Geological Behavior (GBR)

The increasing demand for efficient and sustainable coal extraction emphasizes the critical need for accurately characterizing coal seams. This study explores the utilization of multi-attribute seismic fusion technology to analyze the seismic response of coal seams in the Kashmir Basin. Through the application of a two-dimensional forward geological model incorporating coal layers and roadways, we extracted seismic attributes such as relative wave impedance, instantaneous amplitude, and frequency, aiming to assess their effectiveness in detecting anomalies caused by roadways within the coal seam. Our findings indicate that these attributes successfully capture variations in seismic response induced by roadways. However, individual attributes may face challenges in differentiation based on roadway fill material. To address this limitation, RGB multi-attribute fusion technology was employed. Compared to single attributes, the fused attribute offers a more comprehensive representation of geological features, enabling clearer visualization of tunnel boundaries and extraction of richer geological information. This methodology enhances the accuracy of seismic data interpretation and simplifies the delineation of complex geological structures within coal seams. This research underscores the potential of multi-attribute fusion technology in advancing coal seam characterization in the Kashmir Basin and beyond. The improved understanding of complex geological structures translates to optimized resource exploration strategies and more informed decision-making in the mining industry.