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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Saipem is taking the lead in advancing the capabilities of FlatFish, an autonomous underwater vehicle being developed by Shell for commercial application by 2020. -
Drones will be just one of the tools that the service company uses in its drive toward net-zero carbon emissions.
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Cataloging data can be a minefield, and not knowing exactly what you can do with the data you have could lead to disaster. What steps should companies take to handle legacy data, and what importance does the tracking of entitlements play in data management systems?
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A survey of oil and gas decision-makers by Ernst & Young sheds light on how companies are formulating their digital strategies.
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Royal Dutch Shell is heavily investing in research and development of artificial intelligence, which it hopes will provide solutions to some of its most pressing challenges.
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Blockchain technology may have gotten its start by keeping cryptocurrency traders honest, but its usefulness is expanding. And the oil and gas industry is taking advantage.
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To test your knowledge, answer these 10 questions from Jim Crompton, who teaches petroleum data analytics at the Colorado School of Mines.
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Digital solutions that have made their mark in other industries may foster stronger collaborative environments in various sectors within energy, including equipment maintenance and data management.
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Oil companies are talking big about using data and analytics, but the experts in the field are not sure what their role will be. Birol Dindoruk, SPE's technical director for management and information, talks about ensuring that they have a say.
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A new geostatistics modeling methodology that connects geostatistics and machine-learning methodologies, uses nonlinear topological mapping to reduce the original high-dimensional data space, and uses unsupervised-learning algorithms to bypass problems with supervised-learning algorithms.
