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Record W2050931799 · doi:10.1520/acem20120027

Effect of Supplementary Cementitious Materials on Rheology of Oil Well Cement Slurries

2014· article· en· W2050931799 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

VenueAdvances in Civil Engineering Materials · 2014
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsWestern University
Fundersnot available
KeywordsMaterials scienceRheologyCementitiousFly ashComposite materialSlurryRheometerCementSilica fumeMetakaolinShear rateShear stress

Abstract

fetched live from OpenAlex

Abstract This study explores the effects of supplementary cementitious materials (SCMs) on the rheological properties of oil well cement slurries. Four different mineral admixtures including metakaolin (MK), silica fume (SF), rice husk ash (RHA), and class F fly ash (FA) were used as partial replacement for API class G oil well cement. A new generation polycarboxylate-based high-range water reducing admixture was used to improve the fluidity of slurries. A series of flow tests was performed using an advanced shear-stress/shear strain controlled rheometer at three different temperatures, namely 23, 45, and 60°C. Rheological properties of cement slurries were calculated from the resulting flow curves using the Bingham plastic model and the Herschel–Bulkley’s model. Changes in shear stress–shear rate relationships, yield stress, plastic viscosity, and shear thinning/thickening behavior were found to be related to temperature and the type and dosage of supplementary cementitious material. Among the four different mineral admixtures tested, low calcium fly ash was found to achieve most suitable yield stress and plastic viscosity values.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.002
GPT teacher head0.198
Teacher spread0.196 · 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