Adaptive linear TFPF for seismic random noise attenuation

Abstract

Abstract To achieve a high level of seismic random noise suppression, the conventional time–frequency peak filtering (TFPF) has been adequately studied and applied in previous researches in recent years. A window is used to improve linearity, thereby achieving the unbiased estimates. However, applying a fixed window length to all frequencies signals will result in serious loss of effective components. The recently proposed the parabolic-trace TFPF (PT-TFPF) resample seismic record along parabolic-trace to enhance linearity. But complex events in field data have different curvatures, and it is difficult to fit parabolic-trace. To resolve these problems, we present an adaptive linear TFPF (AL-TFPF) in this paper. In this novel method, the linearity of the effective signals is implemented by grouping instead of window or filtering trace. Based on temporal continuity and spatial correlation, grouping is able to adaptively resample. The AL-TFPF stores the similar blocks into a new matrix. In this approach, degree of improvement of linearity is related to the accuracy of block matching. Finally, we evaluate the performance of our method on both synthetic records and field data. The experimental results illustrate that our proposed method realizes the retention of useful components and attenuation of the noise simultaneously, compared with the conventional TFPF and the PT-TFPF.

Keywords

• Seismic signal
• Block matching
• Time–frequency peak filtering (TFPF)
• Random noise suppression