Honorable Mentions (Interpretation)
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The SEG recognizes those authors whose papers received an Honorable Mention in the search for Best Paper in Interpretation.
By clicking on the title of the article, you will be taken to a landing page to choose either the SEG Library or GeoScienceWorld to view the abstract or the full article. The abstract is available after choosing a platform, regardless of member status. Clicking on an author's name will open the biography page of that author, if it exists (blue). Names in red indicate biography pages that have not been created in the Wiki.
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Honorable Mention Recipients
2024
- Uncertainty assessment in unsupervised machine-learning methods for deepwater channel seismic facies using outcrop-derived 3D models and synthetic seismic data, Karelia La Marca, Heather Bedle, Lisa Stright, and Kurt Marfurt
- Modeling mobile shales under contraction: Critical analyses of new analog simulations of shale tectonics and comparison with salt-bearing systems, Tim P. Dooley, Juan I. Soto, Jacqueline E. Reber, Michael R. Hudec, Frank J. Peel, and Gillian M. Apps
2023
- Imaging distributed acoustic sensing-to-geophone conversion data: A field application to CO2 sequestration data, Yong Ma, Lei Fu, and Weichang Li
- Visualizing subtle structural and stratigraphic features on 3D seismic-reflection data: A case study from offshore Libya, Nabil Khalifa and Stefan Back
- Stochastic velocity modeling for assessment of imaging uncertainty during seismic migration: Application to salt bodies, Nicolas Clausolles, Pauline Collon, Modeste Irakarama, and Guillaume Caumon
- Anomalous elastic properties of mudrocks bounding reservoirs with high concentrations of naturally occurring CO2, Mark Sams and Thivyaadarshini Jayasangar
2022
- Quantifying the sensitivity of seismic facies classification to seismic attribute selection: An explainable machine-learning study, David Lubo-Robles, Deepak Devegowda, Vikram Jayaram, Heather Bedle, Kurt J. Marfurt, and Matthew J. Pranter
- Exploring factors affecting the performance of deep learning in seismic fault attribute computation, Bo Zhang, Yitao Pu, Zhaohui Xu, Naihao Liu, Shizhen Li, and Fangyu Li
- Generating a labeled data set to train machine learning algorithms for lithologic classification of drill cuttings, Daniela Becerra, Rafael Pires de Lima, Henry Galvis-Portilla, and Christopher R. Clarkson