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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Four CEOs describe what goes into turning a world of data into a data-driven world. -
The authors write that even simple deep-learning architectures can identify a leak using pressure data.
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We need to analyze the carbon intensity of reserves, the potential emissions that are in front of us, not just the carbon intensity of current operations. An engineering solution associated with production forecasts over time offers a framework for thinking through the carbon-emissions issue.
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The authors demonstrate how artificial intelligence and machine learning can help build a purely data-driven reservoir simulation model that successfully history matches dynamic variables for wells in a complex offshore field and that can be used for production forecasting.
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The recent cyberattack on Colonial Pipeline’s IT system has thrust the issue of oil and gas industry cybersecurity into the spotlight, which, according to specialists in the field, is where it should always be.
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One of the major characteristics of petroleum data analytics is its incorporation of explainable artificial intelligence (XAI). Predictive models of petroleum data analytics are not represented through unexplainable black-box behavior. Predictive models of petroleum data analytics are reasonably explainable. This second part of a two-part series presents the use of XA…
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The latest iteration of the Top500 list puts the Perlmutter supercomputer at Lawrence Berkeley Laboratory in the spotlight.
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The new data-management platform is designed to increase access to energy data.
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The US represents the largest regional market, while China is expected to emerge as the fastest-growing market.
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One of the major characteristics of petroleum data analytics is its incorporation of explainable artificial intelligence (XAI). Predictive models of petroleum data analytics are not represented through unexplainable black-box behavior. Predictive models of petroleum data analytics are reasonably explainable. This first part of a two-part series presents the history of…
