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Record W1991485322 · doi:10.2118/165526-ms

Enhanced Vapor Extraction through Foamy-oil flow

2013· article· en· W1991485322 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

VenueSPE Heavy Oil Conference-Canada · 2013
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Regina
FundersPetroleum Technology Research CentreUniversity of Regina
KeywordsPetroleum engineeringSoil vapor extractionOil in placeSolventExtraction (chemistry)ViscosityMaterials scienceVolumetric flow rateOil viscosityOil productionPetroleumChromatographyChemistryGeologyContaminationComposite materialMechanics

Abstract

fetched live from OpenAlex

Abstract Hydrocarbon solvent-based enhanced oil recovery techniques, such as vapor extraction (VAPEX) and cyclic solvent injection (CSI), have showed great potential to recover heavy oil reserves. However, VAPEX suffers from low production rates because of the slow mass transfer and inefficient gravity drainage. CSI benefits from solution gas drive and foamy-oil flow; however, solvent gas release would cause the viscosity of the diluted oil to re-increase to slow down the oil flow. In addition, the oil rate of CSI might be uneconomical due to the long no-production injection/soaking period. This paper proposes a new process, named foamy-oil assisted VAPEX, to enhance the heavy oil recovery. This process applies the same production mode as a traditional VAPEX except the model pressure is reduced cyclically to induce foamy-oil flow. Laboratory experiments are conducted to analyze the new process and compare it with VAPEX under the same well pattern and similar physical conditions. Sandpack permeability is about 5 Darcy. Propane is used to recover a heavy oil sample with a viscosity of 5,875 cP. For VAPEX, model pressure is kept at ~800 kPa. For foamy-oil assisted VAPEX, pressure control in each cycle consists of two periods: a constant pressure period and a pressure reduction period. Results show that a strong foamy-oil flow can be induced through a pressure drawdown, which forms a foamy-oil zone. The foamy-oil flow pushes the solvent-diluted heavy oil inward the solvent chamber, which not only increases the oil production, but also helps solvent to contact the fresh heavy oil and accelerate the mass-transfer process. In the foamy-oil assisted VAPEX, oil that could not be produced in a traditional VAPEX by the gradititional force could be recovered in the foamy-oil assisted VAPEX process by a foamy-oil flow. Compared with a traditional VAPEX, foamy-oil assisted VAPEX can increase the oil production rate by 68.5 % and the final recover factor by 20.4%.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.859
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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.219
Teacher spread0.205 · 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