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Record W2773093580 · doi:10.17576/jsm-2017-4609-37

An Overview of the Present Stability and Performance of EOR-Foam

2017· article· en· W2773093580 on OpenAlexfundno aff
Mohammed Falalu Hamza, Chandra Mohan Sinnathambi, Zulkifli Merican Aljunid Merican, Hassan Soleimani, Stephen Karl D.

Bibliographic record

VenueSains Malaysiana · 2017
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
FundersUniversiti Teknologi PetronasUniversitetet i BergenDalhousie UniversityUniversity of Cambridge
KeywordsPetroleum engineeringEngineering

Abstract

fetched live from OpenAlex

Foam flooding technique, commonly known as foam assisted water alternating gas method (FAWAG) has been identified as an effective chemical enhanced oil recovery (CEOR) technique.The ability of EOR-foam to sweep oil in low permeable zones makes it important displacement fluid in the oil industry.However, extreme reservoir conditions such as temperature, pressure and salinity have detrimental effects on the stability and the overall performance of the EOR-foam.Consequently, understanding foam stability and performance under different conditions is crucial for long term oil field application.This paper discusses the current status of the EOR-foam stability, performance and challenges from laboratory studies to field application perspective.The paper also highlights the knowledge gaps which require further research for successful field application.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.035
GPT teacher head0.282
Teacher spread0.248 · 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
GenreReview

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

Citations16
Published2017
Admission routes1
Has abstractyes

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