Radial-Trace Time–Frequency Peak Filtering Based on Correlation Integral

Time-frequency peak filtering (TFPF) has been widely applied to suppress the random noise in seismic data in recent years. Conventional TFPF adopts a pseudo-Wigner-Ville distribution to ensure the approximate linearity of the signal. However, a short window length (WL) cannot effectively attenuate the random noise and a long WL can hardly recover the subtle structures of seismic events. In this letter, we discuss the different correlation integral values of signal and noise in the radial-trace domain for identifying the noise and signal segments. Then, a longer WL according to the noise intensity is used to remove the random noise and a shorter WL according to the frequency characteristics of the signal is used to preserve the details of the signal. The experiment results on both the synthetic model and the field seismic data show that this method can effectively remove noise from seismic record and maintain the amplitude of the valid signal.