How the Redwater Case Makes the Orphan Well Crisis Much Worse for Alberta
Bibliographic record
Abstract
As of November 1st, many I Alberta are still waiting to hear whether the Supreme Court of Canada (SCC) will grant leave to the Alberta Energy Regulator (AER) to hear its appeal of Orphan Well Association v Grant Thornton Limited, 2017 ABCA 124 (Redwater). The Court of Appeal’s decision in Redwater has punched a hole in the AER’s program for ensuring that licensees of oil and gas wells have the capital necessary to satisfy their reclamation and abandonment obligations. The ruling effectively allows trustees in bankruptcy to disclaim worthless assets (e.g., non-producing wells where the abandonment process is not yet complete), while selling valuable assets (e.g., producing wells). Redwater grants secured creditors the best chance possible to be compensated from the bankrupt’s assets, while guaranteeing that Alberta’s oil and gas industry (and potentially taxpayers) pay the cost for the bankrupt’s reclamation and abandonment obligations. As things stand today, if Redwater is not reversed, even more wells will be orphaned, adding to the already alarming number on the books of the Orphan Well Association (OWA). This article outlines how Redwater complicates the daunting challenge facing the Alberta government and the AER to deal with the problem of orphan wells. Part II sketches the AER’s current regulatory framework for abandoning, remediating, and reclaiming wells. Part II explains how Redwater adds to the reform challenge. Part IV offers some concluding thoughts.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.011 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.010 | 0.012 |
| 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".