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Record W2072534332 · doi:10.2118/149190-ms

Solvent Chamber Development in 3D Physical Model Experiments of Solvent Vapour Extraction Processes SVX With Various Permeabilities and Solvent Vapour Qualities

2011· article· en· W2072534332 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCanadian Unconventional Resources Conference · 2011
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsSaskatchewan Research Council (Canada)
FundersPetroleum Technology Research Centre
KeywordsSolventInjectorMaterials sciencePetroleum engineeringChemical engineeringViscosityPorosityChemistryComposite materialGeologyOrganic chemistryThermodynamics

Abstract

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Abstract Solvent vapour extraction (SVX) processes offer an attractive alternative to thermal recovery processes, being less energy intensive; and are more suitable for thinner, partially depleted reservoirs. A typical SVX process uses solvent injection to dilute the heavy oil by reducing its viscosity, allowing it to be mobilized for production. During this process the injection of hydrocarbon solvents results in partial deasphalting of the heavy oil, thus further reducing its viscosity and enhancing the process performance. This work examined the formation and growth of solvent chambers in laterally and vertically spaced horizontal injector/producer well pairs in porous media with five different permeabilities and three different solvent vapour qualities. Consolidation of the porous media due to asphaltene precipitation was also analyzed. Thermal imaging and model excavation studies were performed to investigate the formation and growth of solvent chambers for seven different experiments conducted on a large 3D physical model apparatus. The important findings from this study are as follows: During solvent injection, one or more solvent fingers develop between the injector and producer. The dominant solvent finger becomes a conduit that grows into a solvent chamber connected to the injection well in the upper portion of the reservoir, and develops into an oil drainage conduit connected to the production well in the lower portion of the reservoir. Solvent dispersion layers are located on the margins of both the solvent chambers and the oil drainage conduits. The location and development of these non-uniform solvent chambers and oil drainage conduits are unpredictable, and the oil drainage conduits do not grow significantly in diameter once connected to the production wellbore, limiting the wellbore inflow efficiency and conformity. Asphaltene precipitation and migration can aggravate this inflow problem, further reducing SVX process performance. SVX performance can be improved by increasing the number and diameter of oil drainage connections between the solvent chamber and the production well, and by controlling the oil deasphalting process. This can be done by optimizing injection and production wellbore geometries, and by optimizing solvent injection rates and vapour quality.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score1.000

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 head0.040
GPT teacher head0.247
Teacher spread0.207 · 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