Life Cycle Greenhouse Gas Emissions of Current Oil Sands Technologies: GHOST Model Development and Illustrative Application
Bibliographic record
Abstract
A life cycle-based model, GHOST (GreenHouse gas emissions of current Oil Sands Technologies), which quantifies emissions associated with production of diluted bitumen and synthetic crude oil (SCO) is developed. GHOST has the potential to analyze a large set of process configurations, is based on confidential oil sands project operating data, and reports ranges of resulting emissions, improvements over prior studies, which primarily included a limited set of indirect activities, utilized theoretical design data, and reported point estimates. GHOST is demonstrated through application to a major oil sands process, steam-assisted gravity drainage (SAGD). The variability in potential performance of SAGD technologies results in wide ranges of "well-to-refinery entrance gate" emissions (comprising direct and indirect emissions): 18-41 g CO(2)eq/MJ SCO, 9-18 g CO(2)eq/MJ dilbit, and 13-24 g CO(2)eq/MJ synbit. The primary contributor to SAGD's emissions is the combustion of natural gas to produce process steam, making a project's steam-to-oil ratio the most critical parameter in determining GHG performance. The demonstration (a) illustrates that a broad range of technology options, operating conditions, and resulting emissions exist among current oil sands operations, even when considering a single extraction technology, and (b) provides guidance about the feasibility of lowering SAGD project emissions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".