Methane Emissions from Abandoned Oil and Gas Wells in California
Bibliographic record
Abstract
Abstract California hosts ∼124,000 abandoned and plugged (AP) oil and gas wells, ∼38,000 idle wells, and ∼63,000 active wells, whose methane (CH4) emissions remain largely unquantified at levels below ∼2 kg CH4 h–1. We sampled 121 wells using two methods: a rapid mobile plume integration method (detection ∼0.5 g CH4 h–1) and a more sensitive static flux chamber (detection ∼1 × 10–6 g CH4 h–1). We measured small but detectable methane emissions from 34 of 97 AP wells (mean emission: 0.286 g CH4 h–1). In contrast, we found emissions from 11 of 17 idle wellswhich are not currently producing (mean: 35.4 g CH4 h–1)4 of 6 active wells (mean: 189.7 g CH4 h–1), and one unplugged wellan open casing with no infrastructure present (10.9 g CH4 h–1). Our results support previous findings that emissions from plugged wells are low but are more substantial from idle wells. In addition, our smaller sample of active wells suggests that their reported emissions are consistent with previous studies and deserve further attention. Due to limited access, we could not measure wells in most major active oil and gas fields in California; therefore, we recommend additional data collection from all types of wells but especially active and idle wells.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".