Digital Oil And Gas

The oil and gas industry generates extraordinary amounts of data from millions of sensors, yet only a tiny fraction, at most  8%, is actually used to inform decisions on complex and valuable assets. Decades of building analytics and machine learning solutions have helped, but they’ve also left companies with a patchwork of siloed systems and “industrial gridlock.” The arrival of foundation models in late 2022 introduced the possibility of moving beyond one-off solutions. But generic internet-trained models are not suitable for high-risk industrial environments, where accuracy, context, and explainability are essential. The sector needs something different. Applied Computing is tackling this challenge head-on by creating a foundation model designed specifically for energy. Built to handle time-series data, diagrams, operator logs, and unstructured engineering information, their model emphasizes contextual understanding, explainability, and zero hallucinations. My guest this week, Dan Jeavons, is President of A