AI/machine learning
Over decades of exploration and production, the oil and gas sector has accumulated vast amounts of legacy data in various formats. Artificial intelligence and machine learning present an opportunity to transform how this unstructured data is processed and used, enabling significant improvements in operational efficiency and decision-making.
SLB will use artificial intelligence-based software to help ensure the delivery of 18 ultradeepwater wells.
This paper describes a deep-learning image-processing model that uses videos captured by a specialized optical gas-imaging camera to detect natural gas leaks.
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In this study, artificial-intelligence techniques are used to estimate and predict well status in offshore areas using a combination of surface and subsurface parameters. -
Almost every day, petroleum engineers are coming to realize that they’ve got an arsenal of good ideas on how to leverage large, messy data sets to add value to their businesses. Those who have enlisted in the Analytics Army have progressed from siloed digitalization attempts to well-concerted digital transformation strategies that reflect high levels of organizational…
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The grant was awarded by the Scottish Funding Council in partnership with Scottish Enterprise to assist in developing an AI demonstrator to optimize subsea decommissioning.
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Chevron and ExxonMobil are working on deals to use natural gas and carbon capture to power the technology industry's AI data centers, executives with the companies said.
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Undocumented orphaned wells pose hazards to both the environment and the climate. Scientists are building modern tools to help locate, assess, and pave the way for ultimately plugging these forgotten relics.
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As we turn the page on our 75th anniversary, JPT’s recent visit to the UAE offers a front-row seat of what some of the industry’s biggest players see coming.
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The USGS has said up to 19 million tons of lithium resource is contained in the briny waters of the Smackover formation in Arkansas.
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Subject-matter experts from industry and academia advanced distributed fiber-optic sensing technologies and their implementation in flow measurement during a special session.
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Technology uptake aimed at optimizing resources, delivering consistency, and augmenting what humans can do.
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This paper investigates the use of machine-learning techniques to forecast drilling-fluid gel strength.
