Next in Energy

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.

As upstream operators move beyond isolated experiments, the hardest part of the AI journey is not building a model, it is making it stick.

Rodriguez reflects on engineering growth, systems thinking, and how strong technical foundations remain valuable across evolving industries.

How 7 decades of AI research, including the emergence of agentic AI, are reshaping oil, gas, renewables, and the grid.

The global energy transition is accelerating, but geopolitical tensions, infrastructure constraints, and behavioral barriers are increasingly shaping its pace, priorities, and long-term impact.

Methane abatement is emerging as a critical strategy for decarbonizing oil and gas operations, enhancing energy security, and creating commercial value by capturing emissions, meeting growing regulatory requirements, and supplying certified low-emissions natural gas to global markets.

A data-driven look at fuel savings, battery degradation, and net CO2 impact over a 10-year ownership period.

Machine learning is transforming equipment reliability by enabling predictive maintenance, improving safety, and reducing costly downtime across drilling, production, pipelines, and CCUS operations.

This article explores how AI is transforming oil and gas operations, including its real impact on methane reduction, predictive maintenance, energy efficiency, and whether it truly delivers measurable sustainability gains or just adds complexity.

AI is evolving into a practical tool that helps geoscientists and engineers work faster, evaluate more opportunities, and manage subsurface uncertainty.