AI/machine learning
As carbon capture scales up worldwide, the real challenge lies deep underground—where smart reservoir management determines whether CO₂ stays put for good.
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 new AIQ ownership structure will see Presight acquire 51% shareholding, with ADNOC retaining 49% and receiving a 4% stake in Presight. AIQ will continue to operate as a standalone company.
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This paper presents the design and development of a prototype intelligent water-injection and smart allocation tool aimed at achieving autonomous waterflood operations.
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Developing alternative power supplies with wide-scale reliability, dependability, and minimization or elimination of GHG emissions within feasible capex/opex scenarios is the brass ring of sustainability and energy security—and data are helping us get there.
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In the pursuit of sustainable industrial operations, three pivotal objectives emerge: risk reduction, safety assurance, and cost minimization. Integrating these objectives into digital transformation strategies enables operators to effectively manage emissions and achieve success.
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Supervised learning was used to develop an ensemble of models that account for historical production data, geolocation parameters, and completion parameters to forecast production behavior of oil and gas wells.
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The combined effort aims to reduce the time necessary for and increase the detail and accuracy of seismic interpretation, including for carbon sequestration studies.
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The national oil company credits lean operating practices and AI for making the three-well, 45,000 B/D project economically viable.
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From the first supercomputer to generative AI, JPT has followed the advancement of digital technology in the petroleum industry. As the steady march of innovation continues, four experts give their views on the state and future of data science in the industry.
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The act aims to create safeguards around general purpose artificial intelligence, limit the use of biometric identification systems by law enforcement, and ban social scoring the untargeted scraping of facial images from CCTV footage to create facial recognition databases.
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More than two dozen artificial intelligence systems are being celebrated for delivering massive value to the national oil company.