The Successful Application of Automated Managed Pressure Drilling (MPD) To Protect Caprock Integrity by Narrow Margin Drilling in SAGD wells
Bibliographic record
Abstract
Abstract The Canadian SAGD (Steam Assisted Gravity Drainage) industry continues to grow with more wells being drilled in Alberta that cannot be mined. Drilling issues addressing low reservoir pressure, tight well spacing, highly pressurized steam injection, cap rock integrity and tight drilling windows are currently some of the challenges that are being faced today. As the industry looks for a way to improve and mitigate both drilling and environmental issues, this paper presents a drilling solution on applying an automated MPD (Managed Pressure Drilling) technique proven to identify and react to the actual wellbore pressures. This can detect and control any gain and losses within liters, while still having the ability to maintain a CBHP (Constant bottom hole Pressure) while drilling through tight windows. This document demonstrates the successful application of advanced automated MPD technologies on Suncor's Dover well close to Fort McMurray, Alberta and will also elaborate on recommended operational procedures, equipment set up and to process flow diagrams along with the analyzed graphical data. The results demonstrated a successful re-drill of a producer well within an over pressured reservoir induced by steam injection, by using near water density mud weights, minimizing mud losses, preventing any steam or bitumen intrusion by monitoring return density to surface while maintaining bottom hole pressure within a narrow operating window.
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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 | 0.000 |
| 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) | 0.001 | 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".