Jesper Sören Dramsch
Title
Cited by
Cited by
Year
Deep-learning seismic facies on state-of-the-art CNN architectures
JS Dramsch, M Lüthje
Seg technical program expanded abstracts 2018, 2036-2040, 2018
522018
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
452018
70 years of machine learning in geoscience in review
JS Dramsch
Advances in Geophysics 61, 1, 2020
242020
Complex-valued neural networks for machine learning on non-stationary physical data
JS Dramsch, M Lüthje, AN Christensen
Computers & Geosciences 146, 104643, 2021
132021
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
112019
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
62020
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
52020
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
52019
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, 2021
32021
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, 2021
22021
Machine Learning in 4D Seismic Data Analysis: Deep Neural Networks in Geophysics
JS Dramsch
Technical University of Denmark, 2019
22019
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
22018
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
22017
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
12018
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
82nd EAGE Annual Conference & Exhibition 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
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Articles 1–20