Last week we proudly announced the release of four stunning, pre-trained models from Lundin GeoLab in OpendTect's Machine Learning solution. In last week's blog post, we showed an...
Last week we proudly announced the release of four stunning, pre-trained models from Lundin GeoLab in OpendTect's Machine Learning solution. In last week's blog post , we showed an example of one of these models: SimpleHmult, a 3D Unet model that attenuates horizontal multiples.
Today, we present Desmile. Like SimpleHmult, Desmile is a 3D Unet. Its purpose is to remove steeply dipping events such as migration smiles from post-stack 3D seismic volumes. The model was trained on synthetic examples with and without migration smile artefacts. The shape of the training examples was 128x128x128 samples. The slider shows a seismic section before and after application of Desmile (courtesy Lundin GeoLab).
For more information or to request a Machine Learning demo license, please email info@dgbes.com .
The next post in this series of posts is available.
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