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Record W2946359044 · doi:10.3968/11004

Analyses of Fluids Used in Gravel Pack Placement in Sand Control Operations

2019· article· en· W2946359044 on OpenAlexvenueno aff
Stanley Ekwueme, K. K. Ihekoronye, Nkemakolam Chinedu Izuwa

Bibliographic record

VenueAdvances in petroleum exploration and development · 2019
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsXanthan gumCircuit breakerDrilling fluidRheologyViscosityPetroleum engineeringGeotechnical engineeringGeologyFracturing fluidSettlingMaterials scienceEngineeringDrillingMechanical engineeringComposite materialEnvironmental engineering

Abstract

fetched live from OpenAlex

Gravel pack fluids for proppant transport in sand control operations have been analyzed. The two fluids considered have been Xanthan and HEC. Laboratory experiment was conducted on the two fluids to determine their capabilities as carrier fluids. 30Lbs/Mgal and 40Lbs/Mgal of both fluids were considered using Trigonox A-W70 as breaker fluid. The result shows that Xanthan withstood more of the breaker fluid than HEC in terms of sand settling and breaker time. HEC broke at lesser time than Xanthan making Xanthan more capable to hold proppant at downhole conditions while transporting to target depth. The combined analyses of the breaking time, the sand settling capability, the plastic viscosity and pH makes Xanthan more preferable as a gravel pack fluid than Xanthan. However, HEC shows more ease of release of proppant once target depth is reached. Effect of proppant release and cost of proppant supports the choice of HEC as a gravel pack fluids. For optimized operation the combined use of HEC and Xanthan is recommended at calculated depth and downhole condition.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.020
GPT teacher head0.265
Teacher spread0.245 · 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 designObservational
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

Citations0
Published2019
Admission routes1
Has abstractyes

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