Data & Analytics

Backed by a $3.5 million US Department of Energy grant, Texas A&M researchers are developing an AI-enabled drilling system that can identify critical minerals in real time, reducing exploration time and costs for rare earth element deposits.
Operational drift in oil and gas starts with small, undocumented deviations that compound over time, making real-time visibility, digital workflows, and frontline execution data critical for preventing safety incidents, compliance failures, and costly operational disruptions.
Discover how AI and machine learning are transforming oil and gas field development by reducing subsurface uncertainty, optimizing development decisions, and maximizing long-term reservoir value from concept selection through production.
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