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Record W2046840327 · doi:10.2118/165396-ms

Optimized Surfactant–Polymer Flooding for Western Canadian Heavy Oils

2013· article· en· W2046840327 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSPE Heavy Oil Conference-Canada · 2013
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsSaskatchewan Research Council (Canada)
FundersPetroleum Technology Research Centre
KeywordsPulmonary surfactantBrineEmulsionAlkali metalChemical engineeringPolymerEnhanced oil recoverySurface tensionPolyacrylamideViscosityChemistrySalinityChromatographyMaterials sciencePolymer chemistryOrganic chemistryComposite materialGeologyThermodynamics

Abstract

fetched live from OpenAlex

Abstract Chemical flooding for Western Canadian heavy oil reservoirs has gained popularity in recent years because of its satisfactory recovery efficiency and low facility cost. Formation brines in most of these reservoirs have extremely high salinity and hardness. Addition of alkali is prone to causing severe precipitation/scaling problems in both the injection/formation brinesand production facilities. As well, breaking of the emulsion generated during oil production is problematic in the presence of alkali. In order to overcome the operation/handling issues associated with alkali, an alkali-free surfactant–polymer (SP) flooding EOR method needs to be developed and evaluated. In this work, several amphoteric surfactants, which exhibit higher salinity- and hardness-resistance than common anionic surfactants, were evaluated in combination with the polymer polyacrylamide. For the crude heavy oil and brine studied, a fairly low interfacial tension (IFT) of 0.012 dyne/cm was measured at 0.1 wt% of surfactant concentration. Emulsification tests showed that the surfactant could easily generate oil-in-water emulsion in the heavy oil–brine system, while it was more difficult to form emulsion with the SP system due to its higher viscosity. Addition of the surfactant helped to slightly increase the polymer solution's viscosity, since the surfactant itself is a viscoelastic fluid. The SP system exhibited long-term stability with consistent viscosity and IFT, whereas an alkaline–surfactant–polymer (ASP) system had increased viscosity for the first 15 days due to solids precipitation in the brine and possible polymer hydrolysis. To compare the recovery efficiency by different chemical injectants, three coreflood tests were conducted using P, SP, or ASP systems. ASP flooding had the highest enhanced oil recovery (chemical injection + extended waterflood] of 25.17% original oil in place (OOIP), followed by SP flooding (24.38% OOIP) and P flooding (20.23% OOIP). However, the potential for operational problems evident with the use of alkali might restrict the application of ASP flooding. Varied oil recoveries at the chemical injection and EWF stages, as well as pressure drop variation (resistance factor), indicated that different recovery mechanisms were involved in each chemical flood. Given its satisfactory recovery results and potential to avoid operational problems, with careful optimization, SP flooding presents a promising method for heavy oil enhanced oil recovery, particularly for Western Canadian heavy oil reservoirs.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.733
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.015
GPT teacher head0.206
Teacher spread0.191 · 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