In recent years, spatiotemporal time-frequency peak filtering (ST-TFPF) has been proposed and successfully applied to seismic random noise suppression. It improves the shortcomings of conventional TFPF and processes seismic data along radial or quadratic traces in spatiotemporal domain. The matching degree of filtering trace and reflection events directly influence the denoising result of ST-TFPF.

Therefore, filtering trace selection has vital significance and plays an important role in ST-TFPF.

Nevertheless, in its existing models, there is hardly any effective selection method. The trace parameters were either fixed or selected by some immature algorithms, which consequently produce inaccurate or error filtering traces. Thus, this paper presents a novel filtering trace selection approach using Hough transform (HT), which designs filtering traces according to the distribution morphology of seismic events. The experimental results prove its strong accuracy and applicability in the aspect of filtering trace selection.


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