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Record W2964925937

Enhanced Oil Recovery

2011· book· en· W2964925937 on OpenAlexaboutno aff
Darya Musharova

Bibliographic record

VenueLAP LAMBERT Academic Publishing eBooks · 2011
Typebook
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPulmonary surfactantWettingCompatibility (geochemistry)RheologyPolymerPetroleum engineeringEnhanced oil recoveryChemical engineeringAlkali metalChemistryEnvironmental scienceMaterials scienceGeologyEngineeringOrganic chemistryComposite material
DOInot available

Abstract

fetched live from OpenAlex

Alkaline Surfactant Polymer (ASP) process is a tertiary method of oil recovery that has promising results for future development. It has already been implemented in different areas of the United States such as Wyoming, west Texas, also in Canada and China. The success of this process depends on the proper combination of alkali, surfactant, and polymer and their compatibility with a reservoir. Therefore, the main objective of the proposed research is to identify chemical interactions between ASP chemicals and reservoir fluids and rock. I hypothesize that testing different alkalis, polymers and surfactants will result not only in getting different profiles of rheological properties of ASP system, but also analyzing compatibility degrees of chemicals with formation fluids and rock properties such as rock wettability, oil mobility and sweep efficiency which will be affected by the designed ASP system. In this paper the results of chemical interactions between ASP chemicals and reservoir fluids are presented and the phenomena occurred are described.

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)0.000
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: Other · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.004

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 head0.017
GPT teacher head0.219
Teacher spread0.202 · 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
GenreOther

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

Citations0
Published2011
Admission routes1
Has abstractyes

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