Total Acid Number Reduction of Alberta McMurray Formation SAGD Bitumen Using Mechanochemically Synthesized Petroleum Coke Hybrid Nanocomposite Catalyst
Bibliographic record
Abstract
Opportunity oils, specifically bituminous crude produced via thermal in situ Steam Assisted Gravity Drainage (SAGD), are considered low quality due to high Total Acid Number (TAN). Catalytic esterification with methanol can improve the quality of crude oil to meet pipeline specification TAN, potentially minimizing netback penalties (estimated global range of USD $1to $10 per barrel) subjected to upstream producers, while also reducing the naphthenic acid corrosivity in downstream refining and upgrading. Based on Alberta Energy Regulator (AER) datafrom 2021, approximately 1.40MM barrels per day of thermal in situ and 0.54MM barrels per day of surface mine high TAN (>1) bituminous crude oil production capacity exists in Alberta. Usingan assumed penalty of USD $2 per barrel, the economic impact of TAN on Alberta’s oil industrycould be upwards of USD $1.4B per year. A solid acid catalyst support derived from wastepetroleum coke, produced from Alberta oil sands mining delayed coking carbon rejectionupgrading, was developed, and tested. The catalyst is a unique hybrid nanocomposite materialproduced via top-down mechanochemical synthesis methodology to decorate, and activate, iron(II,III) oxide magnetite nanoparticles on petroleum coke, which is a new material with no previous reported studies in literature related to TAN reduction via esterification. Lewis acidity isintroduced via magnetite nanoparticle comminution, or fracturing, during mechanochemical high energy planetary ball milling producing an active catalyst for the esterification of highly acidic model compound distillate and SAGD produced bituminous crude from the Alberta McMurray formation. The catalyst, denoted as Fe3O4@PC, is a weak Lewis acid catalyst with a surface area of approximately 170 m2/g and total acidity of 1.80 mmol/g. The acidity of bituminous crude was reduced to below pipeline specification (TAN ?1.1) from TAN 2.25 mg KOH/g to 0.74 mg KOH/g at 200ºC, 4.8 MPa (gauge), using the developed catalyst, with methanol in a batch reactor.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".