An Optimized Detection Approach to Subsurface Coalfield Spontaneous Combustion Areas Using Airborne Magnetic Data

It is of great significance to clarify the ranges and states of subsurface coalfield spontaneous combustion areas for coal mining and disaster management. Since the spontaneous combustion of coal seams produces highly magnetic burnt rocks and high temperatures, magnetic and infrared remote sensing measurements are commonly used for detection. To infer the accurate ranges of highly magnetic burnt rocks, we propose a three-dimensional constrained magnetization vector inversion method based on coal seam information, which considers highly magnetic burnt rocks to be produced via the combustion of a coal seam and to have thermal remanence, and this method can more accurately obtain the ranges of magnetic source for deducing coalfield spontaneous combustion areas. Combined with infrared remote sensing temperature measurement data, we analyze the range, state, and future spread direction of coalfield spontaneous combustion areas in Liaoning Province, China, according to the relative positions of high-temperature areas and highly magnetic burnt rocks. Based on the inversion results, we divided the survey area into nine blocks and obtained corresponding interpretation results. The accuracy of the interpretation was verified through drilling. This provides comprehensive spontaneous combustion area information for coal mining and disaster management.