Traditional seismic interpretation of surface seismic data is focused primarily on seismic oscillation. Rich singularity information carried by, but deeply buried in, seismic data is often ignored. We show that wavelet-based singularity analysis reveals generic singularity information conducted from acoustic impedance to seismogram. The singularity exponents (known as H¿lder exponent α) calculated from seismic data are independent of amplitude and robust to phase changes and noises. These unique properties of α offer potentially important application in many fields, especially in studying seismic data interpretation, processing, inversion, and wave attenuation.