AI/machine learning
The Energy and AI Observatory aims to use up-to-date information on energy demand from data centers to determine how artificial intelligence is optimizing the energy sector.
This article is the third in a Q&A series from the SPE Research and Development Technical Section focusing on emerging energy technologies. In this piece, Zikri Bayraktar, a senior machine learning engineer with SLB’s Software Technology and Innovation Center, discusses the expanding use of artificial intelligence in the upstream sector.
This article presents a results-driven case study from an ongoing collaboration between a midstream oil and gas company and Neuralix Inc.
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The international major has been playing with intelligent programs for years, but this new deal shows that it is now ready to scale those efforts up to cover hundreds of thousands of pieces of equipment. -
BP has invested more than $100 million into nine different startup companies in the past 2 years—but only one of them wants to turn your brain into a piece of its software.
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A new detection and alerting methodology, validated on more than 100 North America onshore wells, blends well information and real-time data to determine a probabilistic belief system. An operator used the system to detect, predict, and alert rig crews to washouts and pump failures.
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This paper demonstrates the viability of a production-data-classification approach adapted from real-time face detection for identifying restimulation candidates.
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Unstructured data, such as process logs, safety reports, and public records, make up the bulk of data produced from the oil field. Emerging NLP technology has been designed to help make sense of this data, enabling better insights into near-accidents.
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DNV GL has published a paper to support the safe use of artificial intelligence. The paper asserts that data-driven models alone may not be sufficient to ensure safety and calls for a combination of data and causal models to mitigate risk.
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Machine learning and artificial intelligence technology offer offshore operators the chance to automate high-cost, error-prone tasks to avoid the effects of inconsistency and errors in analysis, improving efficiencies and safety.
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Technologies are being developed that have the potential to support marine mining in all stages from prospection to decommissioning. These developments will likely have substantial influence in the oil and gas industry, itself searching for ways to maximize exploitation of assets.
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Hundreds of rod-lift wells in North Dakota are about to get a big upgrade.
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A recent research effort has shown that the digital journey is full of stumbling blocks. Just like humans, advanced computing technology will get some things right and some things wrong.
