A method for fine-scale identification of collapse columns based on offset vector tile domain seismic data

Objectives and Methods The YQ mining area in the Qinshui Basin is characterized by complex seismic and geological conditions, as well as well-developed collapse columns and flexure structures. Consequently, conventional three-dimensional (3D) seismic exploration fails to meet the precision requirements for safe coal mining. By constructing a physical model based on the actual geological conditions of the study area, this study conducted forward modeling for the seismic responses of collapse columns under varying azimuths. Accordingly, the azimuthal anisotropy of the collapse columns were systematically analyzed. By employing a regular noise suppression technique based on curvelet transform, combined with prestack migration in the off vector tile (OVT) domain under varying azimuths and offsets, this study obtained high-fidelity five-dimensional (5D) seismic data. These data, combined with the seismic variance and coherence attributes and the watershed edge-detection algorithm, contributed to enhanced identification precision of collapse column boundaries.Results and ConclusionsThe results indicate that the most distinct collapse column boundaries were achieved under near offset and azimuths perpendicular to the longer axes of collapse columns. The processing of 5D OVT-domain seismic data effectively preserved azimuthal information and enhanced the capacity for identifying collapse columns, flexures, and faults. In the engineering practice, 62 collapse columns were newly identified, agreeing well with the verification results of an underground roadway. The proposed method enhances the seismic exploration precision of collapse columns under complex geological conditions, thereby providing technical support for safe coal mining.