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Record W2607865193 · doi:10.3968/9448

Laboratory Experiment on Inaccessible Pore Volume of Polymer Flooding

2017· article· en· W2607865193 on OpenAlexvenueno aff
Yiqi Zou, Zijuan Cao, Erlong Yang

Bibliographic record

VenueAdvances in petroleum exploration and development · 2017
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPolymerVolume (thermodynamics)KeroseneMaterials scienceMolecular massElectromagnetic coilMolar mass distributionChemical engineeringMineralogyComposite materialPolymer chemistryChemistryThermodynamicsOrganic chemistryPhysicsEngineering

Abstract

fetched live from OpenAlex

The research on inaccessible pore volume is completed on the basis of laboratory experiments. The experiment prepared 4 different kinds of polymers, whose molecular weight are 8 million, 12 million, 16 million and 20 million whose molecular coil size are measured by light blockage counter. Through kerosene mass method we can get pore cumulative distribution of field cores and finally plot the relation between the inaccessible pore volume and molecular coil size of polymer. The size of small pore where primary water was taken as the minimum number polymer coils can be passed. Then the polymer molecular weight with better compatibility with rock pores is optimized. The study shows with the increase of polymer relative molecular mass, pore volume increased linearly. The conclusion can better guide the selection of the polymers in practical production.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.273
Teacher spread0.259 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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