MétaCan
Menu
Back to cohort
Record W2784268004 · doi:10.11575/prism/5250

On Effects of Wettability on Multiphase Flow in Porous Media

2017· dissertation· en· W2784268004 on OpenAlexaboutno aff
Wei Wu

Bibliographic record

VenueOpen MIND · 2017
Typedissertation
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsWettingPorous mediumMultiphase flowMaterials scienceFlow (mathematics)PorosityGeotechnical engineeringPetroleum engineeringComposite materialMechanicsEngineeringPhysics

Abstract

fetched live from OpenAlex

Heavy oil resources have become an important sector of oil and gas industry. The Athabasca oil sand deposit, mainly in the McMurray Formation, is the largest and most important one in Alberta, Canada. The wettability of porous media is the most important property that directly controls multiphase flow and phase distribution. But there are still arguments about the wettability of the McMurray Formation oil sands and factors that affect the wettability and the consequent water-oil relative permeability curves. In the research reported in this thesis, surface mined unconsolidated McMurray Formation oil sands were analyzed for its wettability and effect on relative permeability. A new method to change the wettability of oil sands sand grains was developed and the wettability was explored by examination of contact angle and relative permeability. It was found that asphaltene and resin adsorption or precipitation on the surface of sand grains alter their wettability from water-wet to oil-wet. Furthermore, water displacement tested are performed to estimate the impact of wettability of the sand grains on the relative permeabilities of oil and water calculated by unsteady state method. The results suggest that in steam chambers where the oil has been extracted at elevated temperature, there is potential for a change of the wettability of the oil sands.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.013
GPT teacher head0.304
Teacher spread0.291 · 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 designSimulation or modeling
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

Citations1
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueOpen MINDSame topicEnhanced Oil Recovery TechniquesFrench-language works237,207