Drilling a Better Pair: New Technologies in SAGD Directional Drilling
Bibliographic record
Abstract
Abstract The precise placement of well pairs is one of the most crucial factors in the successful execution of a steam assisted gravity drainage (SAGD) drilling program. A SAGD drilling program includes placing the producer well relative to the reservoir boundaries, as well as accurately twinning the producer with the injector well. Delivering on these high expectations in unconsolidated formations, such as the McMurray oil sands, requires a strong focus on technological innovation. A common practice in drilling SAGD wells in northeast Alberta is to drill lateral SAGD pairs with conventional steerable mud motors and logging-while-drilling (LWD) resistivity measurements. Although this combination has delivered success, certain limitations exist in terms of wellbore quality and placement. At the Statoil Leismer Demonstration Project, several industry firsts were successfully implemented, including a combination of the newest and most cutting-edge directional, measurement, and LWD technology. The keystone of these industry firsts was the application of a soft formation modified, point-the-bit rotary steerable system (RSS), used on 20 horizontal wells. Combined with an ultra deep azimuthal resistivity sensor, the RSS provided precise geosteering along the bottom bed boundary in the producer wells, resulting in improved reservoir capture and reservoir characterization. More on-bottom time enabled more efficient drilling and significantly reduced well costs. Smooth, almost effortless liner runs reflected the lack of tortuosity in the wellbore, made possible by the rotary bottom hole assembly (BHA). Improved directional control made uniform well separation possible between lateral pairs, thereby reducing the risk of hot spots and short-circuiting during SAGD operations. The use of an even-walled power section above the RSS increased the bit RPM for improved BHA responsiveness while minimizing casing and pipe wear. Overall, the results and lessons learned from the demonstration of these new techniques provide a clear indication of the progressive future of directional drilling in SAGD.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".