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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This study compares seven imputation techniques for predicting missing core-measured horizontal and vertical permeability and porosity data in two wells drilled in the North Rumaila oil field in southern Iraq. -
This paper describes an approach that combines rock typing and machine-learning neural-network techniques to predict the permeability of heterogeneous carbonate formations accurately.
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This study describes the performance of machine-learning models generated by the self-organizing-map technique to predict electrical rock properties in the Saman field in northern Colombia.
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This paper presents an integrated view of three key areas of knowledge that typically are addressed individually—cybersecurity, process safety, and human factors—from the perspective of cybersecurity.
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Implemented for the first time offshore, the technology uses artificial intelligence to operate wells autonomously.
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The planned long-term partnership aims to digitally transform Aker BP’s subsurface workflows in an effort to lower costs, shorten planning cycles, and increase production.
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BMT and Ocius plan to deploy 1,000 autonomous vessels to collect data as “satellites of the sea.”
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It’s hard to create corporate or master data strategies when every user group you talk to has a different idea of what “good” should look like from their perspective.
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Geo Oceans has achieved class sign off for the world’s first entirely robotic FPSO cargo oil tank special survey.
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This paper outlines how one company uses digital technologies to manage HSE risks in project delivery, developing an artificial intelligence (AI) predictive model to predict HSE risks and incidents based on historical incident data.
