1 citations · 2 across the 4 of their papers we have counts for
4 papers
Does shallow geological knowledge help neural-networks to predict deep units?
Bas Peters, Eldad Haber, Justin Granek
Geological interpretation of seismic images is a visual task that can be automated by training neural networks. While neural networks have shown to be effective at various interpre…
Neural-networks for geophysicists and their application to seismic data interpretation
Bas Peters, Eldad Haber, Justin Granek
Neural-networks have seen a surge of interest for the interpretation of seismic images during the last few years. Network-based learning methods can provide fast and accurate autom…
Automatic classification of geologic units in seismic images using partially interpreted examples
Bas Peters, Justin Granek, Eldad Haber
Geologic interpretation of large seismic stacked or migrated seismic images can be a time-consuming task for seismic interpreters. Neural network based semantic segmentation provid…
Multi-resolution neural networks for tracking seismic horizons from few training images
Bas Peters, Justin Granek, Eldad Haber
Detecting a specific horizon in seismic images is a valuable tool for geological interpretation. Because hand-picking the locations of the horizon is a time-consuming process, auto…