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Record W2060372779 · doi:10.2118/144071-ms

The Effects of Wall Slip in a Couette Rheometer When Measuring and Comparing Hydraulic Fracturing Fluids

2011· article· en· W2060372779 on OpenAlexaff
Scott D. Churchill

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsRheometerSlippageRheologySlip (aerodynamics)Materials scienceHydraulic fracturingCouette flowSurface roughnessGeotechnical engineeringSurface finishSlippingGeologyComposite materialMechanicsFlow (mathematics)Mechanical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract The most common apparatus to gather rheological properties on hydraulic fracturing fluids is the Couette rheometer. It functions by rotating a pressurized cup filled with a sample of the fluid around a bob. The rheometer calculates the apparent viscosity and power law values by measuring the friction between the bob, the fluid, and the cup based on the deflection of the bob at different shear rates of the rotating cup. With this sort of apparatus, the assumption is made that any "slippage" that the fluid encounters at the wall's surface is negligible. Although this assumption may be valid with other types of fluids such as those within the food or cosmetics industry, due to the unique characteristics of hydraulic fracturing fluids this is not always the case. Based on a rhelogical study of three different types of hydraulic fracturing fluids presented in this paper, conclusions were drawn on the effects of wall slip when measuring and comparing different types fracturing fluids and how this wall slipping phenomenon can be minimized. In this study three types of fracturing fluids were tested: a borate crosslinked water based gel, a surfactant water based gel and a hydrocarbon based gel. The water based gels demonstrated a significant amount of wall slip due to a phase separation of the water and gel. No phase separation was found in the hydrocarbon based fracturing gels, as such no wall slippage was observed. Several different metals were tested with varying surface roughness in order to attempt to minimize slip. Non-corrosive metals with a roughened surface allowed for higher viscosity readings in the water based gels. The surface roughness played a minimal effect in the viscosity readings for hydrocarbon based gels.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.196
Teacher spread0.177 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations2
Published2011
Admission routes1
Has abstractyes

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