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Record W1994107724 · doi:10.2118/71361-ms

Drilling with Aerated Drilling Fluid from a Floating Unit Part 2: Drilling the Well

2001· article· en· W1994107724 on OpenAlexaff
Antonio Lage, Hélio Santos, Paulo R. C. Silva

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2001
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsImpact
FundersPetrobras
KeywordsDrillingDrilling fluidPetroleum engineeringSeparator (oil production)Measurement while drillingDrilling engineeringWork (physics)Marine engineeringDrill pipeEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract The biggest challenge of the aerated fluid drilling technology development was overcome with the well in Albacora being drilled with the semi-submersible platform Petrobras 17 (P17). A previous paper1 described the stages before the drilling activity: planning, new equipment, rig modifications and all the preparation for drilling the well. This paper describes the drilling operation itself. All the important points and differences relative to the conventional drilling method are highlighted, with special emphasis to the new equipment installed at the platform: the vertical compact separator, the automatic control system, and the RiserCap™rotating control head. The operation of the new equipment, performance and the problems observed are presented and discussed. The points of improvement are suggested and ways to move forward with this new technology also discussed in the paper. The present work also addresses the positive impact of this field test relative to the implementation of the light-weight fluids technology from floating units. This initiative has been carried out systematically by Petrobras in the form of a Joint Industry Project (JIP) and has been congregating operators, service companies and consultants. The next steps of this project to use effectively light-weight fluids for drilling in deepwater are discussed. The experienced obtained with this operation was crucial to direct and guide the most important points to be studied and developed in the next phase of the project.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.209
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2001
Admission routes1
Has abstractyes

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