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Record W2946240772 · doi:10.3390/catal9050431

Partial Upgrading of Athabasca Bitumen Using Thermal Cracking

2019· article· en· W2946240772 on OpenAlexaff
Thomas Kaminski, Maen M. Husein

Bibliographic record

VenueCatalysts · 2019
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCokeAsphaltCrackingWaste managementAPI gravityDiluentFluid catalytic crackingMaterials scienceYield (engineering)ViscosityChemistryMetallurgyPulp and paper industryPetroleumComposite materialOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

The current industry practice is to mix bitumen with a diluent in order to reduce its viscosity before it can be pumped to refineries and upgraders. The recovery of the diluent and its recycling to the producers, on the other hand, pose major environmental and economic concerns. Hence, onsite partial upgrading of the extracted bitumen to pipeline specifications presents an attractive alternative. In this work, thermal cracking of Athabasca bitumen was carried out in an autoclave at 400 °C, 420 °C and 440 °C in presence and absence of drill cuttings catalyst. At 400 °C, despite no coke formation, the reduction in viscosity was insufficient, whereas at 440 °C, the coke yield was significant, ~20 wt.%. A balance between yield and viscosity was found at 420 °C, with 88 ± 5 wt.% liquid, ~5 wt.% coke and a liquid viscosity and °API gravity of 60 ± 20 cSt and 23 ± 3, respectively. Additionally, the sulfur content and the Conradson carbon residue were reduced by 25% and 10%, respectively. The catalytic thermal cracking at 420 °C further improved the quality of the liquid product to 40 ± 6 cSt and 25 ± 2 °API gravity, however at slightly lower liquid yield of 86 ± 6 wt.%. Both catalytic and non-catalytic cracking provide a stable liquid product, which by far exceeds pipeline standards. Although small relative to the energy required for upgrading in general, the pumping energy requirement for the partially upgraded bitumen was 3 times lower than that for diluted bitumen. Lastly, a 5-lump, 6-reaction, kinetic model developed earlier by our group successfully predicted the conversion of the bitumen to the different cuts.

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 score0.047
Threshold uncertainty score0.466

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 head0.015
GPT teacher head0.252
Teacher spread0.238 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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