Data & Analytics
Shell has demonstrated drone-in-a-box operations from its Mars floating production unit, becoming the first operator in the region to secure FAA approval for self-approved offshore beyond-visual-line-of-sight flights. JPT Senior Technology Editor Jennifer Pallanich visited Shell Technology Center Houston to see the system in action.
Panelists at the SPE Subsea Well Intervention Symposium discussed where AI is delivering value today, where risks remain, and how engineers can best determine its usefulness.
As digital technologies become commonplace, industry leaders say core engineering knowledge remains essential for making informed decisions and avoiding costly mistakes.
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Joelle Pineau, a machine-learning scientist at McGill University, is leading an effort to encourage artificial-intelligence researchers to open up their code. -
The international major is calling its latest multiwell project in the Permian Basin a “beacon of innovation.” The goal is to see if combining digital technologies will lower the operating costs of its shale assets.
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As companies look to reduce the time it takes to inspect a subsea pipeline, as well as the costs involved in the operation, autonomous systems have become a more desirable option. How close are they to becoming the norm?
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Innovating internal systems at Exxon inspires executives to create a forum for the oil and gas industry.
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The report focuses on the effect of data analytics on reservoir engineering applications, more specifically the ability to characterize reservoir parameters, analyze and model reservoir behavior, and forecast performance to transform the decision-making process.
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Should that outside hotshot lead your digital transformation work or an insider who knows more about the culture and customers?
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This paper investigates the most important independent variables, including petrophysics and completion parameters, to estimate ultimate recovery with a machine-learning algorithm. A novel machine-learning model based on random forest regression is introduced to predict estimated ultimate recovery.
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As this year comes to a close, it has been defined by some big themes in oil and gas data management: innovation, collaboration, governance, stuck proofs of concept, trendy tech, and oil shaming.
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What is explainability in artificial intelligence, and how can we leverage different techniques to open the black box of AI and peek inside? This practical guide offers a review and critique of the various techniques of interpretability.
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Leaders in the AI community came together to release the 2019 AI Index report, an annual attempt to examine the biggest trends shaping the AI industry, breakthrough research, and AI’s impact to society.
