Microbial Community Composition and MIC in Water Systems for Bitumen Production by SAGD
Bibliographic record
Abstract
Abstract Internal corrosion risk exists in the pipeline systems and treatment facilities supplying water from the subsurface to steam-generating facilities in Steam Assisted Gravity Drainage (SAGD) operations. The waters contain high concentrations of bicarbonate, and some sulfate, but no nitrate. Water treatment includes addition of sodium bisulfite (SBS), as an oxygen scavenger. Samples were obtained from a source well and water treatment facility upstream and downstream of the SBS injection point. The planktonic microbial community was found to change significantly through the system. Exposure of steel coupons to CO2-containing synthetic oilfield brine in the laboratory resulted in the rapid development of biofilm populations rich in methanogenic Archaea. These organisms are increasingly being recognized as agents of microbially influenced corrosion (MIC). Addition of SBS in the water treatment process promoted a microbial population able to ferment added sulfite into sulfate and sulfide or sulfur, all of which have the potential to cause further corrosion problems downstream through the action of sulfate reducing bacteria and/or through the deposition of elemental sulfur on exposed steel surfaces. The observations reported here support previous work on brackish water facilities in the same site.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".