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Record W4252838952 · doi:10.2118/2008-089

Modelling of Mass Transfer Boundary Layer Instability in the CO-Vapex Process

2008· article· en· W4252838952 on OpenAlexafffundabout
M. Javaheri, J. Abedi

Bibliographic record

VenueCanadian International Petroleum Conference · 2008
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsUniversity of Calgary
FundersWestern Canada Research Grid
KeywordsMass transferBoundary layerInstabilityProcess (computing)Layer (electronics)MechanicsBoundary (topology)Computer scienceMaterials sciencePhysicsMathematicsComposite materialMathematical analysis

Abstract

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Abstract Vapex (vapor extraction) is a promising technique for the recovery of heavy oil and bitumen reservoirs, especially for cases where steam-assisted gravity drainage and other thermal recovery methods are not economical. In the Vapex process, a solvent is injected into the reservoir to reduce the oil viscosity and mobilize it towards the production well. CO2-based Vapex is an attractive option from both economical and environmental perspectives. In CO2-based Vapex, unlike other hydrocarbon solvents, the dissolution of CO2 in oil can result in a density increase of the diluted oil. As a consequence, the diluted oil has a higher density than the immobile oil beneath and a gravitationally unstable diffusive boundary layer is induced, which may lead to natural convection. In this paper, a mathematical model for the diffusive boundary layer in the CO2-oil contact region is developed; and, the possibility of convective mixing is examined using linear stability analysis, based on the amplification of the initial perturbations. It is found that in most experimental cases, depending on the Rayleigh number of the porous medium, convective mixing occurs, which results in higher dissolution of CO2 in oil and thus a higher oil production rate than what is expected from theoretical analysis. This would explain the unexpected higher oil production rate of some experiments in Vapex when CO2 was used as a solvent. In field-scale operations, the results are different. In field cases, since it is almost impossible for the Rayleigh number to exceed the critical Rayleigh number (Rac), convection does not happen. Introduction The world's total reserve of heavy oil and bitumen is about six trillion barrels, which is about six times the amount of the conventional resources[1]. A major part of these resources is in Canada, Venezuela and the United States. Most of these reserves are at such depths that open-pit mining cannot be used economically, and in-situ methods have to be used to reduce the viscosity of the oil in-place and mobilize it. Either thermal methods or non-thermal methods can be used to recover these reserves. The viscosity of oil is a strong function of temperature and decreases sharply with increasing temperature. Currently steam-assisted gravity drainage (SAGD), a thermal method, is a popular method for the recovery of heavy oil and bitumen and has been successfully applied in several fields. Despite the success of this process for some reservoirs, there are many reservoirs that SAGD cannot be applied due to excess heat loss, which makes it uneconomical to operate. In thin reservoirs, the need for steam increases and the steam-to-oil ratio (SOR) is prohibitively high. Many oil and bitumen reservoirs have a bottom aquifer, and heat loss to the water can make the process infeasible[2]. There are also reservoir conditions where SAGD may not be applied, such as when water saturation is high, or porosity is low. In cases where SAGD cannot be applied, Vapex is the most promising technique for the recovery of these resources.

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 categoriesInsufficient payload (model declined to judge)
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 score0.024
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.051
GPT teacher head0.272
Teacher spread0.221 · 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.

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

Citations3
Published2008
Admission routes3
Has abstractyes

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