Data & Analytics
Switching from continuous circulation to cyclic huff-‘n’-puff operation in enhanced geothermal systems can significantly delay thermal breakthrough, sustain higher production temperatures, and improve long-term economic performance.
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.
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Gaining insights from digital data in the highly technical exploration and production industry requires experience, knowledge, and awareness about the acquisition of the data. The technologies presented here aim to facilitate the decision-making process while requiring less time and lower costs without sacrificing the accuracy of the data and still decreasing the prob… -
The authors of this paper describe the development and implementation of a data-streaming solution that allows for real-time processing and interpretation of fiber-optics data.
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The authors of this paper present a system, developed to achieve data transmission using a time-division approach, that includes sealed chambers for microchip storage, a power-release device, and a circuit.
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Industry leaders are harnessing the power of data to improve efficiencies, eliminate nonproductive time, and reduce Capex.
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The data-management company has raised its investment in the technology company IWS by $7.9 million, with an agreement to invest an additional $25 million depending on the performance of IWS.
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The optimization process presented in this paper gradually incorporates process control, digital twins, planning, scheduling, and blending for refiners.
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A recently signed memorandum of understanding is designed to let the two companies work together on digital transformation and decarbonization.
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Synthetic data generation is a solution that allows citizen data scientists and auto ML users to quickly and safely create and use business-critical data assets. Benefits go beyond democratizing data access, and even those with privileged data access are building synthetic data generators into their work flows.
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This paper describes a novel method based on machine learning to maintain an evergreen competency database. The tool reduces discrepancies between organizational requirements and the actual talent deployment by using unstructured corporate data.
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Geosteering is supposed to ensure the wellbore stays in the most-productive zone, but a recent study suggests it often misses the mark.
