A semi-supervised recurrent-convolutional network with a seismic forward-model loss inverts elastic impedance on Marmousi 2 with 98% average correlation using only 10 labeled well logs.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.geo-ph 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Semi-supervised Sequence Modeling for Elastic Impedance Inversion
A semi-supervised recurrent-convolutional network with a seismic forward-model loss inverts elastic impedance on Marmousi 2 with 98% average correlation using only 10 labeled well logs.