Case Study - Evaluation of Horizontal Well Multi-stage Fracturing in the Viking Oil Formation
Bibliographic record
Abstract
Abstract The Viking formation in Western Saskatchewan and East to Central Alberta is comprised of many different oil pools. These plays have seen resurgence in activity over the last 6 years as a result of the horizontal multi-stage fracturing revolution. A wide variety of fracturing technologies have been applied, encompassing open versus cased hole, variable proppant tonnage per stage and fracture spacing along the wellbore. How does the average company make meaningful decisions as to how to stimulate their wells? There is a need to make sense of the production response of the wells given reservoir quality differences, primarily permeability variation, and the variety of fracturing technologies being applied. The paper will develop a workflow which integrates publically available production data to first identify a production rate metric. This metric can be used for production forecasting and as a basis to compare area and pool production performance. Combining this information with well ownership leads to a preliminary assessment of whether production success is due solely to the reservoir, or the drilling and completion strategy applied.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".