Prediction of Fractures in Coal Seams with Multi-component Seismic Data

Fractures that develop in coal seams threaten safety in many ways, but they can be predicted using fracture parameters derived from seismic data. However, the post-stack split shear waves are difficult to thoroughly separate by Alford rotation due to wavefield mixing. We propose a method of predicting fractures in a coal seam using multi-component seismic data, which was applied to coal seam 13-1 of the Huainan coalfield, China. We employed the Alford rotation to separate the split PS-waves (P-to-S converted waves) and perform interlayer travel-time inversion of the fast shear waves using geophysical logs, rock-physics parameters, and tunnel-excavation information as constraints. However, post-stack wavefield mixing of the coal seam interfered with the Alford rotation of the real post-stack seismic data. Therefore, we only performed the Alford rotation on radial and transverse component post-stack sections to derive fracture azimuths, which were then applied to the pre-stack separation of the split PS-waves. Using joint PP- and PS-wave inversion, anisotropy parameters were derived for use in fracture prediction. Finally, we predicted unsafe mining areas with a high probability of coal and gas outbursts. The application results were verified by excavation data from the mine tunnels. Our method contributes to fracture prediction on coal mine safety.