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Record W1995545556 · doi:10.1080/15567036.2010.492380

A Laboratory Study for Assessing Microbial Enhanced Oil Recovery

2013· article· en· W1995545556 on OpenAlexaff
Mutai Bao, Tieqiao Liu, Z. Chen, Lin Guo, Guancheng Jiang, Y. Li, Xinhai Li

Bibliographic record

VenueEnergy Sources Part A Recovery Utilization and Environmental Effects · 2013
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsConcordia University
Fundersnot available
KeywordsMicrobial enhanced oil recoveryResidual oilMicroorganismEnhanced oil recoveryEnvironmental sciencePetroleum engineeringRecovery ratePulp and paper industryChemistryChromatographyGeologyBacteriaEngineering

Abstract

fetched live from OpenAlex

Microbial enhanced oil recovery utilizes microorganisms and their metabolic products to improve the oil recovery. A pilot scale study was conducted to investigate the effectiveness of two microorganisms (D-2 and M-1), presenting as an individual and a mixture, by recovering residual oil from a sandstone core oil reservoir at Shengli Oil Reservoir, China. Five microbial flooding tests were conducted sequentially by injecting microbial cultures into the experimental reservoir. The results showed that a polymer surfactant produced by D-2, M-1, and their mixture, enhanced oil recovery by 5.4, 5.6, and 7.9%, respectively, which are within the reported ranges of increased tertiary oil recovery.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.006
GPT teacher head0.204
Teacher spread0.197 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2013
Admission routes1
Has abstractyes

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