Reducing oil and gas well leakage: a review of leakage drivers, methane detection and repair options
Bibliographic record
Abstract
Abstract Oil and gas wells (OGWs) with integrity failures can be a conduit for methane and contaminant leakage to groundwater aquifers, surface water bodies and the atmosphere. While there have been numerous reviews addressing OGW leakage, there is a gap in the literature regarding an examination of OGW leakage that encompasses both abandoned and active wells, as well as factors that impact leakage, methane emission measurements, and options for repairing leaks. Here, we review the literature to evaluate factors and policies affecting leakage of active and abandoned OGWs, studies quantifying OGW methane emissions, and leakage repair and emission reduction options. Furthermore, our review places a greater emphasis on abandoned oil and gas wells and does not focus on one well type, such as unconventional wells. Of the 38 factors in published literature reviewed here, studies find that 15 (39%) factors, including geographic location, well deviation, casing quality and plugging status consistently affect OGW leakage. For 15 (39%) factors, including surface casing depth, well elevation and land cover, one or two studies show that they do not affect OGW leakage. For the remaining eight (21%) factors, including well age, studies show conflicting results. Although increased frequency of well monitoring and repair can lead to reduced OGW leakage, several studies indicate that monitoring and repair requirements are not always enforced. Moreover, we find 13 studies quantifying OGW methane emissions to the atmosphere at the oil and gas wellhead scale across Canada and the United States with major gaps in the geographical distribution of the collected data. Moreover, although studies measuring abandoned wells include measurements from orphaned wells, available measurements do not differentiate between orphaned and abandoned OGWs, which is important for policy makers aiming to quantify methane emission reductions of plugging hundreds of thousands of orphaned wells. To repair OGW leakage, we find that most studies focus on well cement and casing repair. There are alternatives to cement and casing repair that only reduce methane emissions, such as soil methane oxidation, but their widespread applicability requires further study. Overall, our review of factors affecting OGW leakage can be used to identify OGWs with high leakage potential and guide OGW leakage monitoring and repair policies, thereby reducing climate and environmental impacts.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".