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Record W1994746193 · doi:10.2118/01-03-05

Chemical Methods for Heavy Oil Recovery

2001· article· en· W1994746193 on OpenAlexaffabout
Sara Thomas, S.M. Farouq Ali, J.R. Scoular, B. Verkoczy

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2001
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsSaskatchewan Research Council (Canada)Peraso Technologies (Canada)
Fundersnot available
KeywordsPetroleum engineeringFlooding (psychology)Steam injectionEnvironmental scienceEnhanced oil recoveryOil fieldWaste managementGeologyEngineering

Abstract

fetched live from OpenAlex

Abstract Many mobile heavy oil reservoirs in Saskatchewan and Alberta are unsuitable forthe application of thermal recovery methods, such as steam injection, for anumber of reasons including formation thicknesses of less than 10 m. Oilrecovery from such reservoirs can be accomplished by the use of nonthermalmethods, among which chemical flooding has considerable importance. This paperdiscusses recent laboratory results using chemical flooding techniques. At thesame time, limitations of such methods, limited field experience in heavy oilformations, and possible improvements are also considered. Among the chemicalflooding methods, alkaline and surfactant flooding techniques are moreimportant, partly because the chemicals involved are less expensive, and alsomuch has been learned from past experience in laboratory and field. Thelaboratory studies discussed consisted of surfactant floods and huff n'puff oftwo Lloydminster heavy oils. The recoveries in the floods were as high as 33﹪.The other recovery method discussed involved cyclic stimulation using twosurfactants. Oil recoveries as high as 12﹪ were achieved. Though recovery wasow, such an approach can be cost-effective in special circumstances. Introduction Much of the heavy oil in Saskatchewan and Alberta is mobile under reservoirconditions to the extent that primary production and waterflooding iseconomically feasible, although the recovery factors are low, 5 to 10﹪ in mostcases. Furthermore, the formation thickness is small (85﹪ of the oil in Saskatchewan occurs in formations less than 5 m thick), so that larger spacingsare needed, which makes the application of thermal methods, notablysteamflooding, doubly unattractive. Non-thermal recovery methods, such aschemical recovery processes and immiscible carbon dioxide WAG(Water-Alternating-Gas) process can be economically viable in such reservoirs, even though the recovery factor is low. This paper discusses primarily the morepromising non-thermal chemical flooding methods, selected laboratory and fieldresults, and their limitations. Results of a few experiments involvingchemicals with hot water are also added. Principles of Oil Recovery The two important concepts involved in oil recovery are Mobility Ratio, M, andthe Capillary Number, Nc. Mobility ratio, M, is usually defined as the mobility?ing (= k/ µ, where k is effective permeability and µ is viscosity)of the displacing fluid divided by the mobility ?ed of the displacedfluid (assumed to be oil in this discussion). If M >1, the displacing fluidwill flow past much of the displaced fluid, displacing it inefficiently. Thusthe mobility ratio influences "displacement efficiency," i.e., the(microscopic) efficiency of oil displacement within the pores. For M>>1, the displacing fluid will channel past oil ganglia. This is oftencalled "viscous fingering" For maximum displacement efficiency, M should be=?1, usually denoted as a "favourable"mobility ratio. If M >1(unfavourable), then, in the absence of viscous fingering, it merely means thatmore fluid will have to be injected to attain a given residual oil saturationin the pores.

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 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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.864
Threshold uncertainty score0.744

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.268
Teacher spread0.258 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreMethods

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

Citations55
Published2001
Admission routes2
Has abstractyes

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