De-Risking the Reservoir for a Commercial Development of the Grosmont Bitumen Carbonates in Alberta
Bibliographic record
Abstract
Abstract Improving on initial experience in the Saleski pilot with wells drilled between 2008 and 2010, a second generation well (drilled 2012) delivers economically attractive bitumen rates at efficient steam-oil ratios. This performance de-risks the reservoir and forms a solid basis for development planning. A larger scale follow-up project will help to optimize well spacing, multiple-well operations, management of well interference, artificial lift systems, etc. Despite comparable conditions of cyclic operation, two wells located in the same reservoir perform differently. This is related to differences in drilling conditions, well completions and stimulation methods. After pioneering horizontal drilling into the Grosmont Carbonate formation, the performance of the second generation well in Saleski is significantly improved. This paper presents the performance indicators for the pilot well and discusses the key learning steps that led to the improvement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".