Drilling
This study explores the use of autoencoder models with convolutional neural networks to present a framework and prototype for early and accurate kick detection during offshore oilwell drilling.
Operators aren’t rushing to drill, even as the closure of the Strait of Hormuz drives oil prices up.
Drilling experts recently shared candid views on what will be required for their segment of the upstream business to move to the next stage of development.
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This paper shows how high-frequency, real-time drilling data from wired drillpipe has helped optimization of drilling performance and achievement of additional improvements in the New Mexico Delaware Basin. -
This paper describes how new technology was implemented and deployed through a downhole acoustic network through a sequence of runs in complex North Sea wells under managed-pressure conditions.
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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 drilling semantic framework that allows software solutions to achieve automatic and versatile self-configuration.
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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.
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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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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.
