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Lukas Mosser
Lukas Mosser
Aker BP
Verified email at akerbp.com - Homepage
Title
Cited by
Cited by
Year
Reconstruction of three-dimensional porous media using generative adversarial neural networks
L Mosser, O Dubrule, MJ Blunt
Physical Review E 96 (4), 043309, 2017
4702017
Stochastic seismic waveform inversion using generative adversarial networks as a geological prior
L Mosser, O Dubrule, MJ Blunt
Mathematical Geosciences 52 (1), 53-79, 2020
2222020
Stochastic reconstruction of an oolitic limestone by generative adversarial networks
L Mosser, O Dubrule, MJ Blunt
Transport in Porous Media 125 (1), 81-103, 2018
1592018
Pores for thought: generative adversarial networks for stochastic reconstruction of 3D multi-phase electrode microstructures with periodic boundaries
A Gayon-Lombardo, L Mosser, NP Brandon, SJ Cooper
npj Computational Materials 6 (1), 82, 2020
1032020
Rapid seismic domain transfer: Seismic velocity inversion and modeling using deep generative neural networks
L Mosser, W Kimman, J Dramsch, S Purves, A De la Fuente Briceño, ...
80th eage conference and exhibition 2018 2018 (1), 1-5, 2018
802018
Conditioning of generative adversarial networks for pore and reservoir scale models
L Mosser, O Dubrule, MJ Blunt
80th EAGE Conference and Exhibition 2018 2018 (1), 1-5, 2018
472018
Deepflow: history matching in the space of deep generative models
L Mosser, O Dubrule, MJ Blunt
arXiv preprint arXiv:1905.05749, 2019
252019
Determining diverter effectiveness in a fracture wellbore
MA Dawson, G Kampfer, L Mosser
US Patent 10,378,333, 2019
202019
Stochastic seismic waveform inversion using generative adversarial networks as a geological prior: Mathematical Geosciences, 52, 53–79, doi: 10.1007/s11004-019-09832-6
L Mosser, O Dubrule, MJ Blunt
Crossref Web of Science, 2020
182020
Mapping of fracture geometries in a multi-well stimulation process
MA Dawson, G Kampfer, L Mosser
US Patent 10,215,014, 2019
182019
Probabilistic seismic interpretation using Bayesian neural networks
L Mosser, R Oliveira, M Steventon
81st EAGE Conference and Exhibition 2019 2019 (1), 1-5, 2019
172019
Deep Bayesian neural networks for fault identification and uncertainty quantification
L Mosser, S Purves, EZ Naeini
First EAGE Digitalization Conference and Exhibition 2020 (1), 1-5, 2020
142020
Stochastic seismic waveform inversion using generative adversarial networks as a geological prior: First EAGE
L Mosser, O Dubrule, M Blunt
PESGB Workshop Machine Learning 3720, 2018
122018
Well-data-based discrete fracture and matrix modelling and flow-based upscaling of multilayer carbonate reservoir horizons
C Milliotte, S Jonoud, OP Wennberg, SK Matthäi, A Jurkiw, L Mosser
112018
A comprehensive study of calibration and uncertainty quantification for Bayesian convolutional neural networks—An application to seismic data
L Mosser, E Zabihi Naeini
Geophysics 87 (4), IM157-IM176, 2022
102022
Tessellations stable under iteration. Evaluation of application as an improved stochastic discrete fracture modeling algorithm
L Mosser, SK Matthäi
International Discrete Fracture Network Engineering Conference, 163, 2014
72014
Reconstruction of Three-Dimensional Porous Media: Statistical or Deep Learning Approach?
L Mosser, TL Blévec, O Dubrule
Statistical Data Science, 125-139, 2018
62018
Deep learning-based unsupervised denoising for coherent noise attenuation in seismic data
L Mosser, B Alaei
Second EAGE Subsurface Intelligence Workshop 2022 (1), 1-5, 2022
32022
A comparison of traditional, supervised, and unsupervised machine learning-based denoising methods for post-stack seismic data
L Mosser, T Papadopoulos, A Kuha, J Herredsvela, EZ Naeini
Second EAGE Digitalization Conference and Exhibition 2022 (1), 1-5, 2022
32022
Stochastic reconstruction of periodic, three-dimensional multi-phase electrode microstructures using generative adversarial networks
A Gayon-Lombardo, L Mosser, NP Brandon, SJ Cooper
arXiv, arXiv: 2003.11632, 2020
32020
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