11 citations · 11 across the 1 of their papers we have counts for
2 papers
physics.geo-ph2023
DAS-N2N: Machine learning Distributed Acoustic Sensing (DAS) signal denoising without clean data
Sacha Lapins, Antony Butcher, J. -Michael Kendall +5
This article presents a weakly supervised machine learning method, which we call DAS-N2N, for suppressing strong random noise in distributed acoustic sensing (DAS) recordings. DAS-…
physics.geo-ph2023★ 11 cited
The FluidFlower International Benchmark Study: Process, Modeling Results, and Comparison to Experimental Data
Bernd Flemisch, Jan M. Nordbotten, Martin Fernø +30
Successful deployment of geological carbon storage (GCS) requires an extensive use of reservoir simulators for screening, ranking and optimization of storage sites. However, the ti…