Improving the quality control of seismic data through active learning. (arXiv:2201.06616v2 [stat.ML] UPDATED)

In image denoising problems, the increasing density of available images makes
an exhaustive visual inspection impossible and therefore automated methods
based on machine-learning must be deployed for this purpose. This is
particulary the case in seismic signal processing. Engineers/geophysicists have
to deal with millions of seismic time series. Finding the sub-surface
properties useful for the oil industry may take up to a year and is very costly
in terms of computing/human resources. In particular, the data must go through
different …

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