Drilling a Better Pair: New Technologies in SAGD Directional Drilling
Bibliographic record
Abstract
Summary 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 and twinning the producer with the injector well accurately. Delivering on these high expectations in unconsolidated formations (e.g., the McMurray oil sands in Canada) 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 a demonstration project by a major oil company, several industry firsts were implemented successfully, 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 ultradeep azimuthal resistivity sensor, the RSS provided precise geosteering along the bottombed boundary in the producer wells, resulting in improved reservoir capture and characterization. More on-bottom time enabled more-efficient drilling and reduced well costs significantly. Highly smooth liner runs reflected the lack of tortuosity in the wellbore, made possible by the rotary bottomhole 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 rev/min 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 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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".