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Publications

2021

  • Jesper Sören Dramsch, Mikael Lüthje, and Anders Nymark Christensen. Complex-valued neural networks for machine learning on non-stationary physical data. Computers & Geosciences, 146:104643, 2021.
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  • Runhai Feng, Niels Balling, Dario Grana, Jesper Soren Dramsch, and Thomas Mejer Hansen. Bayesian convolutional neural networks for seismic facies classification. IEEE Transactions on Geoscience and Remote Sensing, pages 1–8, 2021. URL: https://doi.org/10.1109/tgrs.2020.3049012, doi:10.1109/tgrs.2020.3049012.
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2020

  • G Corte, Jesper Sören Dramsch, C MacBeth, and H Amini. Deep neural network application for 4d seismic inversion to pressure and saturation: enhancing training data sets. In 82nd EAGE Annual Conference & Exhibition, volume 2020, 1–5. European Association of Geoscientists & Engineers, 2020.
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  • Jesper Sören Dramsch. 70 years of machine learning in geoscience in review. In Machine Learning in Geosciences, pages 1–55. Elsevier, 2020. URL: https://doi.org/10.1016/bs.agph.2020.08.002, doi:10.1016/bs.agph.2020.08.002.
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  • Gustavo Côrte, Jesper Sören Dramsch, Hamed Amini, and Colin MacBeth. Deep neural network application for 4d seismic inversion to changes in pressure and saturation: optimizing the use of synthetic training datasets. Geophysical Prospecting, 68(7):2164–2185, June 2020. URL: https://doi.org/10.1111/1365-2478.12982, doi:10.1111/1365-2478.12982.
    [abstract▼] [BibTeX▼]
  • Tala Maria Aabø, Jesper Sören Dramsch, Camilla Louise Würtzen, Solomon Seyum, Frédéric Amour, Michael Welch, and Mikael Lüthje. An integrated workflow for fracture characterization in chalk reservoirs, applied to the kraka field. Marine and Petroleum Geology, 2020. URL: http://www.sciencedirect.com/science/article/pii/S026481721930501X, doi:https://doi.org/10.1016/j.marpetgeo.2019.104065.
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  • Jesper Sören Dramsch. Machine learning geoscience: applications of deep neural networks in 4d seismic data analysis. PhD Thesis, 2020.
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2019

  • Jesper Sören Dramsch, Anders Nymark Christensen, Colin MacBeth, and Mikael Lüthje. Deep unsupervised 4d seismic 3d time-shift estimation with convolutional neural networks. IEEE Transactions in Geoscience and Remote Sensing, 2019.
    [abstract▼] [full text] [BibTeX▼]
  • Jesper Sören Dramsch, Gustavo Corte, Hamed Amini, Mikael Lüthje, and Colin MacBeth. Deep learning application for 4d pressure saturation inversion compared to bayesian inversion on north sea data. In Second EAGE Workshop Practical Reservoir Monitoring 2019. EAGE Publications BV, 2019. doi:10.3997/2214-4609.201900028.
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  • Jesper Sören Dramsch, Gustavo Corte, Hamed Amini, Colin MacBeth, and Mikael Lüthje. Including physics in deep learning – an example from 4d seismic pressure saturation inversion. In 81st EAGE Conference and Exhibition 2019 Workshop Programme. EAGE Publications BV, 2019. URL: https://doi.org/10.3997/2214-4609.201901967, doi:10.3997/2214-4609.201901967.
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2018

  • Jesper Sören Dramsch and Mikael Lüthje. Deep-learning seismic facies on state-of-the-art cnn architectures. In SEG Technical Program Expanded Abstracts 2018, 2036–2040. Society of Exploration Geophysicists, 2018. URL: https://doi.org/10.1190/segam2018-2996783.1, doi:10.1190/segam2018-2996783.1.
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  • Lukas Mosser, Wouter Kimman, Jesper Sören Dramsch, Steve Purves, A De la Fuente Briceño, and Graham Ganssle. Rapid seismic domain transfer: seismic velocity inversion and modeling using deep generative neural networks. In 80th EAGE Conference and Exhibition 2018. EAGE Publications BV, 6 2018. URL: https://doi.org/10.3997/2214-4609.201800734, doi:10.3997/2214-4609.201800734.
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  • Jesper Sören Dramsch and Mikael Lüthje. Information theory considerations in patch-based training of deep neural networks on seismic time-series. In First EAGE/PESGB Workshop Machine Learning. EAGE Publications BV, 2018. URL: https://doi.org/10.3997/2214-4609.201803020, doi:10.3997/2214-4609.201803020.
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  • Jesper Sören Dramsch, Frédéric Amour, and Mikael Lüthje. Gaussian mixture models for robust unsupervised scanning-electron microscopy image segmentation of north sea chalk. In First EAGE/PESGB Workshop Machine Learning. EAGE Publications BV, 2018. URL: https://doi.org/10.3997/2214-4609.201803014, doi:10.3997/2214-4609.201803014.
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2017

  • Tala Maria Aabø, Jesper Sören Dramsch, Michael Welch, and Mikael Lüthje. Correlation of fractures from core, borehole images and seismic data in a chalk reservoir in the danish north sea. In 79th EAGE Conference and Exhibition 2017. EAGE Publications BV, 6 2017. URL: https://doi.org/10.3997/2214-4609.201701283, doi:10.3997/2214-4609.201701283.
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2016

  • Jesper Sören Dramsch. Seismic subsalt imaging with prestack data enhancement methods. Master Thesis, November 2016. URL: https://doi.org/10.31237/osf.io/aec7p, doi:10.31237/osf.io/aec7p.
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2011

  • Jesper Sören Dramsch and DJ Gajewski. Trace interpolation with partial crs stacks. In 73rd EAGE Conference and Exhibition incorporating SPE EUROPEC 2011, cp–238. European Association of Geoscientists & Engineers, 2011.
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  • Jesper S Dramsch. Trace interpolation with partial crs-stacks. 2011. URL: thesiscommons.org/mvxuh, doi:10.31237/osf.io/mvxuh.
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