Topics

• State of AI in the geosciences 
• Advancements in workflows/processes
• Disruptive technologies available today (cloud, HPC etc.)
• AI in the seismic domain
• Advancements, applications and impacts in the reservoir characterization
• Inversion related AI updates (post/pre stack)
• Integration of physics and data-driven approaches in geoscience
• Coupling physical processes to design & refine ML solutions
• Uncertainty in AI methods used for reservoir characterization
• Methods and applications of quantifying uncertainty
• Data management for AI/ML
• Structured vs unstructured data utilization
• Data governance and information management
• Case Studies
• Uses and applications of SI 
• In the exploration phase
• In reservoir characterization 
• In real-time operations
• In static/dynamic model building
• Underground storage
• Lessons learned