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Twenty-seven SPE Sections around the world have been recognized with the 2025 Regional Outstanding Section Award.

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.

Successful in other applications, self-healing coatings could be the oil industry’s ticket to fighting corrosion and extending the life of steel.

Speakers from various disciplines and professions focus on industry trends, challenges, technology applications and advances. Scheduled DL events are in-person meetings only.

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

Shell became the first international company to operate producing fields offshore Brazil and the first to navigate the country’s complex and detailed decommissioning permitting process, which involved extensive environmental assessments, regulatory approvals, and coordinated stakeholder engagement.

The service giant shares how its new technology can sense rock properties 50 ft ahead of the bit in horizontal wells.

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

This study aims to thoroughly assess the influence of various completions, fracturing stimulation, and intrinsic reservoir properties affecting the productivity of 10 major unconventional plays while uncovering insights and trends unique to each play.

This paper aims to describe the role of liquefied natural gas as a transitional energy source for automobile transportation in Nigeria.

This study concludes that it is relatively easy to generate enhanced hydrogen in the laboratory during injection of high-pH aqueous solution through a pack of olivine sand.

The authors of this paper present a workflow designed to achieve maximum integration between analytical and modeling activities in carbon capture and storage projects.