41 citations · 159 across the 16 of their papers we have counts for
5 papers · 1 filter
Strategic Geosteering Workflow with Uncertainty Quantification and Deep Learning: A Case Study on the Goliat Field
Muzammil Hussain Rammay, Sergey Alyaev, David Selvåg Larsen +2
The real-time interpretation of the logging-while-drilling data allows us to estimate the positions and properties of the geological layers in an anisotropic subsurface environment…
Verification of a real-time ensemble-based method for updating earth model based on GAN
Kristian Fossum, Sergey Alyaev, Jan Tveranger +1
The complexity of geomodelling workflows is a limiting factor for quantifying and updating uncertainty in real-time during drilling. We propose Generative Adversarial Networks (GAN…
Probabilistic forecasting for geosteering in fluvial successions using a generative adversarial network
Sergey Alyaev, Jan Tveranger, Kristian Fossum +1
Quantitative workflows utilizing real-time data to constrain ahead-of-bit uncertainty have the potential to improve geosteering significantly. Fast updates based on real-time data…
Probabilistic model-error assessment of deep learning proxies: an application to real-time inversion of borehole electromagnetic measurements
Muzammil Hussain Rammay, Sergey Alyaev, Ahmed H Elsheikh
The advent of fast sensing technologies allows for real-time model updates in many applications where the model parameters are uncertain. Bayesian algorithms, such as ensemble smoo…
Direct multi-modal inversion of geophysical logs using deep learning
Sergey Alyaev, Ahmed H. Elsheikh
Geosteering of wells requires fast interpretation of geophysical logs, which is a non-unique inverse problem. Current work presents a proof-of-concept approach to multi-modal proba…