Data & Analytics
The two companies say they plan to work together to use agentic AI to increase the capabilities of technical experts.
This article is the first in a Q&A series from the SPE Methane Emissions Management Technical Section (MEMTS) on methane intelligence and how oil and gas teams translate emissions data into credible decisions and measurable reductions.
This paper presents a robot integrated with a microcontroller that provides multiple functions to help with data logging, analysis, and reporting to identify hazards and improve safety protocols.
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Even as industry faces policy and tariff uncertainty, companies view spending on digital transformation as a driver of efficiency. -
Geophysicist Markos Sourial discusses advances in seismic imaging, the challenges of modern data processing, and what they mean for the next wave of subsurface professionals.
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The Tela artificial intelligence assistant is designed to analyze data and adapt upstream workflows in real time.
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SPE and The Open Group have signed a memorandum of understanding to advance collaboration and innovation in the global energy industry.
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In this third work in a series, the authors conduct transfer-learning validation with a robust real-field data set for hydraulic fracturing design.
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This research aims to develop a fluid-advisory system that provides recommendations for optimal amounts of chemical additives needed to maintain desired fluid properties in various drilling-fluid systems.
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This paper explains that the discovery of specific pressure trends, combined with an unconventional approach for analyzing gas compositional data, enables the detection and prediction of paraffin deposition at pad level and in the gathering system.
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This paper discusses a comprehensive hybrid approach that combines machine learning with a physics-based risk-prediction model to detect and prevent the formation of hydrates in flowlines and separators.
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Adaptability, collaboration, and digital technologies are all pages in Aramco’s oilfield R&D playbook.
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SponsoredSince 1997, intelligent completions have transformed reservoir management, but adoption remains limited due to perceived complexity. The industry reached a pivotal moment with the development of next-generation technologies that address longstanding challenges and offer simpler operation solutions.
