Tight Cardium Multi-Stage Fractured Horizontal Oil Well Performance Study Focusing on the Effectiveness of Various Fracture Fluid Systems
Bibliographic record
Abstract
Abstract In recent years, the tight Cardium sandstones of west central Alberta have seen significant new development with the application of multi-stage fractured horizontal wells. This case study reviews the completion costs, economics and production performance of 148 horizontal oil wells completed in the Pembina Field halo areas (west and east), central Pembina, Willesden Green and Garrington Fields. Production analysis was performed on all wells using the Duong decline curve analysis technique. This technique has been successfully used on tight multi-stage fractured wells in other areas, and has proven successful at predicting long-term well performance and recoveries. Wells were chosen for comparison that were in the same geological and pressure regions, had a minimum of 2 years of production information, and were stimulated with various fracture fluid systems. In one of the analyzed areas, a definite trend was identified; it was found that wells drilled in a certain orientation performed better than wells drilled with other orientations. Completions and hydraulic fracturing costs were gathered from public sources in order to understand the cost differences between areas and types of fracture fluid systems. Using decline curves and cost information, full cycle economics were run on the ‘average’ well for each area in order to determine the Net Present Value (NPV) of each area. This case study shows there is value in optimizing fracture designs through look-back studies, and there is a need to focus on more effective fracture treatment designs in unconventional oil development.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".