Abstract: To address the urgent need for precision mining under complex topographic conditions at Yuanzigou Coal Mine, and in response to prominent issues in early 3D seismic data such as significant static correction problems, severe noise interference, substantial spatial variations in energy frequency, and low identification accuracy of small faults, a study on secondary fine processing and interpretation techniques of 3D seismic data was conducted. This research employed key technologies including joint static correction, fidelity-preserving noise suppression, and multi-parameter joint correction, significantly enhancing the signal-to-noise ratio, resolution, and fidelity of the data. During the interpretation phase, a multi-attribute fusion technique based on time-frequency continuous wavelet transform frequency division combined with RGB-IHS transformation was comprehensively applied, effectively improving the identification capability of small faults and coal seam boundaries. Application results demonstrate that the reprocessed data volume shows remarkable improvements in fault positioning, clarity of fault points, and convergence of diffracted waves. The new interpretation scheme redefined 46 faults, with significantly enhanced identification accuracy for faults with distance less than 5 meters. The determined faults exhibit an 85% consistency with actual roadway exposures, greatly improving the reliability of geological results. This provides precise geological assurance for mine safety production.