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Record W2022101619 · doi:10.2118/138188-ms

Effect of Oil Viscosity, Permeability and Injection Rate on Performance of Waterflooding, CO2 Flooding and WAG Process in Recovery of Heavy Oils

2010· article· en· W2022101619 on OpenAlexaffabout
Farshid Torabi, Benyamin Yadali Jamaloei, Ostap Zarivnyy, B. A. Paquin, N. J. Rumpel, Ryan R. Wilton

Bibliographic record

VenueCanadian Unconventional Resources and International Petroleum Conference · 2010
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsSaskatchewan Research Council (Canada)University of CalgaryUniversity of Regina
Fundersnot available
KeywordsPetroleum engineeringPermeability (electromagnetism)Enhanced oil recoveryEnvironmental scienceWater injection (oil production)Relative permeabilityOil viscosityDrainageViscosityGeologyMaterials scienceGeotechnical engineeringPorosityChemistryComposite material

Abstract

fetched live from OpenAlex

Abstract The economic life of a typical heavy oil reservoir under primary or secondary recovery schemes can be short lived or near their limit, with recovery factors in the range of 5–15%. Waterflooding alone has been successfully practiced in the Lloydminster area of the Western Canada for decades. Heavy oils located in thick reservoirs have benefited from the application of thermal, gravity drainage processes; however, thin, unconsolidated heavy oil reservoirs are unsuitable due to lack of drainage height. These reservoirs may benefit from immiscible CO2 or CO2-WAG processes. This paper examines the effect of oil viscosity, permeability and injection rate on the performance of heavy oil waterflooding, immiscible CO2 flooding and immiscible CO2 water-alternating-gas (WAG) processes. A series of 11 sand packfloods were conducted using 440 and 1,500 mPa·s heavy oils and sand packs with absolute permeabilities of 12 and 40 μm2. Water injection volumes for the waterfloods were 1.5 pore volumes (PVs) at rates of 0.112, 1.124, and 5.62 cc/min. For the CO2 flooding process, 4.5 PVs of gas were injected at a rate of 1 cc/min. For the WAG process, the water:CO2 slug ratios were varied from 1:1, 1:2 and 2:1. A 99.9% purity CO2 gas stream was used for all gas floods. All experiments were performed at a controlled temperature of 25°C and 345 kPa. Among the 11 sand packfloods conducted, the waterfloods consistently yielded the highest recovery factor for both heavy oils and sand packs, with 48-52% OOIP recovered and most of this recovery occurring during 0.112 cc/min. During CO2 flooding of the 440 mPa·s oil, 48.5% OOIP was produced from the 40 μm2 sand pack. From the same fluid-sand system, a 1:1 slug ratio, CO2-WAG process produced 42% OOIP. For the 1,500 mPa·s heavy oil, 1:2 and 2:1 slug ratios of CO2-WAG both produced ~25% OOIP from the 40 μm2 sand pack and a 1:1 slug ratio produced 35% OOIP from the 12 μm2 sand pack. All WAG injection schemes were compared on a 2.5 PV injected basis. These results suggest that the role of displaced fluid viscosity plays the most prominent role in the recovery of 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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score0.512

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 head0.006
GPT teacher head0.226
Teacher spread0.219 · 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 designObservational
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

Citations17
Published2010
Admission routes2
Has abstractyes

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