Mitigating in Situ Oil Sands Carbon Costs
Bibliographic record
Abstract
Abstract You've heard the direction, you've seen the papers, and you've read the publications. The Government of Canada's March 2008 "Turning The Corner - Taking Action to Fight Climate Change" report has set the foundation for CO2 regulations which "start tough and get tougher". The "Toughest" requirements are set for new oil sands plants and coal-fired power plants that come into operation in 2012, or later. The public and legal arena is also impacted by how oil sands carbon emissions are addressed. The Report on Business, March 6, 2008, reported; "a federal court judge … found the approval of Imperial Oil Ltd's $8 billion oil sands mine insufficient on climate change and green house gas emissions." The Conference Board of Canada Carbon Disclosure Project Report 2007 has also stated that "Alberta's GHG reduction legislation will add approximately $0.18/bbl in additional operating costs for a typical integrated oil-sands mining project, and $0.22/bbl for a steam-assisted gravity drainage project." These and other factors have changed the landscape for oil sands development. A review of the political, social, and regulatory pressures and obligations for the in situ oil sands industry to reduce its oil sands carbon foot print will be provided. This paper will discuss Laricina's insights and views on the carbon challenge, describe initiatives Laricina is taking to manage these imperatives and outline the challenges the overall industry is facing. The objective of this paper is to spur dialogue and collaboration by the oil sands industry in an effort to evolve and advance the knowledge and understanding of the impacts this important issue has on our business. This paper will also attempt to describe the dimensions of the carbon problem, point out the experience base our industry has to contribute to a solution, review the parameters to demonstrate CO2 or GHG's containment and storage, touch on the state of regulatory and policy issues, and try to scope out a progression to technical and economic success.
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 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 | 0.000 |
| 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) | 0.000 | 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".