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 paper presents an approach using artificial neural networks to predict the discharge pressure of electrical submersible pumps. -
The authors integrated azimuths and intensities recorded by fiber optics and compared them with post-flowback production-allocation and interference testing to identify areas of conductive fractures and offset-well communication.
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This article describes how Oxy developed an in-house application to handle critical production operations tasks including surveillance, optimization, downtime entry, and well testing. The application, called Nexus, allows well analysts and production engineers to manage twice the number of wells they were able to manage just 5 years ago.
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SEG and SPE join forces to offer access to a robust research portal that harnesses the power of AI and ML.
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This article explores the effect of quantum computing on data science and AI, looking at the fundamental concepts of quantum computing and the key terms used in the field. It also covers the challenges that lie ahead for quantum computing and how they can be overcome.
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The Taiwanese company is upgrading its ships in an effort to improve its ability to work with companies pursuing offshore renewable energy.
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This paper addresses the challenges related to well control and the successful implementation of deep-transient-test operations in an offshore well in Southeast Asia carried out with the help of a dynamic well-control-simulation platform.
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This paper presents an approach for automatic daily-drilling-report classification that incorporates new techniques of artificial intelligence.
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The authors of this paper present the results of implementing a rig-automation solution applied to 20 wells in Ecuador in 2022.
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The authors of this paper propose an artificial-intelligence-assisted work flow that uses machine-learning techniques to identify sweet spots in carbonate reservoirs.
