Simultaneous Coherent and Random Noise Attenuation by Morphological Filtering With Dual-Directional Structuring Element

Seismic data are highly corrupted by noise or unwanted energies arising from different kinds of sources. In general, seismic noise can be divided into two categories, namely, coherent noise and random noise, and is treated with essentially different methods. Traditional methods often utilize the differences in frequency, wavenumber, or amplitude to separate signal and noise. However, the application of traditional methods is limited if the above-mentioned differences are too small to distinguish. For this reason, we have proposed a novel morphology-based technique to simultaneously attenuate random noise and coherent noise, i.e., to extract the useful signal. In this technique, we first flatten the signal by normal move out correction or other alternative approaches. For the extraction of the flatten reflections, we propose dual-directional mathematical morphological filtering, which can detect morphological information of the seismic waveforms from two orthogonal directions and then separate signal and other unwanted energy utilizing their difference in morphological scales. Application of the proposed technique on synthetic and field data examples demonstrates a successful performance.