Data & Analytics
2026 TWA Energy Influencer Muhammad Karimi shares how he transformed academic research into a globally deployed energy technology, offering insights on innovation, entrepreneurship, oilfield digitalization, and the energy transition.
Discover how AI leader Fatai Anifowose transformed skepticism into innovation, sharing insights on artificial intelligence in energy, leadership, continuous learning, and the skills shaping the future of the industry.
Utkarsh Sinha, 2026 TWA Energy Influencer, is driving innovation at the intersection of reservoir physics and AI, combining research, patents, and industry leadership to develop practical machine learning solutions that improve reservoir and production engineering decision-making.
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Honeypots and pen testers. If these terms are unfamiliar, you’ll want to learn their roles in the safekeeping of critical evaluation and operational data in oil and gas activities, from the reservoir to the well pad to pipelines. -
Always recorded but almost never used, the water hammer signal could offer completions engineers another set of insightful data if petroleum engineers can crack its code.
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Figuring out the right price for an active oil and gas field is tricky business in the shale sector but one producer explains how it uses data analytics to get a clearer picture.
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Permian Basin producer Callon Petroleum is attributing its data-driven approach to a routine completions practice to improved proppant placement and higher oil production.
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The oil and gas industry has a lot to gain from the adoption of big data analytics as recently highlighted examples from major service company Halliburton demonstrate.
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Through data gathering, machine learning, and the use of a supercomputer, a non-profit organization in Texas is seeking to boost oil and gas production on land owned by the states’ two largest university systems.
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A look at the universities, startups, and multinational corporations in Silicon Valley, California, which are applying data science and predictive modeling for oilfield management.
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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.
