Methane and hydrogen sulfide emissions and environmental impacts of oil and gas wells: Field measurements and data analysis
Bibliographic record
Abstract
Oil and gas wells (OGWs) around the world can leak methane (CH4), a potent greenhouse gas, and hydrogen sulfide (H2S), a highly toxic gas. OGW leakage can contaminate groundwater resources and/or cause emissions. Measurements of OGW emissions at the surface have been used to test for and understand OGW leakage; however, measurements have been limited. Therefore, we reviewed literature to identify factors linked to OGW leakage and conducted field measurements to better understand OGW leakage and the associated CH4 and H2S emissions and environmental impacts. First, focusing on Canada and the US, we reviewed published literature to evaluate factors affecting leakage of active (producing) and abandoned (non-producing) OGWs, studies quantifying OGW CH4 emissions, and leakage repair and emission reduction options. Thirty-eight (38) factors were reviewed, of which 15 (39%) were found to have a consistent impact on OGW leakage, including geographic location and plugging status. In terms of CH4 emissions from OGWs, we identified major gaps in the geographical distribution of well scale measurements that can be used to study factors affecting leakage. We found that only 13 studies in two provinces and nine states quantified these emissions at the well scale. This shows the need for additional measurements given the high influence geography has on OGW leakage.Then we conducted direct measurements of CH4 and H2S emissions from 63 gas wells in Ontario, Canada, a historical oil and gas-producing region that has been understudied. We found that CH4 emission rates varied by well status, where unplugged wells emitted the most CH4 at an average rate of 10,100 mg CH4/hour/well, in line with the 10,000 mg CH4/hour/well used in Canada’s greenhouse gas inventory. Importantly, we found that CH4 emissions from abandoned plugged wells are underestimated by a factor of 920 in Canada’s greenhouse gas inventory. We found positive H2S emissions at 3 wells and discovered that H2S emitting wells are high CH4 emitters. H2S emissions, not included in the Canadian Air Pollutant Emissions Inventory, averaged 160 mg H2S/hour/well. The H2S emitting wells have led to emissions exceeding safety levels, resulting in evacuations of nearby residents in 2017 in Norfolk county, Ontario. We then developed a more comprehensive approach to evaluate the interrelated environmental impacts of OGW leakage. We conducted well and soil emission rate measurements from wells in Ontario and Quebec, mapped OGWs in urban and built-up areas and estimated CH4 and H2S emissions from an OGW-linked explosion in Ontario. We investigated the variation in soil emission rates in proximity to OGWs, considering both soil and meteorological parameters and distance to the well. We identified 7,264 and 161 OGWs that pose an increased explosion risks in Ontario and Quebec, respectively. For the Ontario explosion, we estimated average CH4 emissions of 10.5 kg/hour and H2S emissions 4 times larger than the largest published H2S emission rate from an abandoned well. In Quebec, well CH4 emissions were lower on average, ranging from -16 to 205 mg CH4/hour/well. For soil emissions, we found that they average 90 mg CH4/hour/well in Ontario and are influenced by distance from the well and soil and meteorological parameters. In our last study, looking across Canada, we conducted measurements of H2S emissions from abandoned oil and gas wells (AOGWs) and identified national H2S occurrence trends. For Alberta, we conducted a geospatial analysis on sour well and pool H2S content, where sour wells are defined as wells with any signs of H2S on Alberta’s Sour Gas Well List. We found that H2S emissions varied by well plugging status with the possibility of plugged wells having higher emissions than unplugged ones. In Alberta we found positive H2S detections from sour and non-sour wells, as defined on Alberta’s Sour Gas Well List, and did not detect H2S from wells overlapping sour pools. Our results indicated high variability between H2S emissions and well and pool H2S content, highlighting individual well measurements as key to estimating H2S emissions. Overall, this thesis presents valuable data and measurements of CH4 and H2S emissions from OGWs in Canada, with a focus on AOGWs. Through our analysis we improve our understanding of OGW leakage and factors affecting it. The inclusion of our data in greenhouse gas and air pollutant inventories allows for reductions in emission uncertainties and better representation of emissions from OGWs in Canada. Our results inform the design of effective leakage mitigation strategies such as those that target highly leaky wells and provide insight into broad environmental risks from explosions to air pollution
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".