Three-dimensional, collaborative detection approach for fire zones in shallowly buried coal seams and its application

Authors

• FAN Kaixiang, State Key Laboratory of Disaster Prevention and Ecology Protection in Open-pit Coal Mines, Shandong University of Science and Technology, Qingdao 266590, China;College of Energy and Mining Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaFollow
• HU Xiangming, State Key Laboratory of Disaster Prevention and Ecology Protection in Open-pit Coal Mines, Shandong University of Science and Technology, Qingdao 266590, China;College of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaFollow
• HONG Haibo, College of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaFollow
• DONG Hao, College of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao 266590, China
• YU Shijian, College of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao 266590, China
• WEI Zhengrong, College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China
• GUO Yongxiang, College of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao 266590, China

Abstract

Objective Fire zones in shallowly buried coal seams have long restricted safe and efficient coal mining due to their considerably hidden and hazardous nature. However, individual methods for fire source detection are susceptible to geological conditions and ambient noise, suffering from limited detection dimensions and the presence of technical blind spots. Therefore, they fail to accurately localize hidden fire sources in shallow coal seams. Methods This study proposes a three-dimensional, collaborative multi-source detection approach that combines the self-potential (SP) method, the radon measurement (Rn) method, electrical resistivity tomography (ERT; also referred to as high-density resistivity method), and the transient electromagnetic method (TEM). Accordingly, the technical pathway is developed, consisting of fire zone delineation in the horizontal direction, fire source positioning in the vertical direction, and multi-source constraint. Specifically, fire zones in coal seams are preliminarily identified using the SP and Rn methods in the horizontal direction, with interference zones being ruled out through anomaly matching. For the hazardous zones delineated horizontally, vertical detection is conducted using the ERT and TEM methods to jointly determine the depths of fire sources. Finally, the detection results are verified through borehole thermometry. Results and Conclusions The proposed approach was applied to a shallowly buried coal seam in Inner Mongolia. The application results indicate that nine suspected fire zones were identified through SP-Rn joint detection after interference zones were ruled out. Then, three fire sources were localized through the vertical ERT-TEM joint detection. The borehole thermometry revealed the presence of high-temperature anomalies with temperatures ranging from 300 ℃ to 450 ℃ in the anomalous zones detected, highly consistent with the detection results. Compared to individual SP and Rn methods, the combination of both increased the detection accuracy by 70.03% and 42.76%, respectively in detecting anomalous zones in the horizontal direction, significantly reducing the misidentification rate of fire zones in the horizontal direction. Compared to individual ERT and TEM methods, the combination of both enhanced the accuracy by 86.07% and 87.49% for survey line 1 and 76.78% and 69.46% for survey line 2, respectively. Therefore, the three-dimensional, collaborative multi-source detection approach can significantly reduce the multiplicity of solutions of individual detection methods, effectively addressing the engineering challenges of difficult identification and low positioning accuracy in identifying fire sources in shallowly buried coal seams. The proposed approach provides a technical solution deserving widespread application for the rapid identification and precise control of fire zones in shallowly buried coal seams.

Keywords

shallowly buried coal seam, hidden fire source, self-potential (SP) method, radon measurement (Rn) method, electrical resistivity tomography (ERT), transient electromagnetic method (TEM)

DOI

10.12363/issn.1001-1986.25.12.0890

Recommended Citation

FAN Kaixiang, HU Xiangming, HONG Haibo, et al. (2026) "Three-dimensional, collaborative detection approach for fire zones in shallowly buried coal seams and its application," Coal Geology & Exploration: Vol. 54: Iss. 7, Article 20.
DOI: 10.12363/issn.1001-1986.25.12.0890
Available at: https://cge.researchcommons.org/journal/vol54/iss7/20

Reference

[1] 王凯,王喆,韩涛,等. 表面横向风流作用下煤体的内部燃烧蔓延规律[J]. 工程科学学报,2024,46(2):187−198. WANG Kai,WANG Zhe,HAN Tao,et al. Spread law of loose coal combustion under lateral wind flow conditions on the surface[J]. Chinese Journal of Engineering,2024,46(2):187−198.

[2] 张嬿妮,侯云超,刘博,等. 卤盐载体无机盐阻化煤自燃的机理及性能[J]. 工程科学学报,2021,43(10):1295−1303. ZHANG Yanni,HOU Yunchao,LIU Bo,et al. Mechanism and performance of coal spontaneous combustion with a halide carrier inorganic salt inhibitor[J]. Chinese Journal of Engineering,2021,43(10):1295−1303.

[3] 罗振敏,张利冬,宋泽阳. 基于全连接的长短期记忆网络实现采空区CO多步预测[J]. 清华大学学报(自然科学版),2024,64(6):940−952. LUO Zhenmin,ZHANG Lidong,SONG Zeyang. Multistep prediction of CO in the extraction zone based on a fully connected long short-term memory network[J]. Journal of Tsinghua University (Science and Technology),2024,64(6):940−952.

[4] HU Xiangming,SU Minghui,DONG Hao,et al. Study on coal spontaneous combustion dangerous zone under different air leakage in the shallow buried coal seam fissure[J]. Combustion Science and Technology,2024,196(17):4811−4835.

[5] 石智军,姚克,姚宁平,等. 我国煤矿井下坑道钻探技术装备40年发展与展望[J]. 煤炭科学技术,2020,48(4):1−34. SHI Zhijun,YAO Ke,YAO Ningping,et al. 40 years of development and prospect on underground coal mine tunnel drilling technology and equipment in China[J]. Coal Science and Technology,2020,48(4):1−34.

[6] LIU Jinglong,WANG Yunjia,YAN Shiyong,et al. Underground coal fire detection and monitoring based on landsat-8 and sentinel-1 data sets in Miquan fire area,Xinjiang[J]. Remote Sensing,2021,13(6):1141.

[7] 孙继平,范伟强. 矿井红外热成像远距离测温误差分析与精确测温方法[J]. 煤炭学报,2022,47(4):1709−1722. SUN Jiping,FAN Weiqiang. Error analysis and accurate temperature measurement method of infrared thermal imaging long-distance temperature measurement in underground mine[J]. Journal of China Coal Society,2022,47(4):1709−1722.

[8] SHAO Zhenlu,WANG Deming,CAO Kai,et al. Treatment of smoldering coal refuse piles:An application in China[J]. Environmental Technology,2020,41(23):3105−3118.

[9] DONG Kaili,ZHOU Bin,ZHANG Yulong,et al. Study on radon gas transport law of overlying rock layer under different geological conditions of coal spontaneous combustion[J]. Journal of Radioanalytical and Nuclear Chemistry,2024,333(12):6379−6389.

[10] 贺小元,王峰,雒铮,等. 高密度电法在煤火勘查中的应用:以活鸡兔煤矿为例[J]. 中国矿业,2022,31(1):168−174. HE Xiaoyuan,WANG Feng,LUO Zheng,et al. Application of high-density electrical method to prospect coal fire:Taking Huojitu coal mine as an example[J]. China Mining Magazine,2022,31(1):168−174.

[11] 于永宁,李雄伟,石磊,等. 时移航空磁法在煤矿火烧区探测中的应用研究[J]. 工矿自动化,2023,49(8):114−120. YU Yongning,LI Xiongwei,SHI Lei,et al. Research on the application of time shifting aeromagnetic method in detecting coal mine burning areas[J]. Journal of Mine Automation,2023,49(8):114−120.

[12] LI Feng,LI Jiale,LIU Xiaoyang,et al. Coal fire detection and evolution of trend analysis based on CBERS-04 thermal infrared imagery[J]. Environmental Earth Sciences,2020,79(16):384.

[13] 黄洁,张锦. 基于多源遥感影像的矿区煤火探测方法[J]. 煤炭工程,2024,56(7):174−180. HUANG Jie,ZHANG Jin. Coal fire detection method in mining area based on multi-source remote sensing images[J]. Coal Engineering,2024,56(7):174−180.

[14] SHAO Zhenlu,ZHANG Guofu,ZHOU Tao,et al. Locating the scope and depth of coal fires based on magnetic and electrical data[J]. Pure and Applied Geophysics,2023,180(11):3883−3900.

[15] 马砺,雷燕飞,苏耀军,等. 近距离煤层开采上覆采空区火区探测及治理[J]. 矿业安全与环保,2020,47(2):76−80. MA Li,LEI Yanfei,SU Yaojun,et al. Fire detection and control of overlying goaf in close-distance coal seam mining[J]. Mining Safety & Environmental Protection,2020,47(2):76−80.

[16] YANG Yanlong,ZHAO Ci,DI Yaxiao,et al. Geological exploration of coal mine burnt rock and waterlogged area boundary based on transient electromagnetic and high-density electrical resistivity[J]. Scientific Reports,2024,14:5105.

[17] 郭建磊,李雄伟,侯彦威,等. 综合探测方法在煤矸石场自燃区探测中的应用[J]. 煤炭工程,2025,57(1):177−181. GUO Jianlei,LI Xiongwei,HOU Yanwei,et al. Application of comprehensive detection method for spontaneous combustion zone detection in coal gangue yard[J]. Coal Engineering,2025,57(1):177−181.

[18] KUMAR S,PAL S K. Underground coal fire mapping using analysis of self-potential (SP) data collected from Akashkinaree colliery,Jharia coalfield,India[J]. Journal of the Geological Society of India,2020,95(4):350−358.

[19] 胡相明,吴佰谦,董浩,等. 小窑隐蔽火源精准探测及帷幕注浆高效治理研究[J]. 工矿自动化,2025,51(7):44−51. HU Xiangming,WU Baiqian,DONG Hao,et al. Accurate detection of concealed fire sources in small coal mines and efficient control via curtain grouting[J]. Journal of Mine Automation,2025,51(7):44−51.

[20] 葛欢,韩猛,刘磊,等. 高温煤岩体电性特征及地球物理数值模拟研究[J]. 煤矿安全,2023,54(11):92−98. GE Huan,HAN Meng,LIU Lei,et al. Study on electrical characteristics and geophysical numerical simulation of high temperature coal and rock mass[J]. Safety in Coal Mines,2023,54(11):92−98.

[21] SHAO Zhenlu,WANG Deming,WANG Yanming,et al. Theory and application of magnetic and self-potential methods in the detection of the Heshituoluogai coal fire,China[J]. Journal of Applied Geophysics,2014,104:64−74.

[22] 刘伟,甘伏平,张庆玉,等. 岩溶区页岩气勘探中的近地表地球物理探测技术应用研究[J]. 地质与勘探,2023,59(1):113−121. LIU Wei,GAN Fuping,ZHANG Qingyu,et al. Application of near-surface geophysical techniques in shale gas exploration in karst area[J]. Geology and Exploration,2023,59(1):113−121.

[23] 赵禹深,许献磊,曹仕龙,等. 地下煤火探测技术及工程应用综述[J]. 矿业科学学报,2025,10(1):24−39. ZHAO Yushen,XU Xianlei,CAO Shilong,et al. A review of underground coal fire detection technology and engineering application[J]. Journal of Mining Science and Technology,2025,10(1):24−39.

[24] 李忠平. 基于高密度电法温纳装置的三维电阻率反演应用[J]. 地球物理学进展,2020,35(3):970−975. LI Zhongping. Application of 3-D resistivity inversion based on Winner device of high density electricity method[J]. Progress in Geophysics,2020,35(3):970−975.

[25] 鲁凯亮,岳建华,樊亚楠,等. 伪随机波形瞬变电磁全时响应数值方法及应用[J]. 煤炭学报,2024,49(增刊2):1116−1129. LU Kailiang,YUE Jianhua,FAN Ya'nan,et al. Numerical method and application of transient electromagnetic full-time responses of pseudo-random waveforms[J]. Journal of China Coal Society,2024,49(Sup.2):1116−1129.

[26] KARAOULIS M,REVIL A,MAO D. Localization of a coal seam fire using combined self-potential and resistivity data[J]. International Journal of Coal Geology,2014,128/129:109−118.

[27] 胡相明,洪海博,董浩,等. "测氡–磁"法探测小窑自然发火技术的应用研究[J]. 煤炭科学技术,2025,53(2):200−210. HU Xiangming,HONG Haibo,DONG Hao,et al. Research on the application of "radon measurement-magnetic" method to detect spontaneous combustion technology in small coal mines[J]. Coal Science and Technology,2025,53(2):200−210.

[28] 李晓春,李喜平,徐广明. 自然电位法在煤田火区勘察中的应用[J]. 物探与化探,2012,36(3):382−385. LI Xiaochun,LI Xiping,XU Guangming. The anomaly investigation of self-potential method for coal fire area survey[J]. Geophysical and Geochemical Exploration,2012,36(3):382−385.

[29] 邵振鲁,王德明,王雁鸣. 高密度电法探测煤火的模拟及应用研究[J]. 采矿与安全工程学报,2013,30(3):468−474. SHAO Zhenlu,WANG Deming,WANG Yanming. Simulation of high-density electrical method in detecting coal fires and its application[J]. Journal of Mining and Safety Engineering,2013,30(3):468−474.

[30] 程铭,杨迪琨,罗强,等. 基于三维快速正反演的瞬变电磁数据解释技术及其应用方法[J]. 地球物理学报,2025,68(1):342−354. CHENG Ming,YANG Dikun,LUO Qiang,et al. Interpretation and application of three-dimensional fast forward and inversion for transient electromagnetic data[J]. Chinese Journal of Geophysics,2025,68(1):342−354.

[31] 邵振鲁,张国富,梁运涛,等. 高温条件下砂岩和页岩的磁电参数变化特征[J]. 中国矿业大学学报,2023,52(4):672−686. SHAO Zhenlu,ZHANG Guofu,LIANG Yuntao,et al. Magnetic and electrical parameter variations in sandstone and shale at high temperatures[J]. Journal of China University of Mining & Technology,2023,52(4):672−686.

[32] 马子钧,杨海燕,李文宇,等. 煤层自燃区隐蔽火源的综合地球物理探测应用[J]. 煤田地质与勘探,2023,51(12):131−137. MA Zijun,YANG Haiyan,LI Wenyu,et al. Application of integrated geophysical surveys in the identification of hidden fire sources in spontaneous combustion zones in coal seams[J]. Coal Geology & Exploration,2023,51(12):131−137.

[33] 邓军,刘登祯. 煤自燃监测预警技术研究进展及展望[J]. 工矿自动化,2025,51(7):1−14. DENG Jun,LIU Dengzhen. Research progress and prospects of coal spontaneous combustion monitoring and early warning technology[J]. Journal of Mine Automation,2025,51(7):1−14.

[34] SHAO Zhenlu,WANG Deming,WANG Yanming,et al. Experimental study of the self-potential anomaly caused by coal fires[J]. Journal of Applied Geophysics,2017,145:124−132.