Data & Analytics
This article explores how AI is transforming oil and gas operations, including its real impact on methane reduction, predictive maintenance, energy efficiency, and whether it truly delivers measurable sustainability gains or just adds complexity.
AI is evolving into a practical tool that helps geoscientists and engineers work faster, evaluate more opportunities, and manage subsurface uncertainty.
Digital drilling technologies are enabling a shift toward more predictive, efficient, and sustainable operations.
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Dan Jeavons, Shell’s VP of computational science and digital innovation, discussed the findings in MIT’s recent report on digital technology’s impact on a net-zero emissions future with Aman Srivastava, TWA deputy editor in chief. -
Join us for the final installment in our four-part series focused on addressing the implementation of AI in the petroleum industry using a real case study.
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Continue our journey with Part 3 of this four-part series focused on addressing the implementation of AI in the petroleum industry using a real case study.
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Join us for Part 2 of a four-part series focused on addressing the implementation of AI in the petroleum industry using a real case study.
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The program is designed to analyze, report, and study solutions for oil and gas greenhouse gas emissions.
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Grab a pen and paper and settle in for Part 1 of a four-part series focused on addressing the implementation of AI in the petroleum industry using a real case study.
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Texas A&M is offering a course designed in collaboration with Peloton for students in the petroleum engineering program.
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SPE has established three new technical sections—the Management Technical Section, the Methane Emissions Management Technical Section, and the Data Science & Engineering Analytics Technical Section.
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Schneider Electric University has been designed to help data center professionals expand their skills by offering free guidance on the latest technology, sustainability, and energy efficiency initiatives.
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The ethics of artificial intelligence (AI) has become an important topic in the application of AI and machine learning in the past several years. This first part of a two-part series explains the evolution and importance of the ethics of AI. The second part will present its relevance and use in engineering applications.
