Enabling Partial Upgrading in Alberta: A Review of the Regulatory Framework and Opportunities for Improvement
Bibliographic record
Abstract
Alberta’s energy resources are market-constrained. The province has the opportunity to alleviate constraints by partially upgrading its crude bitumen before shipping to refinery: partial upgrading would create new markets for Alberta oil and free up pipeline capacity for all producers by reducing the volume of diluent in the system. The Government of Alberta has taken steps to take advantage of this opportunity through enactment of the Energy Diversification Act (2018) and subsequent launch of the Alberta Partial Upgrading Program to provide fiscal support to proponents of partial upgrading. In addition to financial risk, however, proponents face regulatory risk and there is the opportunity to facilitate the proliferation of partial upgrading at scale by ensuring an enabling regulatory environment. As a new approach to oil processing, partial upgrading may not fit neatly into existing rules and regulatory processes. There is the need for a comprehensive review of the regulatory framework and how it would apply to commercial-scale partial upgrading in order to understand where gaps exist and opportunities for improving regulatory certainty may lie. Here we show several gaps and sources of uncertainty in Alberta’s regulatory framework that may hinder proliferation of partial upgrading at scale. We find that partial upgrading would likely be treated as an oil sands processing plant but the lack of formal delineation between types of processing plants creates ambiguity and inefficiencies. Other gaps and sources of uncertainty are not unique to partial upgrading projects, but are of special importance to this group due to timing, the newness of the technology, and the shifting environmental regulation context in Alberta and Canada in general. Our analysis shows that numerous immediate opportunities exist to improve regulatory certainty for proponents.
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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 | 0.016 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".