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20172025
most citedGraph Neural Networks with convolutional ARMA filters

439 citations

Showing physics.geo-phShow all

10 papers · 1 filter

physics.geo-ph2025★ 21 cited

Benchmarking CO Storage Simulations: Results from the 11th Society of Petroleum Engineers Comparative Solution Project

Jan M. Nordbotten, Martin A. Fernø, Bernd Flemisch +40

The 11th Society of Petroleum Engineers Comparative Solution Project (shortened SPE11 herein) benchmarked simulation tools for geological carbon dioxide (CO) storage. A total o…

physics.geo-ph2022★ 4 cited

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…

physics.geo-ph2022★ 13 cited

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…

physics.geo-ph2022★ 8 cited

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…

physics.geo-ph2022★ 17 cited

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…

physics.geo-ph2022★ 17 cited

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…

physics.geo-ph2022★ 1 cited

Numerical studies of long-term wettability alteration effects in CO storage applications

David Landa-Marbán, Kundan Kumar, Sarah Eileen Gasda +2

The wettability of the rock surface in porous media has an effect on the constitutive saturation functions that govern capillary pressure and relative permeability. The term wettab…

physics.geo-ph2021★ 29 cited

Field-scale impacts of long-term wettability alteration in geological CO storage

Abay Kassa, Sarah Eileen Gasda, David Landa-Marbán +2

Constitutive functions that govern macroscale capillary pressure and relative permeability are central in constraining both storage efficiency and sealing properties of CO stor…

physics.geo-ph2020★ 74 cited

Practical approaches to study microbially induced calcite precipitation at the field scale

David Landa-Marbán, Svenn Tveit, Kundan Kumar +1

Microbially induced calcite precipitation (MICP) is a new and sustainable technology which utilizes biochemical processes to create barriers by calcium carbonate cementation; there…

physics.geo-ph2020★ 2 cited

Modeling of relative permeabilities including dynamic wettability transition zones

Abay M. Kassa, Sarah E. Gasda, K. Kumar +1

Wettability is a pore-scale property that impacts the relative movement and distribution of fluids in a porous medium. There are reservoir fluids that provoke the surface within po…