| Deep-learning seismic facies on state-of-the-art CNN architectures JS Dramsch, M Lüthje Seg technical program expanded abstracts 2018, 2036-2040, 2018 | 69 | 2018 |
| 70 years of machine learning in geoscience in review JS Dramsch Advances in geophysics 61, 1-55, 2020 | 54 | 2020 |
| 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 | 52 | 2018 |
| Complex-valued neural networks for machine learning on non-stationary physical data JS Dramsch, M Lüthje, AN Christensen Computers & Geosciences 146, 104643, 2021 | 18 | 2021 |
| Deep learning application for 4D pressure saturation inversion compared to Bayesian inversion on North Sea data JS Dramsch, G Corte, H Amini, M Lüthje, C MacBeth Second EAGE Workshop Practical Reservoir Monitoring 2019 2019 (1), 1-5, 2019 | 12 | 2019 |
| Deep neural network application for 4D seismic inversion to changes in pressure and saturation: Optimizing the use of synthetic training datasets G Côrte, J Dramsch, H Amini, C MacBeth Geophysical Prospecting 68 (7), 2164-2185, 2020 | 11 | 2020 |
| Bayesian convolutional neural networks for seismic facies classification R Feng, N Balling, D Grana, JS Dramsch, TM Hansen IEEE Transactions on Geoscience and Remote Sensing 59 (10), 8933-8940, 2021 | 8 | 2021 |
| An integrated workflow for fracture characterization in chalk reservoirs, applied to the Kraka Field TM Aabø, JS Dramsch, CL Würtzen, S Seyum, M Welch Marine and Petroleum Geology 112, 104065, 2020 | 6 | 2020 |
| Including Physics in Deep Learning--An example from 4D seismic pressure saturation inversion JS Dramsch, G Corte, H Amini, C MacBeth, M Lüthje arXiv preprint arXiv:1904.02254, 2019 | 5 | 2019 |
| Deep Unsupervised 4-D Seismic 3-D Time-Shift Estimation With Convolutional Neural Networks JS Dramsch, AN Christensen, C MacBeth, M Lüthje IEEE Transactions on Geoscience and Remote Sensing 60, 1-16, 2021 | 4 | 2021 |
| Machine Learning in 4D Seismic Data Analysis: Deep Neural Networks in Geophysics JS Dramsch Technical University of Denmark, 2019 | 3 | 2019 |
| Correlation of Fractures From Core, Borehole Images and Seismic Data in a Chalk Reservoir in the Danish North Sea TM Aabø, JS Dramsch, MJ Welch, M Lüthje 79th EAGE Conference and Exhibition 2017 2017 (1), 1-5, 2017 | 3 | 2017 |
| Gaussian mixture models for robust unsupervised scanning-electron microscopy image segmentation of north sea chalk JS Dramsch, F Amour, M Lüthje First EAGE/PESGB Workshop Machine Learning 2018 (1), 1-3, 2018 | 2 | 2018 |
| Information theory considerations in patch-based training of deep neural networks on seismic time-series JS Dramsch, M Lüthje First EAGE/PESGB Workshop Machine Learning 2018 (1), 1-3, 2018 | 2 | 2018 |
| Keynote 5: Informing neural networks with fluid flow consistent property correlations: A 4D seismic inversion application G Corte, J Dramsch, H Amini, C MacBeth EAGE GeoTech 2021 Third EAGE Workshop on Practical Reservoir Monitoring 2021 …, 2021 | | 2021 |
| Deep Neural Network Application for 4D Seismic Inversion to Pressure and Saturation: Enhancing Training Data Sets G Corte, J Dramsch, C MacBeth, H Amini EAGE 2020 Annual Conference & Exhibition Online 2020 (1), 1-5, 2020 | | 2020 |
| Machine Learning in Geoscience Applications of Deep Neural Networks in 4D Seismic Data Analysis JS Dramsch Department of Physics, Technical University of Denmark, 2020 | | 2020 |
| Machine Learning in Geoscience JS Dramsch parameters 1, 1ˆγik, 2019 | | 2019 |
| Fracture Characterization and Modelling in the Kraka Field TM Aabø, MJ Welch, JS Dramsch, M Lüthje, S Seyum, F Amour, ... Danish Hydrocarbon Research and Technology Centre Technology Conference 2017, 2017 | | 2017 |
| Pre-stack Data Enhancement for Subsalt Imaging JS Dramsch University of Hamburg, 2015 | | 2015 |
Mikael LuthjeVerified email at dtu.dk
