Potential increase in oil and gas well leakage due to earthquakes
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
Abstract Earthquakes occurring naturally or induced by human activities can damage surface and subsurface infrastructure. Oil and gas wells represent a category of subsurface infrastructure that can act as leakage pathways connecting oil and gas reservoirs, groundwater aquifers, and the atmosphere. The integrity of these wells can be compromised through a wide range of processes and contribute to groundwater contamination, greenhouse gas emissions, and air quality degradation. We estimate the increase in such subsurface leakage potential due to seismic activity through geospatial analysis of 579,378 oil and gas well and 196,315 earthquake (magnitudes greater than 1.0) locations in Oklahoma, California, and British Columbia. We perform density-based clustering analysis and point density mapping using ArcGIS . We combine the well and earthquake point density maps to identify hot spots of joint high well and earthquake densities. We find that oil and gas wells and earthquakes are clustered in space, with densities reaching ∼60 wells per km 2 and ∼40 earthquakes per km 2 in California. There are at least two hot spots where these clusters overlap in each state/province. In Oklahoma and British Columbia, the hot spots are more correlated with earthquake densities; while, in California, the hot spots are more correlated with well densities. Our findings indicate the need to investigate the role of earthquakes on wellbore leakage through additional analysis of earthquake characteristics, wellbore attributes, improved data collection, and empirical field studies for all oil and gas wells, including those that are abandoned. In particular, large scale geospatial analysis establishing the scope of the problem and empirical field studies focusing on identified hot spots are needed to understand potential environmental impacts of earthquakes, especially those induced by oil and gas activities.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.007 |
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