Multivariate and geochemical analyses of brines in Devonian strata of the Western Canada Sedimentary Basin for geothermal energy development
Bibliographic record
Abstract
Geothermal favorability maps in the Western Canada Sedimentary Basin (WCSB) are focused on depth and temperature. The transfer of mass and heat by a geothermal system, however, depends on the brine's transport and thermodynamic properties, which are predominantly controlled by its solute geochemistry. As an ongoing attempt to identify, map, and model potential geothermal reservoirs in sedimentary formations in the WCSB, we collect brine samples from various databases and perform rigorous quality control to identify representative formation waters from the carbonate platforms and reefs of the Leduc and Swan Hills formations, and the sandstone of the Granite Wash and Gilwood formations. We carry out multivariate analysis on 1963 representative samples using major chemical components, i.e., sodium, potassium, calcium, magnesium, chloride, bicarbonate, sulfate, and brine's pH. Principal component and cluster analyses identify distinguishable hydrogeochemical groups and the corresponding influential constituents. We then examine the direct influence of fluid chemistry on the engineering aspects of geothermal energy development in terms of parasitic loads and geochemical risks. The high salinities and associated high densities in one of the groups generate significant parasitic loads, e.g., greater than 55% at 110 °C. The geochemical modeling in each group demonstrates the potential scaling risks of dolomite, calcite, and brucite. The geochemical approaches presented here can be applied to geothermal energy development in sedimentary basins around the world.
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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 | 0.003 |
| Science and technology studies | 0.001 | 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".