Articles | Volume 16, issue 6
Ocean Sci., 16, 1367–1383, 2020
https://doi.org/10.5194/os-16-1367-2020
Ocean Sci., 16, 1367–1383, 2020
https://doi.org/10.5194/os-16-1367-2020

Research article 11 Nov 2020

Research article | 11 Nov 2020

Random noise attenuation of sparker seismic oceanography data with machine learning

Hyunggu Jun et al.

Data sets

Random Noise Attenuation of Sparker Seismic Oceanography Data with Machine Learning Jun, H., Jou, H.-T., Kim, C.-H., Lee, S. H., and Kim, H.-J. https://doi.org/10.5281/zenodo.4020335

Model code and software

Random Noise Attenuation of Sparker Seismic Oceanography Data with Machine Learning Jun, H., Jou, H.-T., Kim, C.-H., Lee, S. H., and Kim, H.-J. https://doi.org/10.5281/zenodo.4020335

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Short summary
Seismic oceanography acquires water column reflections by seismic exploration. The use of a high-frequency seismic source such as sparker can enhance the resolution of reflection image but suffers from a low signal-to-noise ratio problem. In this study, we applied a machine learning to remove the random noise in water column seismic section. We constructed appropriate training data and showed that the machine learning can successfully remove the random noise in the water column seismic section.