Next in Energy

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.

Digital drilling technologies are enabling a shift toward more predictive, efficient, and sustainable operations.

Breakthroughs in energy, similar to those seen in AI, require coordinated progress across multiple fields and the resolution of structural bottlenecks. As a result, a successful energy transition depends on integrated advances in infrastructure, policy, technology, and investment rather than isolated efforts.

The Genesis Mission is a US Department of Energy initiative that integrates AI, national labs, and cross-sector collaboration to accelerate scientific discovery, strengthen energy innovation, and enhance national security.

This commentary by the chair of the SPE Data Science and Engineering Analytics Technical Section examines how AI is reshaping petroleum engineering careers, highlighting growing risks to entry‑level training, judgment development, and the future pipeline of subject-matter experts in high‑consequence industries.

Gas chromatography is a proven tool supporting the safe, compliant, and optimal operation of operation of carbon capture, utilization, and storage processes.

Louisiana's orphan wells may provide an opportunity for successful microbial hydrogen production as the energy industry looks toward sustainability.