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Record W3122490440 · doi:10.3997/2214-4609.202011678

Effect of Dip Angle on Recovery Factor During Free Fall Gravity Drainage and Forced Gravity Drainage

2021· article· en· W3122490440 on OpenAlexaff
Maryam Hasanzadeh, R. Azin, Rouhollah Fatehi, Sohrab Zendehboudi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsDrainageGeologyOrientation (vector space)Geotechnical engineeringMatrix (chemical analysis)MechanicsMaterials scienceGeometryMathematicsPhysicsComposite material

Abstract

fetched live from OpenAlex

Summary Gravity drainage is an effective recovery mechanism in the majority of fractured reservoirs. In this study, the effects of matrix and fracture orientation, and 0–20 degrees’ deviation from vertical alignment on recovery factors were investigated during free fall gravity drainage (FFGD) and forced gravity drainage (FGD). Experiments were conducted in a novel fractured sand pack with a different number of fractures. Water was used as the wet phase, and during the FGD process, nitrogen at a constant rate of 10 cc/min was used as the non-wet phase. Results demonstrated that final recovery factors in FGD were almost 3% more than FFGD experiments. Also, it is found that depend on the number, position, and orientation of fractures, the final recovery factor by increasing deviation from vertical alignment can increase or decrease. In other words, the position of matrix and fractures and their orientation have an important effect on the rule of fluid flow mechanisms and enhance oil recovery.

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 score0.002
Threshold uncertainty score0.004

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 communication0.0000.000
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 head0.004
GPT teacher head0.215
Teacher spread0.211 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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