Drilling automation
This paper describes an autonomous drilling approach using an autocurve-drilling mode to automatically drill curved sections without human intervention and complete autonomous well construction.
This paper presents an approach for automatic daily-drilling-report classification that incorporates new techniques of artificial intelligence.
The authors of this paper present the results of implementing a rig-automation solution applied to 20 wells in Ecuador in 2022.
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The authors describe a drilling-systems automation roadmap for a transition from humans to automation in the general drilling space.
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The authors describe a platform that integrates advanced data analytics and hydraulic modeling in real time for managed-pressure-drilling applications.
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Totally automated drilling today looks like a robot doing all the heavy lifting on a drilling floor. By 2025, there may no longer be anything surprising about it.
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A supervised machine-learning algorithm is developed to classify drilling parameters that increase rate of penetration and bit endurance for use in unconventional fields in Australia.
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The failure of the Raptor rig to drill its first-ever well offers a short history of the challenges that came with creating the first automated drilling rig.
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Drilling automation is not “there” yet, but it no longer seems like a pipe dream.
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This paper describes how severe rig limitations were overcome through an optimization plan in which an optimal bottomhole assembly was designed and drilling practices were customized.
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This paper presents a methodology that aims to allows the anticipation of problems such as mechanically stuck pipe or lockup situations when running casing or completion strings in hole.
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The 2021–2022 Drillbotics competition will require the contestants to integrate human factors engineering considerations into their automated drilling rigs for the first time.
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Intellilift and Transocean are working together on a software solution to expedite the well construction process.