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Record W4323657668 · doi:10.2118/212779-ms

Oil in Water Emulsion Formation in SAGD with Chemical Additives

2023· article· en· W4323657668 on OpenAlexaff
S. Ali Ghoreishi, Javier O. Sanchez, Julian D. Ortiz Arango, Ian D. Gates, S. Hossein Hejazi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsConocoPhillips (Canada)University of Calgary
Fundersnot available
KeywordsEmulsionOil sandsAsphaltPetroleum engineeringSteam-assisted gravity drainageOil dropletPorous mediumMaterials sciencePulmonary surfactantChemical engineeringPorosityComposite materialGeology

Abstract

fetched live from OpenAlex

Abstract The in-situ formation of oil in water emulsions can contribute to the oil mobilization when combined with Steam-Assisted Gravity Drainage (SAGD). The produced fluids in SAGD operations and sand pack SAGD experiments often show the existence of both oil in water and water in oil emulsions. Due to the opaque nature of sand packs, however, it is unclear whether the emulsions are formed in-situ during the flow through porous media or in the production tubing. This study aims at understanding the impact of a surfactant known as "High-temperature Emulsifying Agent" (HEA) as an additive on the SAGD process and the possibility of forming preferred oil in water emulsions. The high-temperature fluid flow experiments are performed in 2.5D glass micromodels which are placed in a custom built compact high pressure-high temperature (HPHT) visual cell. Hot water and HEA solution (3000 ppm concentration) at 82 °C are injected at a constant rate of 5 μl/min. The injected fluid first displaces bitumen in the form of an advancing finger, forming a condensate-bitumen interface which is slowly advancing towards the production port at the bottom end of the model. Hot water initially displaces bitumen from the pores leaving a film of bitumen on the grain surfaces which is eventually removed as the injection continues. Water droplets dispersed in bitumen are observed at the areas experiencing high shear forces, i.e., near the main two-phase front and close to the production port. In contrast to the hot water process, no oil film is observed during the HEA injection. In the presence of HEA solution, oil in water emulsion is formed at the condensate-bitumen interface and ahead of the interface deep in the oil zone. The latter could be the result of corner flow which promotes the fast distribution of HEA solution throughout the model, ahead of the main water-oil interface. This work provides insights on the role of surfactants in forming oil in water emulsions in steam-based bitumen production. A novel HPHT visual cell enables the rapid assessment of solvent-surfactant-steam recovery processes and a better understanding of the active emulsifying mechanism in this system.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.201
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes1
Has abstractyes

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