Sub-surface coal mine fires burn valuable resources and give rise to great threat in the local environs and people’s health. Jharia coal field is one of utmost fire affected coal fields in India. This paper deals with the study of sub-surface coal fire using self-potential (SP) method, a cost-effective and non-invasive passive geophysical technique. SP method in coal fire mapping works based on redox potential generated by oxidation of coal and also on Thomson potential due to temperature gradient. Initially, SP anomaly map generated using electrode drift corrected field data. The SP anomalies in the present study area vary from ∼95 to ∼ −40mV. SP anomaly map has been continued to a height of 10m from the ground to remove the possible shallow surface noises. The upward continued anomaly map has been enhanced using first vertical derivative. Further, Euler’s depth solutions have been estimated to understand possible geometry and source depth of sub-surface coal fires. The local geological map and field photograph corroborate well with the results for the characterization of coal seam fires.

中文翻译：

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使用从印度贾里亚煤田 Akashkinaree 煤矿收集的自电位 (SP) 数据分析绘制地下煤火图

地下煤矿火灾燃烧着宝贵的资源，对当地环境和人们的健康造成巨大威胁。Jharia 煤田是印度受火灾影响最大的煤田之一。本文使用自电位 (SP) 方法研究地下煤火，这是一种具有成本效益的非侵入性被动地球物理技术。煤火制图中的 SP 方法基于煤氧化产生的氧化还原电位以及温度梯度引起的汤姆逊电位。最初，SP 异常图使用电极漂移校正场数据生成。目前研究区的 SP 异常从~95 到~-40mV 不等。SP 异常图已继续到距地面 10m 的高度，以消除可能的浅表噪声。使用一阶垂直导数增强了向上的连续异常图。此外，Euler 的深度解已被估计以了解地下煤火的可能几何形状和源深度。当地地质图和现场照片与煤层火灾特征的结果相吻合。