High-Angle Gyro-While-Drilling Technology Delivers An Economical Solution To Accurate Wellbore Placement And Collision Avoidance In High-Density Multilateral Pad Drilling In The Canadian Oil Sands
Bibliographic record
Abstract
Abstract Cenovus Energy initiated an aggressive infill drilling program early in 2011 in its Pelican Lake polymer/water flood project in northeast Alberta. By mid-year, the company had drilled 52 injection and producing wells, and drilling is scheduled to continue at the same pace through year-end. Pelican Lake employs a two-phase drilling program from 18-well pads: batch-drilling the intermediate hole sections to approximately 425m MD at 70° of inclination; using follow-up rigs to drill the horizontal sections of over 2,000m in the Wabiskaw formation. Wellbore collisions in the intermediate phase and landing the wells accurately prior to horizontal drilling are critical concerns. Highly accurate gyroscopic surveying techniques are required throughout the project considering the close well spacing and congestion of existing wells. Early in 2011, the company tested a new gyro-while-drilling (GWD) system, capable of accurate performance up to 70° of inclination versus the 20° to 40° of previous models. If successful, the higher operational range would facilitate collision avoidance and accurate well placement in one operation with real-time data, potentially enhancing both the economics and the feasibility of the drilling program. Since accurate well placement was so critical—some well passes would be as close as 4 meters—the company developed a plan to evaluate the new tool: first, by surveying previously surveyed wells and comparing the results; and, second, by running back-up gyro surveys on wireline during drilling. GWD performance exceeded expectations, both in the initial tests and in the drilling operations—to the extent that the back-up surveys were eliminated, with the GWD data accepted as the definitive wellbore survey. This paper will provide the results of the initial tests and analyze GWD performance during drilling with statistics compiled from 36 wells. The savings from eliminating the back-up surveys will be presented along with other benefits and observations.
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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".