Data & Analytics
This paper presents a smart safety monitoring system to prevent accidents in environments with moving machinery at use on various global rigs.
The Energy and AI Observatory aims to use up-to-date information on energy demand from data centers to determine how artificial intelligence is optimizing the energy sector.
The company is making available its data on ocean and weather conditions in an effort to boost transparency and innovation.
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The collaboration expects to redefine methane detection and contribute to emission-reduction efforts across dozens of industries, including energy, agriculture, manufacturing, and transportation. -
This article presents a deep-learning approach, the long short-term memory network, for adaptive hydrocarbon production forecasting that takes historical operational and production information as input sequences to predict oil production as a function of operational plans.
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The authors of this paper describe a continuous monitoring system based on the Internet of Things (IoT) to use methane-concentration sensors permanently installed at facilities and connected to a cloud-based interpretation platform.
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The Robotic Supervision System project is expected to bring autonomous cooperation a step closer for oil and gas operators.
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Ocean services provider DeepOcean has mobilized its first autonomous inspection drone and plans to conduct offshore trials for an operator on the Norwegian continental shelf.
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While the industry is adopting the technology, one expert highlights areas where the oil and gas sector could speed up the adoption of artificial intelligence.
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SponsoredThis Q&A highlights the benefits of AI and ML to automate work flows and analyze data at a much faster rate—within minutes. These capabilities deliver a fit-for-basin approach designed specifically for US-centric work flows.
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This paper proposes a series of work flows to simplify model deployment and set up an automatic advisory system to provide insight in justifying an engineer’s day-to-day engineering decisions.
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This paper presents an artificial intelligence algorithm called dual heuristic dynamic programming that can be used to solve petroleum optimization-control problems.
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This paper describes an approach implemented by the operator to solve research and development challenges by creating in-house infrastructure of both software and hardware.
