| The potential of self-supervised networks for random noise suppression in seismic data SL Claire Birnie, Matteo Ravasi, Tariq Alkhalifah arXiv, 2021 | 56* | 2021 |
| Data-driven microseismic event localization: An application to the Oklahoma Arkoma basin hydraulic fracturing data H Wang, T Alkhalifah, U bin Waheed, C Birnie IEEE Transactions on Geoscience and Remote Sensing 60, 1-12, 2021 | 32 | 2021 |
| Analysis and models of pre-injection surface seismic array noise recorded at the Aquistore carbon storage site C Birnie, K Chambers, D Angus, AL Stork Geophysical Journal International 206 (2), 1246-1260, 2016 | 29 | 2016 |
| Is CO2 injection at Aquistore aseismic? A combined seismological and geomechanical study of early injection operations AL Stork, CG Nixon, CD Hawkes, C Birnie, DJ White, DR Schmitt, ... International Journal of Greenhouse Gas Control 75, 107-124, 2018 | 27 | 2018 |
| Machine learning in microseismic monitoring D Anikiev, C Birnie, U bin Waheed, T Alkhalifah, C Gu, DJ Verschuur, ... Earth-Science Reviews 239, 104371, 2023 | 26 | 2023 |
| A joint inversion-segmentation approach to assisted seismic interpretation CB Matteo Ravasi Geophysical Journal International 228 (2), 893-912, 2021 | 24* | 2021 |
| Self-supervised learning for random noise suppression in seismic data C Birnie, M Ravasi, T Alkhalifah First International Meeting for Applied Geoscience & Energy, 2869-2873, 2021 | 18 | 2021 |
| Transfer learning for self-supervised, blind-spot seismic denoising C Birnie, T Alkhalifah Frontiers in Earth Science 10, 2022 | 17 | 2022 |
| Coherent noise suppression via a self-supervised deep learning scheme S Liu, C Birnie, T Alkhalifah 83rd EAGE Annual Conference & Exhibition 2022 (1), 1-5, 2022 | 15 | 2022 |
| Coherent noise suppression via a self-supervised blind-trace deep learning scheme S Liu, C Birnie, T Alkhalifah arXiv preprint arXiv:2206.00301, 2022 | 15 | 2022 |
| Bidirectional recurrent neural networks for seismic event detection C Birnie, F Hansteen Geophysics 87 (3), KS97-KS111, 2022 | 15 | 2022 |
| Leveraging domain adaptation for efficient seismic denoising C Birnie, T Alkhalifah Energy in Data Conference, Austin, Texas, 20–23 February 2022, 11-15, 2022 | 11 | 2022 |
| On the importance of benchmarking algorithms under realistic noise conditions C Birnie, K Chambers, D Angus, AL Stork Geophysical Journal International 221 (1), 504-520, 2020 | 11 | 2020 |
| Improving the generalization of deep neural networks in seismic resolution enhancement H Zhang, T Alkhalifah, Y Liu, C Birnie, X Di IEEE Geoscience and Remote Sensing Letters 20, 1-5, 2022 | 9 | 2022 |
| An introduction to distributed training of deep neural networks for segmentation tasks with large seismic data sets C Birnie, H Jarraya, F Hansteen Geophysics 86 (6), KS151-KS160, 2021 | 9 | 2021 |
| A real-time fiber optical system for wellbore monitoring: A Johan Sverdrup case study MG Schuberth, HS Bakka, CE Birnie, S Dümmong, KE Haavik, Q Li, ... SPE Offshore Europe Conference and Exhibition, D011S001R001, 2021 | 9 | 2021 |
| Improving the quality and efficiency of operational planning and risk management with ml and nlp CE Birnie, J Sampson, E Sjaastad, B Johansen, LE Obrestad, R Larsen, ... SPE Offshore Europe Conference and Exhibition, D021S009R002, 2019 | 9 | 2019 |
| Seismic arrival enhancement through the use of noise whitening C Birnie, K Chambers, D Angus Physics of the Earth and Planetary Interiors 262, 80-89, 2017 | 9 | 2017 |
| A hybrid approach to seismic deblending: when physics meets self-supervision N Luiken, M Ravasi, CE Birnie arXiv preprint arXiv:2205.15395, 2022 | 7 | 2022 |
| Integrating self-supervised denoising in inversion-based seismic deblending N Luiken, M Ravasi, C Birnie Geophysics 89 (1), WA39-WA51, 2024 | 6 | 2024 |
Matteo RavasiKing Abdullah University of Science & TechnologyEmail verificata su kaust.edu.sa
