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Record W2380549100

Research Progress Of CO_2 Flooding To Enhance The Recovery Ratio Technology

2011· article· en· W2380549100 on OpenAlexaboutno aff
Wenbo Luo

Bibliographic record

VenueInner Mongolia Petrochemical Industry · 2011
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsEnhanced oil recoveryPetroleum engineeringEngineeringOil fieldChinaFlooding (psychology)Environmental scienceCraftBusinessWaste managementPolitical scienceGeography
DOInot available

Abstract

fetched live from OpenAlex

With some oil-field development entered the later period,the water-injection development as well as three extraction technology already could not raise the recovery ratio any more,by now CO2 flooding technology to raise the crude oil recovery ratio,which obtained the widespread application in the scene. At present,this technology has already applied in US,Canada maturely.Our country is relatively late to this technology,also needs to be deeply researched to this craft.In China,with the discovery of CO2 source,this technology has been applied more and more in oil field.On investigating and studying massive literature materials in both the domestic and foreign,This article had expounded the mechanism of CO2 raising the crude oil recovery ratio,the irrigation way as well as the research present situation and the progress of CO2 driving to raise the recovery ratio.And summarized the screening standard goal reservoir which suited CO2 to drive.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.038
GPT teacher head0.325
Teacher spread0.287 · 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 designNot applicable
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

Citations1
Published2011
Admission routes1
Has abstractyes

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