofwaterinjectionseepagemodelforcoalbodyandmicroscopicdominantinfluencelaw AT handanliang constructionofwaterinjectionseepagemodelforcoalbodyandmicroscopicdominantinfluencelaw |