Re-Fracturing and Water Flooding Western Canada Tight Oil Reservoir Horizontal Wells
Bibliographic record
Abstract
Summary Horizontal multistage fracturing technology has been used with multiple tight oil formations in the Western Canadian sedimentary basin. The paper presents and answers the following questions: How does performance vary between geological areas? How does the geological/depositional environment affect the performance? What options are available to improve ultimate recovery? The study includes the analysis of production data from fractured and re-fractured horizontal oil producers from three typical tight oil formations: Bakken, Cardium and Viking. Re-fracturing wells increased oil production significantly, with the incremental oil production ranging from 3,000 Bbl in Viking to 30,000 Bbl in Bakken. The study also includes geomodeling and water flooding simulations of three typical tight oil reservoirs: Viewfield Bakken, Pembina Cardium and Kindersley Viking. Layer constrained geostatistical modeling is employed instead of box models to accurately model the heterogeneities that exist in tight oil reservoirs. The simulation results show that with horizontal water flooding, the ultimate recovery factor for tight oil reservoirs can be significantly improved with ultimate recovery factors up to 25 to 30% compared to 10 to 15% under primary production with hydraulic fractures.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".