Technical Topics

Researchers at Colorado School of Mines explore an internally deployed fiber-optic distributed acoustic sensing (DAS) method for continuous gas-pipeline monitoring, demonstrating its potential to improve leak detection, enable early intervention, and enhance overall pipeline-integrity management compared to conventional inspection techniques.

Part 2 of this two-part series focuses on the disciplines of drilling engineering and production engineering.

In the real world, where data is messy and workflows are rarely linear, automation often fails. That's where agentic AI comes in.

Mircea Calarasu, SPE, takes us offshore to share lessons from a scale squeeze campaign in the North Sea.

This article outlines observations regarding P&A design and analyzes what can be done better to strengthen safety, reliability, and sustainability.

For upstream operations, blockchain can help in delivering trusted and secure data, faster transactions, and increased collaboration across complex data chains.

AI is beginning to transform well management by helping engineers predict electrical submersible pump failures before they happen, optimize drawdown more efficiently, and generate reliable forecasts even when data is scarce or noisy.

The oil and gas industry's shift to smart fields—driven by automation, AI, and real-time data—requires petroleum engineers to master digital technologies alongside traditional skills.

This article explores how early-career engineers can build the competencies needed to support sustainability in oil and gas operations, not just for efficiency but also for climate resilience.

Part 1 of this series focuses on the disciplines of geology and geophysics, petrophysics, and reservoir engineering using real-world field examples from Malaysia and the author's experiences in training undergraduate students in Malaysian universities.