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Record W2149145861 · doi:10.2118/150691-ms

Effects of Waterflooding and Solvent Injection on the Solvent Vapour Extraction (VAPEX) Heavy Oil Recovery

2011· article· en· W2149145861 on OpenAlex
Mohammad Derakhshanfar, Xu Jia, Tao Jiang, Fanhua Zeng, Yongan Gu

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 and Exhibition · 2011
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsPetroleum Technology Research CentreUniversity of Regina
FundersNatural Sciences and Engineering Research Council of CanadaPetroleum Technology Research Centre
KeywordsSolventPetroleum engineeringDissolutionMaterials scienceSaturation (graph theory)Water injection (oil production)Light crude oilPermeability (electromagnetism)PorosityChemical engineeringChromatographyChemistryPulp and paper industryGeologyComposite materialOrganic chemistryMembrane

Abstract

fetched live from OpenAlex

Abstract Solvent vapour extraction (VAPEX) process is an economically viable, technically sound, and environmentally friendly in-situ heavy oil recovery method to exploit tremendous heavy oil and bitumen reserves. In this recovery process, significant heavy oil viscosity reduction is achieved through sufficient solvent dissolution and possible asphaltene precipitation. Over the past two decades, several researchers have carefully studied the effects of some major factors on the VAPEX process, such as the test pressure, reservoir porosity and permeability, solvent and heavy oil types, well configuration, and connate water saturation. However, it is unclear how waterflooding and solvent injection will affect a typical VAPEX process. In this paper, waterflooding and solvent injection effects are experimentally studied by using a visual rectangular sand-packed high-pressure VAPEX physical model with a low permeability. The physical model is packed and then saturated with a heavy oil sample at the connate water saturation. Pure propane and a mixture of n-butane and methane are used as respective solvents to extract two different heavy oil samples. The waterflooding effect is examined by performing a series of VAPEX tests with the initial waterflooding, prior to the subsequent solvent injection/soaking. In addition to the visual observation of the solvent chamber evolution, the heavy oil production rate, produced solvent–oil ratio, and asphaltene content of the produced heavy oil are measured during the waterflooding and solvent injection/soaking. It is found that the initial waterflooding causes an oil production reduction in the subsequent solvent injection. Also solvent breakthrough occurs earlier and a small amount of water is produced afterwards. This is because the initial waterflooding creates some low-resistance channels for the injected solvent to bypass the untouched heavy oil. As a result, the heavy oil is not diluted enough to be produced during the subsequent solvent injection/soaking. In the absence of waterflooding, however, solvent injection alone can increase the heavy oil production in comparison with the solvent-soaking process. Moreover, it is visually observed that solvent injection leads to less asphaltene deposition onto the porous media. This is quantitatively verified by a higher measured asphaltene content of the produced heavy oil at a higher solvent injection rate.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.697

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 head0.023
GPT teacher head0.229
Teacher spread0.206 · 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