346 research outputs found
Propagation and attenuation of seismic Rayleigh waves along single paths in Scotland
SIGLELD:D50447/84 / BLDSC - British Library Document Supply CentreGBUnited Kingdo
Including Physics in Deep Learning -- An example from 4D seismic pressure saturation inversion
Geoscience data often have to rely on strong priors in the face of
uncertainty. Additionally, we often try to detect or model anomalous sparse
data that can appear as an outlier in machine learning models. These are
classic examples of imbalanced learning. Approaching these problems can benefit
from including prior information from physics models or transforming data to a
beneficial domain. We show an example of including physical information in the
architecture of a neural network as prior information. We go on to present
noise injection at training time to successfully transfer the network from
synthetic data to field data.Comment: 5 pages, 5 figures, workshop, extended abstract, EAGE 2019 Workshop
Programme, European Association of Geoscientists and Engineer
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