Abstract
Artificial intelligence (AI), specifically machine learning (ML), has emerged as a powerful tool to address many of the challenges we face as we try to illuminate the earth and make the proper prediction of its content. From fault detection, to salt boundary mapping, to image resolution enhancements, the quest to teach our computing devices how to perform these tasks accurately, as well as quantify the accuracy, has become a feasible and sought-after objective. Recent advances in ML algorithms and availability of the modules to apply such algorithms enabled geoscientists to focus on potential applications of such tools. As a result, we held the virtual workshop, Artificially Intelligent Earth Exploration Workshop: Teaching the Machine How to Characterize the Subsurface, 23–26 November 2020.
Original language | English (US) |
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Pages (from-to) | 298-301 |
Number of pages | 4 |
Journal | The Leading Edge |
Volume | 40 |
Issue number | 4 |
DOIs | |
State | Published - Apr 2021 |
Bibliographical note
KAUST Repository Item: Exported on 2021-04-05ASJC Scopus subject areas
- Geology