MétaCan
Menu
Back to cohort
Record W2772092506 · doi:10.1002/cjce.23097

Laboratory investigation of oil viscosity effect during carbonated water injection: Comparison of secondary and tertiary recovery

2017· article· en· W2772092506 on OpenAlexvenueno aff
Mohsen Bahaloo Horeh, Hamid Reza Norouzi

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsWettingViscosityEnhanced oil recoveryLight crude oilWater injection (oil production)Petroleum engineeringSwellingMaterials scienceEnvironmental scienceChemistryComposite materialGeologyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Although the effect of viscosity on oil recovery is well established, no systematic investigation has been implemented regarding the effect of oil viscosity changes on performance of carbonated water injection (CWI). In this study, the performance of CWI with different oil viscosities and rock wettability was investigated through two main series of high‐pressure core flooding experiments on both clean and aged sand. The results obtained demonstrate that the capability of carbonated water to enhance oil recovery for both secondary and tertiary flooding is significantly greater versus that for water flooding. The creation of a low resistance flow channel and low oil recovery in water flooding is compensated for by CO 2 diffusion and subsequent viscosity reduction and oil swelling in heavy and light oils. The results of the aged sand experiments showed that changing the wettability towards mixed wet caused ultimate reduction in oil recovery in each experiment, compared to the similar one in clean sand. However, it was observed that the amount of oil recovered after breakthrough compared to that in clean sand was increased, which showed the capacity of CW for enhanced oil recovery through alteration of wettability.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.350

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 head0.005
GPT teacher head0.198
Teacher spread0.193 · 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 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

Citations14
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicCO2 Sequestration and Geologic InteractionsFrench-language works237,207