The Western Canada Sedimentary Basin energy wells: δ13C gas isotopic mapping, from production to ground migration
Bibliographic record
Abstract
Despite the emerging new technology in renewables, society still relies overwhelmingly on fossil fuels for energy. Overall, data indicate that there is an increase in natural gas production as a less expensive, more “environmentally friendly” and efficient resource. ẟ13C studies are a standard tool to understand the origin, migration and mixing of natural gases. In the Western Canada Sedimentary Basin (WCSB), which is a major hydrocarbon producer, the isotopic variability of formations gases have been well characterized (i.e., Tilley and Muehlenbachs, 2006). Industry implements such information for predicting where economically substantial amounts of natural gas form. Ethane isotopic fingerprinting is more diagnostic of such thermally matured gases. Thus, it is a useful tool to identify unwanted fugitive gas emissions associated with petroleum resource development and activities. In an initiative to better understand, constrain and ultimately mitigate this historic engineering challenge, we contoured the isotopic values of 2800 SCV wells and 1200 GM, and used the production data to identify the source of gas emissions. Our outcomes are not only valuable to industry, but also to regulatory agencies to increase awareness about the use of organic (e.g. n-alkanes) and inorganic (e.g. CO2) carbon isotope fingerprinting as retrospective environmental indicators at a local and regional scale. Reference: Tilley, B., and Muehlenbachs, K. (2006). Gas maturity and alteration systematics across the Western Canada Sedimentary Basin from four mud gas isotope depth profiles. Organic Geochemistry, 37(12), 1857–1868.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".