Comparison of water chemistry of hydraulic-fracturing flowback water from two geological locations at the Duvernay Formation, Alberta, Canada
Bibliographic record
Abstract
We analyzed and compared the water chemistry between 17 Fox Creek region samples, each from a different well, and 23 Three Hills region samples from a single well. Overall, the two regions were similar in chemical composition but showed small differences in some lower abundance dissolved elements. Additionally, we investigated changes in water chemistry of FPW over time from a single well. The majority of water quality parameters and water chemistry remained constant over the 7-month sampling time. Major ion chemistry showed increasing concentrations of Ca and Mg, and a decreasing concentration of SO4. Several trace elements also showed small trends of both increasing and decreasing concentrations over time. There was a strong correlation between Ca and Mg concentrations in both the Fox Creek region samples and Three Hills region samples, which is an indication of the mixing of formation water. However, the correlation between B and Sr was different among two region samples, which is likely due to the delayed mixing of formation water with the fracturing fluids during the flowback at different time periods of post fracturing. Likewise, Fox Creek region samples showed correlations between concentrations of Cl and Ca, Na and Ca, and Na and Mg, but these correlations were not seen in the Three Hills region samples. Geochemical modeling demonstrates that there are potential scales formed in the flowback water, but most of the minerals are still in the dissolution state in the formation. Stable isotopic analysis confirmed the mixing of injection water and the formation water.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".