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Record W2092395542 · doi:10.2118/141515-pa

A 3D Analytical Model for Wellbore Friction

2010· article· en· W2092395542 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2010
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsWellboreMechanicsTension (geology)Rotation (mathematics)EngineeringGeologyPetroleum engineeringMathematicsGeometryMaterials sciencePhysicsCompression (physics)

Abstract

fetched live from OpenAlex

Summary This paper presents a new friction model for application in petroleum wells. Although very simple, it applies for all wellbore shapes such as straight sections, drop-off bends, build-up bends, side bends or a combination of these. The drillstring is modelled as a soft string. In high tension the string weight is negligible as compared to the tension. This leads to simplified equations where the friction caused by the weight is negligible. For this case the friction in a bend is formulated in terms of the 3D dogleg. The same model therefore applies for 2D and 3D wellbores. The entire well can be modelled by two sets of equations, one for straight wellbore sections and one for curved wellbores. The latter is based on the absolute directional change, or the dogleg of the wellbore. Three worked examples are given in the paper: a 2D well, a 3D well and combined hoisting and rotation in the 3D well. One main purpose of this paper is to provide a simple explicit tool to model and to study friction throughout the well by separating gravitational and tensional friction effects.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.581
Threshold uncertainty score0.679

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.191
Teacher spread0.185 · 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