Data & Analytics
Working with Dell Technologies and NVIDIA, the French supermajor is targeting improved seismic processing and artificial intelligence applications.
A discussion at the inaugural executive breakfast convened by the SPE Data Science and Engineering Analytics Technical Section, held alongside CERAWeek by S&P Global and powered by Black & Veatch, tackled the challenge of value creation from artificial intelligence in the energy industry.
AI‑driven data center growth is straining US power grids and accelerating interest in enhanced geothermal systems as a scalable, low‑carbon solution.
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Many reviews of unsuccessful digital-transformation projects point to the lack of the proper organizational culture for the adoption of digital oilfield solutions. What is the right organizational culture for a data-driven enterprise? -
When the world reopens, it will be flooded with the opportunities and tools that extended-reality platforms have to offer.
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SponsoredTo optimize decision-making, minimize risk, and create value, oil and gas companies can turn to liberated, contextualized data. For exploration or drilling, liberated, contextualized data can help the upstream industry make trustworthy decisions that save time and costs. This paper explains how.
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SponsoredFor surveying, exploration, analytics, and a whole host of processes, liberated, contextualized data tailored to the environments of E&P subsurface will empower confidence, speed, reliability, agility, and most importantly, innovation. This is how Aker BP is doing it.
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As SPE members deal with challenging and uncertain times, they are reminded that there are a number of programs available to provide support and key resources. Read more to see which ones are useful to you and your career.
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“Dark data” may be a relatively unknown term for many, even though all contribute to its growing presence. It represents data that is accumulated continually by the interconnected systems used every day. A recent survey estimated that an average of 55% of accumulated data is dark and unexplored.
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An estimate says data centers, including edge sites, will soon use four times the energy all data centers used in 2018. Can it be true?
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Support vector machines are powerful for solving regression and classification problems. You should have this approach in your machine-learning arsenal, and this article provides all the mathematics you need to know. It's not as hard you might think.
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When the field emerged at the end of the 20th century, it was hoped that computers would be able to operate on their own, with human-like abilities—a capability known as generalized AI.
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As deep learning matures and moves from the hype peak to its trough of disillusionment, it is becoming clear that it is missing some fundamental components.
