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Record W2002359034 · doi:10.1021/ef900690y

Numerical Simulation of Displacement Mechanisms for Enhancing Heavy Oil Recovery during Alkaline Flooding

2009· article· en· W2002359034 on OpenAlexaff
Mohamed Arhuoma, Daoyong Yang, Mingzhe Dong, Heng Li, Raphael Idem

Bibliographic record

VenueEnergy & Fuels · 2009
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of CalgaryPetroleum Technology Research CentreUniversity of Regina
Fundersnot available
KeywordsEmulsionSurface tensionEnhanced oil recoveryDrop (telecommunication)Pressure dropPermeability (electromagnetism)In situPetroleum engineeringViscosityWater floodingChemistryRelative permeabilityMaterials scienceGeologyMechanicsThermodynamicsComposite materialPorosityOrganic chemistry

Abstract

fetched live from OpenAlex

In this paper, a simulation technique has been developed and successfully applied to numerically simulate the experimentally determined displacement mechanisms governing alkaline flooding for enhancing oil recovery in heavy oil reservoirs. The measured pressure drop and oil recovery during the alkaline flooding processes have been found to increase as the alkaline concentration increases. The increase in pressure drop is mainly due to in situ formation of water-in-oil (W/O) emulsions, and oil recovery is thus improved because of the blockage of the high-permeability zones. The interfacial tension between heavy oil and alkaline solutions, viscosity of the in situ generated W/O emulsion, and relative permeabilities during waterflooding and alkaline flooding processes have been experimentally determined. An excellent agreement between the measured and simulated pressure drop and cumulative oil production are obtained by taking both the measured viscosity of W/O emulsions and the relative permeability into account. In particular, the in situ generation of W/O emulsion during alkaline flooding in heavy oil reservoirs has been numerically found to occur in the high-permeability zones. This finding is consistent with the experimentally determined displacement mechanisms (i.e., in situ generation of W/O emulsion) in the literature.

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)0.000
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: none
Teacher disagreement score0.753
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.008
GPT teacher head0.237
Teacher spread0.229 · 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 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

Citations64
Published2009
Admission routes1
Has abstractyes

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