Mainstream Options for Heavy Oil:Part I-Cold Production
Bibliographic record
Abstract
Abstract Heavy oil production has enjoyed a resurgence as both major and junior operating companies diversify their portfolios and pursue new opportunities. The key factors for the renewed interest are:Improved profitabilityTechnological advances have improved productivityEnormous reserve sizeLow geological riskLow capital investment required for non-thermal projects In addition, immediate concerns about environmental issues such as sand disposal and gas migration appear to have been resolved to the extent that there is no immediate threat to the operating environment. The key risk factors remain oil and gas prices, land prices, and economic means of sand disposal. This paper focuses on "cold production" as one of the most attractive new technologies used to produce heavy oil in the Lloydminster area. Steam assisted gravity drainage (SAGD) will be the focus of a future paper. Introduction Western Canadian crude oil production is approximately 320,000 m3/d. Of this amount, 50﹪ is comprised of heavy crude and bitumen. While bitumen demand has been essentially flat since the mid- to late-1980s, heavy oil production has doubled from 56,000 m3/d to 112,000 m3/d in the last ten years(1). Why Heavy Oil?
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".