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Record W2347032611 · doi:10.1002/cjce.22476

Reservoir impairment by asphaltenes: A critical review

2016· review· en· W2347032611 on OpenAlexaffvenue
Dmitry Eskin, Omid Mohammadzadeh, Kamran Akbarzadeh, Shawn D. Taylor, John Ratulowski

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typereview
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsSchlumberger (Canada)
Fundersnot available
KeywordsAsphaltenePrecipitationPetroleum engineeringDeposition (geology)HydrocarbonCrude oilEnvironmental scienceGeologyChemical engineeringChemistryOrganic chemistryMeteorologyEngineeringGeomorphologySediment

Abstract

fetched live from OpenAlex

Abstract Precipitation and deposition of asphaltenes and other organic substances in formation rock causes formation damage and reduces effective hydrocarbon mobility, which can result in significant production losses. The development of reliable experimental, analytical, and modelling methods improves the understanding of asphaltene‐induced formation damage and provides tools for preventing and/or controlling formation damage due to asphaltenes in oil‐bearing formations. To make further advancements in understanding asphaltene impairment, it is important to analyze the current state of technology and research in this area. In addition to analyses of known experimental data and models of reservoir impairment by asphaltenes, prospective directions of future research in this area are also suggested.

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)0.002
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.020
GPT teacher head0.275
Teacher spread0.255 · 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

Citations68
Published2016
Admission routes2
Has abstractyes

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