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Record W2567567674 · doi:10.1115/1.4035513

Scaling Criteria for Waterflooding and Immiscible CO2 Flooding in Heavy Oil Reservoirs

2016· article· en· W2567567674 on OpenAlex
Deyue Zhou, Daoyong Yang

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Energy Resources Technology · 2016
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of CanadaPetroleum Technology Research Centre
KeywordsScalingPetroleum engineeringFlooding (psychology)Oil fieldWater floodingDisplacement (psychology)MechanicsGeologyPhysicsMathematicsGeometry

Abstract

fetched live from OpenAlex

Scaling criteria have been developed and validated to evaluate performance of waterflooding and immiscible CO2 flooding in heavy oil reservoirs by using a three-dimensional (3D) sandpacked displacement model. Experimentally, the 3D physical model consisting of a pair of horizontal wells together with five vertical wells is used to conduct waterflooding and immiscible CO2 flooding processes, respectively. Theoretically, mathematical formulae have been developed for waterflooding and immiscible CO2 flooding by performing dimensional and inspectional analyses. The scaling group of the gravitational force to viscous force is found to be negligible when scaling up a model to its prototype. The relaxed scaling criteria are validated by comparing the simulation results of a synthetic reservoir with experimental measurements and then extended for a field application. There also exists a reasonably good agreement between the laboratory measurements and the field application with the determined scaling criteria.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.156
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.241
Teacher spread0.231 · 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