Drilling
Improved bit and bottomhole-assembly technologies and designs have helped turn what used to be record-breaking drilling runs into routine expectations.
The project with ExxonMobil used closed-loop drilling and digital well-construction technologies.
ExxonMobil's Jason Gahr uses the five stages of grief to explain how the upstream industry should respond to the rise of AI.
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Without exception, the featured articles reflect increased volumes of surface and downhole data that are being captured and analyzed to enable deep learning, improved efficiency, safety, and value. -
This paper discusses how oil and gas companies are using a new generation of AI-driven applications powered by computational-knowledge graphs and AI algorithms to create a digital knowledge layer for oil and gas wells that provides a timeline of significant well events.
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Drilling systems automation (DSA) is moving into commercial activities on a broad front. Equipment suppliers are delivering automated drilling-control systems, and everyone (equipment suppliers, service companies, drilling contractors, operators) is delivering systems-automation applications.
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The complete paper presents a process used to successfully implement a rig-based drilling advisory system (RDAS) across a mixed group of rig contractors.
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The complete paper presents a drilling semantic framework that allows software solutions to achieve automatic and versatile self-configuration.
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One of the frustrating aspects of well-productivity analysis is identifying the causes of lower-than-expected production/injection during initial well lifetime. Our task is to evaluate the multivariate aspects of well design.
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In the current work, a rig advisory system is developed to continually improve rate of penetration (ROP) and drilling performance. An intelligent drilling advisory system (IDAS), based on a soft closed-loop solution with multiple regression analysis has been established.
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For the development of the Dvalin high-pressure/high-temperature (HP/HT) gas field in the Norwegian Sea, a completion scheme using standalone screens is planned.
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Wells in deepwater reservoirs show significant rate decline with time as the result of various causes. A diagnostic tool for quantification of factors influencing well-productivity decline is presented in this paper.
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The success of water-conformance operations often depends on clear identification of the water-production mechanism. Such assessment can be complicated significantly when formation damage is also occurring.
