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Record W2010944122 · doi:10.2118/08-02-08-tn

The Role of Connate Water Saturation in VAPEX Process

2008· article· en· W2010944122 on OpenAlexaffabout
Brij Maini, S. Reza Etminan, Riyaz Kharrat

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2008
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSaturation (graph theory)Mixing (physics)Mass transferPermeability (electromagnetism)Water vaporRelative permeabilityOil in placePetroleum engineeringSolventWater injection (oil production)Surface tensionCapillary pressureChemistryMineralogyGeologyThermodynamicsChromatographyPetroleumGeotechnical engineeringPorosityPorous mediumMembraneOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract A large fraction of the physical model tests of the VAPEX process reported in the literature have been conducted without any connate water in the system. The absence of connate water was rationalized by suggesting that it has little or no influence on relative permeability of oil and since the vapourized solvent does not dissolve in water, there is no effect of water on the mass transfer process. However, this ignores the possible contribution of oil spreading at the gas-water interface to the mass transfer and the contribution of film drainage to oil relative permeability at low oil saturation. We have evaluated the effect of connate water on VAPEX performance using physical model experiments carried out in a visual model with different connate water saturations. Butane was used as the solvent and Ottawa sand was used for packing the model to obtain permeability and capillary pressure values comparable to field conditions. In addition to the visual observations of the size and shape of the vapour chamber, the rates of oil and gas production were monitored during the experiments. The results show that connate water has a measurable effect on the process, both in terms of the shape of the vapour chamber and the drainage rate of the diluted oil. The presence of connate water causes faster spreading of the vapour chamber in the lateral direction and tends to increase the thickness of the mixing zone. This increase in the mixing zone thickness appears to result from capillarity driven fingering phenomenon. The mixing zone had a distinct uneven appearance that was similar to patterns generated by frontal instabilities in miscible displacements. The effect of connate water on the drainage rate was an increase in the initial rate, but a reduction in the rate, subsequently. The presence of mobile water speeds up the communication between the two wells and leads to even faster spreading of the vapour chamber. Introduction Although several successful SAGD and CSS field projects have been reported, the high cost of steam generation, considerable energy loss, need for water and water treatment(1) are some of the problems which necessitate finding a more effective and environmentally friendly recovery method. Meanwhile, solvent-based processes, like VAPEX, have drawn more attention due to their potential advantages. In this process, vapourized light hydrocarbons, like propane and butane or a mixture of these with carrier gases, are used. VAPEX is a solvent analogue of the SAGD process and uses essentially the same well configuration(1). Solvent dissolves into the bitumen and reduces its viscosity through dilution, swelling and de-asphalting mechanisms(2). It has been noted that vapourized rather than liquid solvents produce a higher driving force for gravity drainage due to a higher density difference between bitumen and solvent(3). The optimum pressure for solvent injection is near its dew point pressure where the solvent solubility in the oil is high. The role of carrier gas is to keep the injected solvent in the vapour phase at the operating pressure.

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: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
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 head0.003
GPT teacher head0.179
Teacher spread0.176 · 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

Citations20
Published2008
Admission routes2
Has abstractyes

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