AI/machine learning
Known as Arena, the collaboration aims to improve decision-making across increasingly complex reservoirs and growing volumes of subsurface data.
Robotic and autonomous systems are transforming energy operations, but their full value emerges only when paired with data science, engineering analytics, and AI/ML to turn data into decisions. The transition of the SPE Robotic & Autonomous Systems Technical Section into the SPE Data Science & Engineering Analytics Technical Section helps bridge this critical technolo…
A credible custody-transfer record depends on far more than the accuracy of a single meter. It is the product of an integrated measurement chain. While meter performance supports measurement-system integrity, commercial confidence also depends on traceability, governance, and authorization.
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The November issues of SPE’s peer-reviewed journals SPE Reservoir Evaluation & Engineering and SPE Production & Operations include papers addressing data analytics and machine learning. -
Microsoft announced that it will open an AI Center of Excellence for Energy in the United Arab Emirates—a global first for the company—to empower organizations in the industry in accelerating digital transformation and equipping their workforce with AI skills.
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Neural networks that borrow strategies from biology are making profound leaps in their abilities. Is ignoring a goal the best way to make truly intelligent machines?
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Just because they both deal with data does not mean they are the same.
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Sensors, robots, and artificial intelligence have made their way into a number of areas within the industry, including pipeline inspections. Shell has begun to examine the innovative technologies that could shift the inspection paradigm.
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Disruption from artificial intelligence (AI) is here, but many company leaders aren’t sure what to expect from AI or how it fits into their business model. Yet, with change coming at breakneck speed, the time to identify your company’s AI strategy is now.
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When Google claimed quantum supremacy, IBM challenged it. Nonetheless, the development is really important for the future of artificial intelligence.
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Deep learning is good at finding patterns in reams of data but can't explain how they're connected. Turing Award winner Yoshua Bengio wants to change that.
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The sixth annual Deep Learning Summit in London saw industry leaders, academics, researchers, and innovative startups present the latest technological advancements and industry application methods in the field of deep learning.
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The controller from Olis will be distributed and supported by iCsys and is expected to increase efficiency and decease costs.
