Parabolic-Trace Time-Frequency Peak Filtering for Seismic Random Noise Attenuation

Abstract

Time-frequency peak filtering (TFPF) has been applied to seismic random noise attenuation in recent years. In the conventional TFPF, a fixed window length (WL) is used for all frequencies signals. Different frequencies signals have different optimal WLs. A fixed WL cannot effectively attenuate random noise for all frequencies signals. In this letter, we present a nonlinear parabolic-trace TFPF (PT-TFPF) to resolve this problem. In the novel approach, a new data matrix is extracted by resampling seismic record along some parabolic traces. It contains both temporal and spatial information of the seismic record and is taken as the new input of TFPF. In each data sequence, the linearity of the effective signals is improved and the degree of improvement is associated with the similarity of the filtering trace to the event. In addition, the dominant frequencies of the effective signals are concentrated to be similar. Thus, a fixed WL can effectively attenuate the random noise with less distortion. The optimal filtering traces are selected based upon the Canny edge detection algorithm. Finally, the effectiveness of the proposed approach is tested on the synthetic record and field data. The experimental results show that the proposed PT-TFPF has better performance than the conventional TFPF.