Drilling automation
The authors of this paper present an autonomous directional-drilling framework built on intelligent planning and execution capabilities and supported by surface and downhole automation technologies.
The authors of this paper discuss a global rate-of-penetration machine-learning model with the potential to eliminate learning curves and reduce time and costs associated with developing a new model for every field.
The authors of this paper describe a project that demonstrated the feasibility of using deep-learning and machine-learning approaches to introduce camera-based solids monitoring to the drilling industry.
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A joint webinar conducted by the Human Factors and Ergonomics Society and the Society of Petroleum Engineers addressed the role of human factors in automation in the oil and gas industry.
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This paper highlights the potential of machine learning to be used as a tool in assisting the drilling engineer in bit selection through data insights previously overlooked.
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The authors write that simple changes in drillstring design can lead to huge savings in a climate that demands continual reductions in well-delivery time and well costs.
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The SPE Workshop “Impact of Digitalization on Drilling Operations” began on 29 November in Al-Khobar, Saudi Arabia, welcoming 316 attendees from 17 countries and 44 companies.
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Nabors' RZR-equipped rig has successfully drilled multiple horizontal wells in the Permian Basin.
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Remote operations and automation have reshaped the drilling landscape in recent years, but this may be just the beginning. Find out here which big milestones may be coming up next for the drilling sector.
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This paper presents an automated directional-drilling process executed on a commercial well in the Norwegian sector of the North Sea, where a next-generation intelligent rotary steerable system completed a well section in a single run.
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This paper describes a collaboration between the operator and a service company that resulted in a successful deployment of an automation platform to manage risks and optimize drilling operations in exploration wells.
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This paper discusses the strategy, approach, and challenges faced in the adoption and implementation of an onsite and remote automated-drilling performance measurement.
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An automated detection application helped identify stringers early for an operator of a mature field in the North Sea while drilling multilateral wells through reservoir sections containing hard calcite stringers interspersed in sand formations with low unconfined compressive strength. The application guided drilling decisions that minimized invisible lost time and sh…
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