Digital Transformation
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.
How 7 decades of AI research, including the emergence of agentic AI, are reshaping oil, gas, renewables, and the grid.
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This article offers a four-part framework for critical infrastructure organizations looking to overcome the skills gap and create a strong cybersecurity workforce. -
The oil and gas industry is facing an invasion of data analytics startups who saw a wide-open gap in the market a few years ago when talk of big data first began.
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A newcomer in the arena of oilfield market research has set an ambitiously high bar for itself: to speed up the oil and gas industry’s widely acknowledged and painfully slow rate of technology adoption.
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The use of intelligent software is on the rise in the industry and it is changing how engineers approach problems. A series of articles explores the potential benefits and limitations of this emerging area of data science.
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Researchers at Heriot-Watt University in Edinburgh, Scotland, are building replica core samples using 3D printers and installing sensors inside them as they go. Their goal is to directly monitor pore-scale flow behavior from the inside of these so-called “smart rocks.”
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PetroWiki.org is a living, growing knowledge resource for oil and gas professionals, featuring more than 2,000 pages of content. Information about a topic can be easily gathered by entering the keyword in the search box.
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Autonomous underwater vehicles (AUVs) have demonstrated their capabilities during the search for Malaysian Airlines flight 370 in the Indian Ocean.
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In an effort to foster collaboration in an area where there is currently very little, researchers at the University of Texas at Austin (UT) created a new web-based application for storing and sharing CT images of rocks.
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Pulled directly from the reservoir rock, core samples provide critical data used to determine how exploration should proceed. Until recently, core analysis remained old school, however, there is an ongoing transition to bring the process of core description into the digital age.
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Case studies from around the world prove that big rewards await companies that optimize the artificial lift systems keeping their mature fields alive. The success stories involve a mix of monitoring, automation, and performance tracking.
