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Record W4288535766 · doi:10.1002/cjce.24578

Cold heavy oil production with sand simulation including wormhole propagation and foamy oil behaviour

2022· article· en· W4288535766 on OpenAlexafffundvenue
Farzan Sahari Moghaddam, Mohammed El‐Naghy, Amer Aborig, Amin Etminan

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsMemorial University of Newfoundland
FundersMemorial University of Newfoundland
KeywordsWormholePetroleum engineeringOil productionViscosityOil consumptionEnvironmental scienceProcess (computing)Materials scienceGeologyComputer sciencePhysicsEngineeringAutomotive engineeringComposite material

Abstract

fetched live from OpenAlex

Abstract Cold heavy oil production with sand (CHOPS) is a primary production method used for heavy oil reservoirs with no requirements of external energy consumption. A new model for CHOPS is simulated by incorporating wormhole propagation and foamy oil behaviour mechanisms to evaluate the recovery of an extra‐heavy oil reservoir of the Athabasca region. The most critical mechanisms of CHOPS, wormhole propagation and foamy oil behaviour, are captured by using Wang's model for wormhole propagation and Uddin's model of gas exsolution. After 120 months of simulation, 53.38%, 99.76%, and 100% of wormhole propagation were achieved during three time steps of 12, 48, and 60 months, respectively, toward the sides of the studied reservoir section. The propagation was achieved within all directions of the investigated section compatible with the erratic nature of wormhole propagation. Furthermore, the application of Uddin's model was incorporated into production by reducing the fluid viscosity as a result of the foamy oil behaviour. Over 3% of the recovery was achieved at the end of the primary CHOPS phase simulation by taking into account that we modelled the recovery based on highly viscous oil with API 7.5. Finally, the model can provide an improved understanding of the primary CHOPS process by considering its two significant mechanisms.

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 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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.017
GPT teacher head0.229
Teacher spread0.212 · 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 teacher head, 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

Citations2
Published2022
Admission routes3
Has abstractyes

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