Coal Fire Study Over East Basuria Colliery

Abstract

Coal seam fire and coal mine fire as well as fire in coal waste or storage piles are worldwide general phenomenon and pose a great threat to the national economy, environment, ecology and health of peoples living in its proximity. In 17th century the coal mining in India first started in Raniganj coalfield in an ill- planned way and some planned mining started in an about 1820. In early days, the collieries were owned by several small companies and owners. In 1971, the Indian coal industry was nationalized under Coal India (CIL) and Bharat Coking Coal Limited (BCCL) was formed as a subsidiary of CIL. The haphazard coal mining without suitable mine planning pose several paramount threats with environmental hazards. At present it is spread over more than 70 areas. The mapping and understanding of hidden subsurface coal fire is a challenging task. In view of this, the present study was attempted for Coal fire mapping and detection of previously burnt coal fire regions in East Basuria colliery, a part of the Jharia coal field, India. Magnetic and Self Potential (SP) methods of geophysical investigation have been used for coal fire mapping over parts of Jharia Coalfield, India mainly due to cost-effectiveness with good accuracy and faster data acquisition. SP study works based on redox potential generated by oxidation of coal and also on Thomson potential due to temperature gradient. Whereas, magnetic study allows to map the previously burned, currently burning and unburned locations based on the magnetic properties of the materials and their changes with temperatures above or below Curie temperature. SP data have been analysed using Particle Swarm Optimization (PSO) technique. Magnetic data have been corrected for diurnal variation followed by correction using reduced to magnetic pole (RTP). The corrected magnetic data further, enhanced using north-south and east-west horizontal derivatives, first vertical derivative, second vertical derivative, Total horizontal derivative, Analytical signal, Tilt Derivative and downward continuation techniques. Radially averaged power spectrum (RAPS) of magnetic data has been calculated to estimate the average depth to the top of different layers. Different sets of 3D Euler’s depth solutions have been estimated separately for each various source geometry (SI = 0, 0.5, 1.0, 1.5, 2, 2.5 and 3) to understand the possible source geometry of complex fire activities. PSO inversion of SP data reveals that the depth of the coal fire extends between 10 and 12 m below the surface. The study based on SP method over East Basuria reveals that the geometry of subsurface coal combustion is possibly similar to the inclined sheet with relatively large horizontal extension. The large variations in inclination angles of the causative sources may possibly indicate complex nature of fire propagation along different inclined fractured planes which are generated in multiphase coal seam combustion. It is observed that the total magnetic field intensity anomaly of the area varies approximately from 44,850 to 47,460 nT and the residual magnetic anomaly varies approximately from −1323 to 1253 nT. The range of the magnetic anomaly after RTP is approximately 1050–1450 nT. Twelve low (L1–L12) and nine high (H1–H9) RTP magnetic anomalies have been delineated from RTP of East Basuria Colliery for 2012. The average depth to the top of different layers estimated using radially averaged power spectrum (RAPS) over East Basuria colliery are (i) 10 m, (ii) 18 m and (iii) 38 m for 2012. It is observed that the average depth of the estimated Euler’s solution for different SI is varies from 10 to 26 m for 2012. Possible fire affected, non-fire and possible baked and cool areas have been delineated as (i) 21%, (ii) 36%, (iii) 42% for the years 2012 based on RTP anomaly distribution over East Basuria colliery. The results prove the efficacy of the SP and magnetic methods for characterization of causative sources associated with coal fires over East Basuria colliery, Jharia coalfield, India.