The Weyburn CO2 monitoring project : economic modelling of CO2 sequestration : provisional report on the Great Plains Synfuels Plant (the CO2 source)
Bibliographic record
Abstract
This report describes various aspects of the economics of a coal gasification plant. The Great Plains Synfuels Plant, N. Dakota, USA, which is the CO2 source for an enhanced oil recovery operation being conducted at the Weyburn Field in Canada. Significant factors in the economics of the plant are political support at national and regional level, government underwriting of loans and financing, tax credits favouring domestic energy production, close proximity to lignite feedstock at a stable & low price, sharing of site facilities with other power generators, a regional market for bi-products- particularly fertiliser, forging long term gas supply contracts, ability to maintain a reliable supply of syngas, successfully hedging on gas price futures against price volatility, and switching interruptible gas production to bi-product production when the market is favourable. Sales of CO2 to an oil company have only recently started, with sales of less than half the available CO2 production expected to bring in net revenue of $15-18m/annum over the next 15 years. Future success of the plant will depend on natural gas prices, development of further bi-products and the ability to sell the remaining CO2 to oil companies. The introduction of some form of carbon tax credit would also significantly enhance the plant's future viability.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".