Data & Analytics
Autonomous drilling through managed pressure drilling (MPD) at the Atlantis field has given the operator confidence to scale the method.
The cloud platform provider said the initiative is designed to help energy companies manage and analyze large-scale operational data.
Major increases in hydrocarbon production require both incremental and revolutionary technologies, industry leaders said during the SPE Hydraulic Fracturing Technology Conference.
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Digital twins are powerful combinations of models and data that “age” throughout the lifecycle of an asset as they gather and integrate data from the field. This technology is a quantum leap from earlier efforts at modeling complex systems. -
This article outlines 10 top trending technologies for 2019, a list that covers diverse topics such as security, the Internet of things, reinforcement learning, energy sustainability, and smart cities.
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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.
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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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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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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.
