Reduction potentials and abatement costs for methane emissions associated with compromised wellbore sealing systems in Russian oil wells
Bibliographic record
Abstract
The growth of methane concentration in the atmosphere affects climate change (United States Environmental Protection Agency (EPA), 2021). Methane has a global warming potential over100 years that is 25 times higher than Carbon dioxide (CO2) per ton gas released (Forster & Ramaswamy, 2007). About 60% of global methane emissions are coming from human activities, including oil and gas, which contributes 33% (United Nations Economic Commission for Europe (UNECE), 2021). Methane emissions are possible across the whole supply chain of the oil and gas industry, from oil exploration to the end-user. This study focuses on the emission group in the oil upstream segment, associated with the well's failed sealingsystem. The first objective of this report is to assess the possible reduction of methaneemissions associated with failures of the well's sealing system in those cases where repair is technically feasible. The second objective is to evaluate the required costs for implementing such measures in the context of additional expenses for each produced ton of oil.Several chapters of the study introduce the reader to the term well integrity, explaining the basic principles of the well construction process and the possible causes of integrity failures.Emissions reduction estimation requires several parameters, and some are not available (e.g.,not measured), such as the share of the oil wells in Russia with integrity issues. Therefore,experts with vast experience in Russia's oil and gas industry were surveyed to fill the informational gaps and determine the required parameters.The study discovers that it is possible to reduce methane emissions associated with the well'sintegrity issues by 78 kt CH4 a year, representing 17% of the category "Oil and venting" from the oil upstream segment in Russia (462 kt CH4 per year as of 2017). Additional costs would be required to restore the integrity of wells in Russia to mitigate methane emissions estimates as 3 US$ per ton of oil produced. Well integrity restoration has a double positive implication.The positive effect on climate change by methane emissions reduction. Additionally, the oilproducers would also benefit from the integrity restoration due to the extended life of the well,and increased of oil production. Therefore, targeting oil wells' integrity to reduce methaneemissions could be quick to implement and relatively low-cost solution for methane emissionsreduction in the oil upstream segment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".