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Welcome presentation
20 Jun, 2021
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Opening notes
20 Jun, 2021
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Session I : “The potential of Machine learning”
20 Jun, 2021
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Talk 1.1 - Advancing Reservoir Simulation with Machine Learning
20 Jun, 2021
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Talk 1.2 - What Can Algorithms Learn from Data & Knowledge to Make Better Reservoir Predictions?
20 Jun, 2021
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Talk 1.3 - NVIDIA building blocks for ML based geoscience
20 Jun, 2021
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Talk 1.4 - Applicability of ML in Capturing the First Principles of Fluid Flow in Porous Media
20 Jun, 2021
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Session I Q&A
20 Jun, 2021
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Session II : “Optimized workflows and the role of HPC”
20 Jun, 2021
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Talk 2.1 - Automating subsurface property modeling through semi-supervised learning
20 Jun, 2021
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Talk 2.2 - NVIDIA platform for AI and HPC, and applications to geosciences
20 Jun, 2021
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Talk 2.3 - Open Seismic: A Toolbox for Seismic Interpretation
20 Jun, 2021
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Talk 2.4 - KAUST Supercomputing Services for HPC and AI
20 Jun, 2021
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Session II Q&A
20 Jun, 2021
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End of Day 1
20 Jun, 2021
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Session III Panel discussion : "The future of ML in Geosciences and Engineering"
21 Jun, 2021
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Session IV : Lightning Talks "Flow and rocks"
21 Jun, 2021
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Talk 4.1 - Physics-informed neural network for high-frequency wavefield representation
21 Jun, 2021
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Talk 4.2 - ExaGeoStat: Exploiting Data Sparsity in Earth System Models
21 Jun, 2021
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Talk 4.3 - Bayesian Deep DCA: A New Approach for Well Oil Production Modeling and Forecasting
21 Jun, 2021
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