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Record W2030403065 · doi:10.1021/ef100518r

Experimental Study on Transport of Ultra-Dispersed Catalyst Particles in Porous Media

2010· article· en· W2030403065 on OpenAlexaff
Amir Zamani, Brij Maini, Pedro Pereira‐Almao

Bibliographic record

VenueEnergy & Fuels · 2010
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCatalysisSuspension (topology)Materials sciencePorosityDeposition (geology)Chemical engineeringPorous mediumOil sandsAsphaltComposite materialChemistryGeologyOrganic chemistry

Abstract

fetched live from OpenAlex

In situ upgrading of heavy oil by catalytic hydrogenation using submicrometer sized dispersed catalysts during thermal recovery is a promising new idea to achieve an environmentally sustainable method for unlocking heavy oil and bitumen resources. This requires placement of the ultradispersed catalyst particles deep into the formation where it can accelerate the high-temperature upgrading reactions. The objective of this work was to investigate the feasibility of transporting such ultradispersed catalyst particles through porous rock formations. This paper presents the results of experiments carried out to systematically examine the propagation of ultradispersed catalyst suspensions in sand packs. These experiments involved the injection of submicrometer-sized catalyst particles suspended in oil into a sand pack and analysis of the produced fluid samples and the sand bed. The results show that it is possible to propagate the ultradispersed catalyst suspension through sand beds. However, a fraction of the catalyst particles are retained by the sand (around 14 to 18%), and much higher retention occurs in the entrance region of the bed. Particles appear to be deposited on sand surfaces by an attachment mechanism deep inside the bed, but larger particles appear to be strained by mechanical trapping near the inlet face. The deposition of particles was found to be almost irreversible in the sense that the deposited particles could not be remobilized by reverse flow of the suspending medium.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.011
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

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

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 head0.009
GPT teacher head0.233
Teacher spread0.224 · 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 teacher head, 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

Citations58
Published2010
Admission routes1
Has abstractyes

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