In this AWS-sponsored webinar, led by Nick Isernia, head of strategic business development, ThinkOnward, and Anna Dubovik, head of subsurface, wAIw we will explore AI-driven subsurface energy solutions using a crowdsourcing model. Emphasized is the critical role of well-organized, high-quality data in enhancing AI precision.
One cannot overstate the role of AI and Large Language Models (LLMs) in transforming the energy industry, as emphasized by ThinkOnward & wAIw. However, for AI to be truly effective, all data must be fully available.
- Structured Data – Needs to be ingested, quality-controlled, enriched with metadata, correlated, and tracked to ensure proper ownership and lineage.
- Geo-structures – Interpretation structures (geometries) must be fully understood by a 6D geometry engine and correlated with the original data for accurate analysis.
- Unstructured Data – Historical documents must be accessible, segmented, and decomposed, with intelligent extraction applied to domain-specific content such as images and tables.
This structured approach ensures that AI and LLMs can provide meaningful insights while maintaining accuracy and reliability in data-driven decision-making. Watch this webinar to learn more today.