Data & Analytics
Major increases in hydrocarbon production require both incremental and revolutionary technologies, industry leaders said during the SPE Hydraulic Fracturing Technology Conference.
This paper presents an automated workflow deployed for scheduling and validating steady-state production-well tests across more than 2,300 wells in the Permian Basin.
This paper presents a multifaceted approach leveraging precise rig control, physics models, and machine-learning techniques to deliver consistently high performance in a scalable manner for sliding.
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This paper describes the development of a comprehensive digital solution for well surveillance and field-production optimization for an offshore field consisting of four stacked reservoirs, each containing near-critical fluids. -
The firm’s latest report, Leading a Data-Driven Transition, presents the results of its annual survey of nearly 1,300 senior professionals and divides the respondents into two groups, which it calls “digital leaders” and “digital laggards.”
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Collaboration agreement lays foundation for advancing tech and know-how for harsh environment operations.
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The Space Act Agreement will allow BP and NASA to share technologies and technical expertise with the goal of benefiting human space exploration and energy production.
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Chevron looks into using remotely operated vehicles to scrub marine growth from subsea structures.
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The support vessel operator has invested in project-management software and in making connections using Starlink satellites.
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European oil and gas company Aker BP has agreed to a software-as-a-service collaboration with software firm Aize.
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The Norwegian data company has launched a 3D seismic survey in the Equatorial Margin area.
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The industry is balancing brains and bots as it squeezes out barrels of oil production.
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Energy efficiency is crucial for the oil and gas industry, where operational costs and environmental impact are under constant scrutiny. Predicting and managing electrical consumption and peak demand accurately, especially with the variability of weather conditions, is a significant challenge. This work presents a neural network model trained on historical weather and…
