NEURAL NETWORK-BASED SEISMIC RESOLUTION ENHANCEMENT TECHNOLOGY
DOI:
https://doi.org/10.15407/dopovidi2024.03.011Keywords:
machine learning model, neural network, U-net architecture, loss functionAbstract
The paper contains description of a U-net architecture-based machine learning model created for seismic resolution enhancement and noise reduction. The presentation includes a brief explanation of the choice of publicly available synthetic data for training and verification purposes. Apart from architecture blocks description, the author describes variations of the loss functions used as metrics to verify the model’s performance.
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Copyright (c) 2024 Reports of the National Academy of Sciences of Ukraine
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