Characterizing and assessing the transport and fate of hydrocarbons in association with methanogenesis in oil sands reclamation scenarios
Bibliographic record
Abstract
Alberta hosts one of the world’s largest oil reserves in the form of oil sands. Oil sands operators are actively developing effective strategies to manage produced tailings during the bitumen extraction and reclaim impacted landscapes to meet regulatory requirements. Syncrude’s Base Mine Lake (BML) is the first full-scale commercial demonstration of water-capped tailings technology (WCTT), which sequestered tailings by constructing an engineered pit lake. The overall objectives of BML are for the lake to develop into a self-sustaining ecosystem as a part of mine closure landscape, and obtaining a certificate of reclamation. Currently, an important component of BML is understanding the biogeochemical processes associated with microbial methane production (methanogenesis), because the produced methane can potentially impact the lake development through greenhouse gas emission, oxygen consumption within the water column, and transporting organics by ebullition. This thesis focuses on assessing the chemical compositions and distributions of hydrocarbons responsible for the methane production within BML fluid tailings, as well as characterizing and assessing the environmental behaviours of petroleum hydrocarbons present in the bitumen transported by methane ebullition in BML. The results of this research indicate that n-alkanes and monoaromatics derived from diluent naphtha are primary substrates fueling methanogenesis, as they are preferentially depleted within BML fluid tailings, and their concentrations are strongly correlated with measured methane production rate. With ongoing methanogenesis, volatile hydrocarbons are transported via direct partitioning into the methane bubble, and bitumen are transported through coating onto the bubble surface. Such transported bitumen is likely derived from small to large volume bitumen mats residing at the tailings-water interface of BML, rather than dispersed bitumen within the tailings. Moreover, the non-polar fraction of the transported bitumen is shown to highly adsorb to organic phase over aqueous and gas phase, so they are highly sorbed to residual bitumen along the shoreline or nearby soils without posing significant environmental risks to the surrounding ecosystems. Overall, this research provides important insights into methanogenesis and associated hydrocarbon dynamics within oil sands reclamation sites, which will aid in the management of BML towards achieving reclamation certification, inform plans for more than 30 pit lakes proposed in the oil sands region, and can be transferred to other organic rich aquatic environments where methanogenesis is present.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".