Orphaned oil and gas well stimulus—Maximizing economic and environmental benefits
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Orphaned oil and gas wells are abandoned wells for which the cost of environmental impacts usually falls on governments and the general public. Government agencies responsible for well plugging often face funding shortfalls and many orphaned wells remain unplugged. To address this and support the oil and natural gas industry, federal governments are already spending, or considering spending, billions of dollars to plug orphaned oil and gas wells. Here, we analyze oil and gas data for the United States and Canada and identify policy recommendations that can best address environmental impacts of abandoned and orphaned wells. At least 116,245 wells across 32 states and four Canadian provinces/territories are operated by companies filing for bankruptcy in the first half of 2020, which may be an indication that many wells will be orphaned in the near future. Moreover, there are 4,700,000 historic and active oil and gas wells in the United States and another 790,000 in Canada. Of these, 2,000,000 and 310,000 wells are active in the United States and Canada, respectively. Thus, three of five wells ever drilled in the United States are currently inactive (2,700,000 wells), but only one in three are plugged (1,500,000 wells). Plugging involves isolating zones containing oil, gas, and water and is the main strategy for well abandonment. If the orphaned well stimulus funding comes through, tens of thousands of wells will be plugged within a few years. Well plugging at this scale far exceeds current rates of plugging, and it is important that we work to ensure long-term environmental benefits of well abandonment to water, air, climate, ecosystems, and human health. Minimizing environmental impacts of the millions of abandoned and orphaned wells in the United States, Canada, and abroad will allow for an economically beneficial and environmentally safe transition to a carbon-neutral economy.
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.
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 | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it