Curvature-Varying Hyperbolic Trace TFPF for Seismic Random Noise Attenuation

Abstract

Time-frequency peak filtering (TFPF) is effective in suppressing random noise in seismic records. However, the signal may be attenuated at the same time, especially for the high-frequency signal. In this letter, we propose a curvature-varying hyperbolic trace TFPF to reduce the error. We sample the seismic record along the time–distance curve of the event. For the event area, the sampled signal in each sampling trace is approximately linear (low frequency) due to the correlation of the signal along the time–distance curve, which reduces the bias of the seismic wave estimation brought by TFPF. However, the curvatures of seismic events are various, so adopting traces with a single curvature to sample the whole seismic record is not reasonable. As the events with different curvatures are located in different areas in Radon domain, the events with almost the same curvature can be separated out by an inverse Radon transform of only part of the Radon data. The optimal hyperbolic sampling traces are chosen for each separated subrecord, and we filter the data along the traces by TFPF. The denoised signal is reconstructed by summing all of the processed subrecords. Compared with TFPF, our method gets a good performance in both seismic reflection event preservation and noise attenuation.