This paper presents a smart safety monitoring system to prevent accidents in environments with moving machinery at use on various global rigs.

The Energy and AI Observatory aims to use up-to-date information on energy demand from data centers to determine how artificial intelligence is optimizing the energy sector.

The company is making available its data on ocean and weather conditions in an effort to boost transparency and innovation.

The nonprofit said the satellite likely is unrecoverable but that it will continue to analyze the data it had collected.

This research developed a clear framework for assessing and selecting fit-for-purpose software. The study focuses on the role of a data-driven approach in the decision process, with application to operational software systems in the oil and gas industry.

As carbon capture scales up worldwide, the real challenge lies deep underground—where smart reservoir management determines whether CO₂ stays put for good.

This article is the third in a Q&A series from the SPE Research and Development Technical Section focusing on emerging energy technologies. In this piece, Zikri Bayraktar, a senior machine learning engineer with SLB’s Software Technology and Innovation Center, discusses the expanding use of artificial intelligence in the upstream sector.

This article presents a results-driven case study from an ongoing collaboration between a midstream oil and gas company and Neuralix Inc.

The SPE Reservoir Technical Discipline and Advisory Committee invite their Reservoir members worldwide to participate in a new survey aimed at assessing the current state of reservoir engineering across industry and academia. Deadline is 21 July 2025.

The agreement focuses on improving operational efficiency and consistency through advanced digital tools and real-time data integration.