Hydraulic fracturing scenarios for low temperature EGS heat generation from the precambrian basement in Northern Alberta
Bibliographic record
Abstract
Previous computer simulations identified the characteristics of a fracture network that would allow sufficient heat and fluid transfer for the sustainable and economic use of geothermal heat for oil sands extraction and processing in Northern Alberta (Pathak et al., 2012). Since this type of fracture system does not occur naturally in the region, hydraulic fracturing treatments are needed. In this paper, different hydraulic fracturing scenarios are modeled with a commercial fracturing simulator to examine the dimensions of fracture systems that could be obtained artificially by conventional gel-proppant, water- or hybrid-fracture treatments. The primary objective is to evaluate different treatment approaches for these applications to the conditions existing in Northern Alberta. Additionally, a sensitivity analysis is conducted to evaluate the influence of reservoir and treatment parameters on fracture properties. Subsequent reservoir simulations show whether these fracture systems could make a sustainable and economical heat extraction possible. Overall, the integration of the results of both models leads to proposed hydraulic fracturing strategies suitable for the conditions expected in Northern Alberta.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".