Data & Analytics
Autonomous drilling through managed pressure drilling (MPD) at the Atlantis field has given the operator confidence to scale the method.
The cloud platform provider said the initiative is designed to help energy companies manage and analyze large-scale operational data.
Major increases in hydrocarbon production require both incremental and revolutionary technologies, industry leaders said during the SPE Hydraulic Fracturing Technology Conference.
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As data management (DM) moves from priority to imperative status in the beleaguered upstream industry, growing gaps between DM-mature and DM-immature organizations will determine future leaders. -
Imagine the time when we are no longer concerned about the digital-transformation issues we face today, such as data availability, security, and many others. This would be the time when companies make the best out of digital infrastructure. This era might be here sooner than expected.
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One year after the Johan Sverdrup field came on stream, Equinor says digital technology has proven to be key to safety and value in all parts of the operation, increasing earnings by more than $200 million.
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Incorporating imagination into AI agents has long been an elusive goal of researchers in the space. Imagine AI programs that are able not only to learn new tasks but also to plan and reason about the future.
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The rise of automation has been a common theme in stories that touch almost every business sector. One of the places where automation has shown the most value has been in enterprise security, where it can reduce costs and mitigate vulnerabilities in many instances.
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Field examples presented in the complete paper describe principles of data acquisition with a sand-detection tool when run in combination with a production logging string and results of logging in slightly deviated wells completed with sand screens.
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The complete paper provides an approach using machine-learning and sequence-mining algorithms for predicting and classifying the next operation based on textual descriptions.
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The complete paper describes an automated machine-learning approach to determine the spatial variation in decline type curves for shale gas production, based on existing data of production, completion, and geological parameters.
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In addition to the well-recognized elements of digital transformation such as real-time monitoring, remote intelligence, and extraction of insights from data, there is a need to evolve the industry hardware through application of enhanced edge computing.
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Automated image-processing algorithms can improve the quality and speed in classifying the morphology of heterogeneous carbonate rock. Several commercial products have produced petrophysical properties from 2D images and, to a lesser extent, from 3D images.
