The accurate detection and identification of coal fires is the key to their effective prevention and control. Self-potential method is an important method to detect coal fires. However, existing research has not fully revealed the evolution of self-potential anomaly in coal fire areas. The interference signal processing technique and 3D inversion method have also not been developed or proposed, which results in the inability to locate the fire accurately in 3D. In this project, theoretical model of the self-potential field that under the influence of multi-geophysical factors is established. Laboratory experiments are also carried out to clarify the microscopic mechanism and macroscopic characteristics of the self-potential anomaly in coal fire areas. A model for synchronizing the self-potential field and temperature field in coal fire area is constructed, based on which the evolution law of self-potential anomaly is grasped. The convolution filtering technique is proposed to separate and suppress the random noise and system interference caused by non-fire factors to improve data signal-to-noise ratio and reliability. Then, the constitutive equation of correlation between surface self-potential field and underground 3D source current density is constructed. A 3D compact constrained inversion algorithm is proposed. Afterwards, field measurement in coal fire area is implemented and the data is used to verify the efficiency of the inversion results. The data processing technique and the inversion code are corrected and strengthened to improve the inversion efficiency and interpretation accuracy. Finally, the accurate stereoscopic targeting of the fire location is realized. The research results of the project can provide theoretical basis and technical support for the accurate detection of coal fire disasters, and have theoretical and practical significance for the efficient prevention and control of coal fires.
煤田火灾的精准探测和识别是煤火高效防治的关键,自然电位法是探测煤田火灾的一种重要方法,然而现有研究未能全面揭示火区自然电位异常演变规律,干扰信号处理及三维反演解释方法研究也未开展,导致不能精准定位火区的三维位置。本项目通过建立火区自然电场理论模型并开展物理模拟,阐明自然电位异常产生的微观机理及宏观特征;构建火区自然电场与温度场的协同变化表征方法,掌握自然电位异常演变规律;采用卷积滤波技术析离压制非煤火因素导致的随机噪声和系统干扰,提高数据信噪比及可靠度;构建地表自然电场与地下三维空间源电流密度的关联性本构方程,提出三维紧致约束反演算法;在火区现场开展实测,结合钻孔资料对反演结果进行验证和误差分析,逆向修正数据处理技术和三维反演算法,提高反演效率及解译精度,最终实现火区的三维精准靶向定位。项目研究成果可为煤火灾害的精准探测提供理论依据和技术支撑,对煤火的高效防治具有十分重要的理论和现实意义。
煤田火灾是危害我国能源安全与可持续发展的重大灾害,不仅烧毁大量不可再生的煤炭资源,还直接威胁煤矿的安全生产,严重破坏当地的生态环境,导致火区附近居民的生命和财产安全受到严重影响。煤火的准确探测是煤火研究的重点和煤田灭火工程的基础,对于提高煤田防灭火的有效性、经济性具有十分重要的现实意义。本项目针对煤田火灾三维反演解释与成像的技术难题,通过采用集理论分析、实验测试、数值仿真、物理模拟和现场应用为一体的综合研究方法,系统研究了煤田火灾自然电位异常产生机理和特征、自然电场演变规律以及三维反演解释方法,运用热电效应、“宏电池”模型及地下水渗流理论,揭示了煤田火区自然电位异常产生的微观机理;构建了煤火自然电位异常沙箱实验系统并开展了大量物理模拟实验,阐明了自然电位异常产生的宏观特征,掌握了煤田火灾不同延燃阶段自然电位异常演变规律;基于准静态低频条件下的Maxwell方程及偶极子理论推导了地表自然电场与地下三维空间火区电流密度的关联性本构方程,研究了电流密度紧致约束三维反演方法,成像得到了体积最小的火区燃烧中心,实现了火区的三维反演;在新疆、山西等煤田火区开展了现场地球物理探测与反演成像,定位了火区位置,并结合钻孔测温等资料进行了验证,实现了火区的立体靶向定位,为重大煤火灾害的高效治理提供了重要的支撑。
{{i.achievement_title}}
数据更新时间:2023-05-31
基于SSVEP 直接脑控机器人方向和速度研究
自然灾难地居民风险知觉与旅游支持度的关系研究——以汶川大地震重灾区北川和都江堰为例
混采地震数据高效高精度分离处理方法研究进展
自组装短肽SciobioⅡ对关节软骨损伤修复过程的探究
2000-2016年三江源区植被生长季NDVI变化及其对气候因子的响应
煤田火灾防治理论与方法
微重力强迫对流条件下火灾与非火灾颗粒群光散射规律与反演识别方法
风环境下室内火灾自然排烟过程与烟气扩散规律研究
直流牵引回流系统异常轨电位产生机理及限制方法研究