Study and application analysis of random noise adaptive morphological filter algorithm reconstruction for seismic signals

In this study, a new adaptive morphological filter is developed based on the mathematical morphology algorithm and characteristics of the subtle differences in the waveform morphology in seismic data. The algorithm improves the traditional morphological dilation and corrosion operations. In this study, we propose a multiscale adaptive operator based on the principle of morphological structural “probes” and present the corresponding mathematical proof. Simulation experiments and actual seismic data processing results show that compared with traditional morphological filters, the constructed OCCO-based multistructure adaptive morphological filter can suppress noise to the greatest extent. Moreover, it can effectively improve the SNR of the images, and offers great application prospects.