Drilling automation
Current classifications often do not capture the complexity of autonomy in drilling systems. By integrating concepts from aerospace, control theory, and other high-risk industries, this study presents a quantitative framework for systematically assessing and comparing levels of drilling autonomy.
Winners of Alberta's Drilling Technology Challenge cover a range of technologies from robotics to enhance drilling rig safety to AI-enabled energy management, downhole sensing, well navigation, hybrid power systems, and geothermal energy.
The company said that its AD-300, a 50-m-high automated island drilling rig that walks between wells, was delivered 3 months ahead of schedule.
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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. -
This paper presents the first global application of autonomous drilling in deepwater and the journey to reach optimal drilling parameters, integrating proprietary tools from the project’s business partners.
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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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Improved bit and bottomhole-assembly technologies and designs have helped turn what used to be record-breaking drilling runs into routine expectations.
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The project with ExxonMobil used closed-loop drilling and digital well-construction technologies.
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Autonomous drilling through managed pressure drilling (MPD) at the Atlantis field has given the operator confidence to scale the method.
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This paper presents a multifaceted approach leveraging precise rig control, physics models, and machine-learning techniques to deliver consistently high performance in a scalable manner for sliding.
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This paper proposes a novel approach toward drilling maximum-reservoir-contact wells by integrating automated drilling and geosteering software to control the downhole bottomhole assembly, thereby minimizing the need for human intervention.
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In this study, a method was developed to analyze the effects of drilling through transitions on bit-cutting structures and construct an ideal drilling strategy using a detailed drilling model.
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This paper describes a machine-learning approach to accurately flag abnormal pressure losses and identify their root causes.
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