1 State Key Laboratory of Safe Mining of Deep Coal and Environmental Protection, Huainan Mining (Group) Co., Ltd., Huainan 232000, China
2 Ping’an Coal Mining Engineering Technology Research Institute Co., Ltd., Huainan 232001, China
3 Key Laboratory of Coupled Hazards Prevention and Control in Deep Coal Mining, National Mine Safety Administration, Huaihe Energy Holdings Group Co., Ltd., Huainan 232000, China
4 Ping’an Coal Mine Gas Control National Engineering Research Center Co., Ltd., Huainan 232000, China
5 School of Earth and Environment, Anhui University of Science and Technology, Huainan 232001, China
6 College of Resources and Environmental Engineering, Hefei University of Technology, Hefei 230009, China
Aiming at the technical problem that it is difficult to distinguish “lithological low resistance” from “water-bearing low resistance” in the limestone aquifer of Taiyuan Formation at the floor of Group A coal face in Huainan mining area, taking the 13421 working face of Gubei Coal Mine as the engineering background, the application research of dual-frequency induced polarization (DFIP) method was systematically carried out by adopting the technical route of “numerical simulation-physical simulation-field detection-comprehensive verification”. The results of numerical and physical simulation show that water-rich areas present the typical response characteristic of “low resistivity + high frequency dispersion rate”, which verifies the feasibility of this method to solve “low resistance multi-interpretability” from the theoretical level. Moreover, the positioning accuracy of dual-frequency IP omni-directional detection technology for anomalies is significantly better than that of traditional methods. In the field of 13421 working face of Gubei Coal Mine, fan-shaped scanning with multiple measuring points was arranged through the dual-frequency IP detection system, and two water-rich abnormal areas were successfully delineated within the depth of 70 m under the floor. Through drilling verification and comparative analysis of three-dimensional electrical method, the delineated abnormal areas have a high degree of coincidence with borehole water outflow points, and the water-rich identification accuracy is significantly superior to that of traditional geophysical exploration technologies. Meanwhile, it is confirmed that the water conductivity of faults in the working face is weak, which is consistent with the actual on-site exposure. The research shows that the dual-frequency IP method can realize the accurate detection and positioning of limestone water hazards at the floor of group A coal, and provide reliable technical support for the safe and efficient mining of Group A coal in Huainan mining area.
HUANG Gang, REN Bo, HAN Yun-chun, YU Guo-feng, LUO Yong, HU Xiong-wu, ZHOU Guan-qun, WEI Ting-shuang, HAN Bi-wu, TAN Xi-ning.
Application of Dual Frequency Induced Polarization Method in Floor Water Disaster Detection of Group A Coal Face in Huainan Mining Area[J].
Science Technology and Engineering, 2026, 26(28): 12022-12037 DOI:10.12404/j.issn.1671-1815.2507781
ZhangHongzhong, LiuQimeng, LiShucai. Mechanism and prevention technology of water inrush from coal floor of group A in Huainan mining area[J]. Journal of Rock Mechanics and Engineering, 2020, 39(S1): 2890-2898.
LiLianchong, YaoChengyu, WeiTingshuang, et al. Determination of floor failure zone depth in working face of group A coal mining in Huainan mining area[J]. Safety in Coal Mines, 2022, 53(1): 212-218.
HuangGang, RenBo, HanYunchun, et al. Safety evaluation of floor failure depth of group a coal seam in paner coal mine of Huainan mining area[J]. Coal Engineering, 2025, 57(5): 70-76.
ZengXiaoying, SunJingjing. Study on hydrogeological conditions of limestone in coal floor of group A in Panbei coal mine[J]. Groundwater, 2018, 40(3): 118-119.
ShiLongqing, QiuMei, ZhuLu, et al. Study on floor water inrush mechanism of lower group coal mining in north China type coalfield[J]. Journal of Coal Industry, 2015, 40(5): 973-984.
WuRongxin, JiangHao, SunBinyang. Development law of mining-induced overburden fractures based on FLAC3D and parallel electrical method[J]. Science Technology and Engineering, 2026, 26(7): 2812-2822.
DongShuning, LiuQisheng, HuWeiyue. Current situation and development trend of water disaster prevention technology in China[J]. Coal Science and Technology, 2020, 48(1): 1-13.
YinShangxian, LianHuiqing, LiuDemin, et al. Research status and Prospect of water inrush mechanism and prevention and control in deep coal mining[J]. Acta Coal, 2019, 44(8): 2417-2426.
ZhuNan, DongYi, GuoKai, et al. Bayesian rapid discrimination of coal mine goaf types based on transient electromagnetic multi-parameters[J]. Science Technology and Engineering, 2025, 25(29): 12364-12371.
LiuShucai, LiuZhixin, JiangZhihai. Exploration technology and application of mine direct current method[J]. Journal of Coal Industry, 2019, 44(7): 2105-2113.
HuangGang, HanYunchun, YuGuofeng, et al. Application of all fiber microseismic monitoring technology in floor water inrush monitoring[J]. Industrial and Mining Automation, 2024, 50(6): 36-45.
ChenRujun, HuangZhe, LiDiquan. Application of dual frequency IP method in mine water disaster detection[J]. Mining Research and Development, 2022, 42(8): 156-161.
ZhouGuanqun, CuiYing, LiangXikai, et al. Application of 3D parallel high-density electrical method in site investigation of liuguo chemical phosphogypsum yard[J]. Science Technology and Engineering, 2024, 24(2): 495-505.
WangXudong, GaoGuangzhe, XuMaoye, et al. Transient electromagnetic laterally constrained inversion for fine exploration of deep-buried coal seams and water-bearing structures in Ordos[J]. Science Technology and Engineering, 2025, 25(35): 14980-14989.
YueJianhua, YangHaiyan, DengJuzhi. Some problems and development trend of mine DC electrical prospecting[J]. Geophysical Progress, 2016, 31(1): 370-377.
HuXiongwu, ZhangPingsong, LiuShengdong. Influence of low resistance shielding layer detected by mine electrical method and its correction method[J]. Progress in Geophysics, 2019, 34(3): 1240-1247.
HuangGang, YuGuofeng, HanYunchun, et al. Research on application of electrical intelligent monitoring technology for water diversion channel in coal mining face[J]. Coal Engineering, 2024, 56(2): 92-98.
JiangZhihai, LuLaiping, LiuShucai. Three dimensional numerical simulation of full space electrical exploration under the influence of roadway[J]. Journal of China University of Mining and Technology, 2017, 46(3): 494-500.
HuXiongwu, HuYuanrong, WuRongxin, et al. Frequency domain induced polarization response characteristics of aquifer in front of coal mine roadway excavation[J]. Coalfield Geology and Exploration, 2025, 53(2): 179-190.
HuXiongwu, YuHao, WangYing, et al. Coal mine roadway po-sitive and negative three pole dual frequency IP detection method[J]. Coal Science and Technology, 2026, 54(2): 401-412.
[53]
余国锋. 基于微震和神经网络的煤层底板突水预警技术研究[D]. 淮南: 安徽理工大学, 2023.
[54]
YuGuofeng. Research on early warning technology of water inrush from coal seam floor based on microseismic and neural network[D]. Huainan: Anhui University of Science and Technology, 2023.
ZhouGuanqun, XuShaotian, ZhangWeixin, et al. Research on Simulation of DC electrical method advanced exploration with two hole observation system at different angles[J]. Coalfield Geology and Exploration, 2025, 53(11): 23-33.
HuXiongwu, XuBiao, ZhangPingsong, et al. Numerical simulation and detection test of double frequency induced polarization method for floor water in coal mining face[J]. Journal of Coal Industry, 2022, 47(8): 3024-3036.
ZhangYugui, LiuShucai, SunJianbo. Experimental study on the relationship between complex resistivity dispersion characteristics and water content of coal[J]. Journal of Coal, 2018, 43(10): 2897-2904.
DuYibo, LiuZhimin, LiLei. Research on the application of mine induced polarization method in water disaster detection of coal roadway[J]. China Coal Geology, 2021, 33(5): 81-86.
LiuShengdong, ZhangJintao, ZhouGuanqun. Induced polarization response model of mine with water conducting structure and its application[J]. Acta Geophysical Sinica, 2020, 63(7): 2765-2776.
ZhouGuanqun, LuoShiling, ZhangWeixin, et al. Microseismic signal recognition and classification based on multi-modal EWT-CNN[J]. Science Technology and Engineering, 2025, 25(30): 12786-12794.