Urban Drilling: Best Practices for Urban Oil and Gas Wells in Alberta
Bibliographic record
Abstract
Recent urban drilling projects in Alberta have met substantial opposition from municipal governments and members of communities within close proximity to the developments. Alberta policymakers only appear to acknowledge urban drilling as a policy issue when a specific project proposal ignites fiery public debate and media coverage. High profile Alberta cases include proposals by Kaiser Exploration Ltd. in Calgary (2012) and Goldenkey Oil Inc. in Lethbridge (2014). Public promises by Alberta's provincial government to address urban drilling at the policy level have been stagnant throughout changes in premiers, energy and municipal affairs ministers, and eventually a wholesale change in government with the 2015 election victory by Alberta's New Democratic Party led by Premier Rachel Notley. This Capstone Project explores and provides a response to the following question: What are best practices for oil and gas wells in Alberta's urban context? For the purposes of this project, the term “urban municipalities” refers to municipalities with populations of 30,000 people and more. Using the geoScout computer program, data and visual representations of drilling activity near and within Alberta's 11 urban municipalities are outlined. Due to the prevalence and frequency of urban drilling in other jurisdictions, their policymakers have moved forward on related issues in more substantive ways than those in Alberta. In this project, the states of Colorado and Texas provide examples of jurisdictions where key issues associated with urban drilling have been addressed at the policy level. The Colorado Oil and Gas Task Force emphasizes the importance of collaboration among local governments, regulators, and energy companies to manage energy developments relative to urban planning. In Texas, setback distances play a significant role in urban drilling policy. However, Texas policymakers have been criticized of using setback distances as a politically-motivated, rather than empirically-designed, tool. Based on findings relative to the scope of urban drilling in Alberta, it is argued that drilling activity factors into Alberta urban municipalities to a degree that justifies provincial policy specific to oil and gas wells near and within urban municipal boundaries. After surveying the broadest landscape of literature and relevant cases, the following best practices should be employed in Alberta urban drilling policy: • Timing: Urban municipal governments receive earlier notification of project proposals. • Engagement: The application stage for proposed projects involves increased participation by urban municipal governments. • Population-based setback distances: Setback distances factor distinctions for urban municipalities into measurements based on population sizes. Through both quantitative and qualitative assessment, it is determined that there is no single, ideal model for urban drilling policy. Instead, it is concluded that a flexible approach to urban drilling policy will serve Alberta most effectively. This approach should employ the identified best practices in the following order, ranked on applicability to Alberta's urban context: 1) Engagement; 2) Timing; and 3) Population-based setback distances. The Modernized Municipal Government Act and City Charter regulation provide mechanisms to implement these best practices, and ultimately improve intergovernmental and community relations over urban drilling projects. The Alberta Energy Regulator continues to control the final decision on proposed projects.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.005 |
| 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".