1 citations · 1 across the 2 of their papers we have counts for
3 papers
physics.geo-ph2021
An introduction to distributed training of deep neural networks for segmentation tasks with large seismic datasets
Claire Birnie, Haithem Jarraya, Fredrik Hansteen
Deep learning applications are drastically progressing in seismic processing and interpretation tasks. However, the majority of approaches subsample data volumes and restrict model…
physics.geo-ph2020★ 1 cited
Bidirectional recurrent neural networks for seismic event detection
Claire Birnie, Fredrik Hansteen
Real time, accurate passive seismic event detection is a critical safety measure across a range of monitoring applications from reservoir stability to carbon storage to volcanic tr…
physics.geo-ph2019
Probabilistic Neural Network Tomography across Grane field (North Sea) from Surface Wave Dispersion Data
Stephanie Earp, Andrew Curtis, Xin Zhang +1
Surface wave tomography uses measured dispersion properties of surface waves to infer the spatial distribution of subsurface properties such as shear-wave velocities. These propert…