Drilling automation
This comprehensive review of stuck pipe prediction methods focuses on data frequency, approach to variable selection, types of predictive models, interpretability, and performance assessment with the aim of providing improved guidelines for prediction that can be extended to other drilling abnormalities, such as lost circulation and drilling dysfunctions.
New case studies highlight how artificial intelligence, advanced hardware, and innovative business models are enabling success in drilling automation.
This paper tests several commercial large language models for information-retrieval tasks for drilling data using zero-shot, in-context learning.
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The SPE Drilling and Wells Interoperability Standards group proposes a dual-path strategy to overcome the technical and commercial barriers facing the advancement of drilling automation. -
This paper presents an approach for automatic daily-drilling-report classification that incorporates new techniques of artificial intelligence.
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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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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.
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The oilfield service giant said it has taken another big step toward fully autonomous drilling operations in its latest project offshore Brazil.
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The companies have integrated their platforms in an effort to increase flexibility and interoperability.
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Few oil and gas companies give data science projects the better part of a decade to prove out, but that’s just what this one did.
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This paper describes an 18-month intensive continuous improvement process between an operator, a rig contractor, and bottomhole-assembly (BHA) service providers aimed at reducing BHAs per well in two Oklahoma rigs.
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This paper presents the study, resulting recommendations, and a proposed change in standard bottomhole-assembly configurations to reduce service-quality-compromising incidents and productive time lost from jar twistoffs.
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This paper presents an approach to optimize the location of wellhead towers using an algorithm based on multiple parameters related to well cost.
