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Record W2327497707 · doi:10.2118/0308-0091-jpt

Enhanced Heavy-Oil Recovery by Alkali/Surfactant Flooding

2008· article· en· W2327497707 on OpenAlex
Dennis Denney

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Petroleum Technology · 2008
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsOil in placePetroleum engineeringAsphaltEnhanced oil recoveryOil sandsEmulsionEnvironmental scienceUnconventional oilPulmonary surfactantFossil fuelGeologyChemical engineeringWaste managementMaterials sciencePetroleumEngineeringComposite material

Abstract

fetched live from OpenAlex

This article, written by Technology Editor Dennis Denney, contains highlights of paper SPE 110738, "Enhanced Heavy-Oil Recovery by Alkali/Surfactant Flooding," by J. Bryan, SPE, and A. Kantzas, SPE, University of Calgary and TIPM Laboratory, prepared for the 2007 SPE Annual Technical Conference and Exhibition, Anaheim, California, 11–14 November. The paper has not been peer reviewed. This study presents the results of laboratory core studies investigating the recovery mechanisms of alkali/surfactant (A/S) flooding in heavy-oil reservoirs. Specifically, mixtures of water and A/S systems have been injected into cores containing heavy oil. Salinity is varied to generate oil-in-water (O/W) vs. water-in-oil (W/O) emulsion systems, and the effects of generating different emulsions were compared. It was demonstrated that in heavy-oil systems, emulsion formation was necessary to produce the heavy oil. Introduction Several countries, including Canada and Venezuela, contain massive resources of unconventional heavy oil and bitumen. These oil sands are characterized as unconsolidated, high-porosity, and high-permeability reservoirs. The single biggest obstacle to successful recovery from the oil sands is the high oil viscosity. Heavy-oil reservoirs are a special subset of the oil sands, whereby the oil viscosity at reservoir temperature and pressure varies on the order of 50 to 50 000 mPa·s. While this oil is very viscous, it does have limited mobility at reservoir conditions. As much as 20% of the oil may be recovered by solution-gas drive, but in many cases, the recovery is much lower. To recover additional heavy oil, a fluid usually must be injected to displace oil to the production wells. However, mobility-ratio concerns dominate displacement of viscous oil, and most enhanced-oil-recovery processes focus on reducing oil viscosity or improving the mobility ratio. Unfortunately, many of the heavy-oil reservoirs in Canada are relatively small and thin, making them poor candidates for expensive thermal processes. This work investigates the potential of A/S flooding for enhanced heavy-oil recovery. Surfactants are a special class of molecule that is both hydrophobic and hydrophilic; thus, the most stable configuration for these molecules is at the oil/water interface. In surfactant flooding, these molecules generally are injected along with water to reduce the oil/water interfacial tension (IFT), which reduces capillary forces that may trap oil in rock pores. Alkali flooding is a special subset of chemical flooding whereby the surfactant is generated in situ through the reaction between the injected alkali and the acidic crude oil. It is likely that in actual reservoir applications, several processes are working together to improve oil recovery. This work considers the possible mechanisms that could be responsible for enhanced recovery of high-viscosity heavy oil.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.205
Teacher spread0.198 · 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