Influence of Horizontal Section Sinuosity and Lateral Accuracy on Heavy Oil Cold Production from Close-Spaced Senlac/Winter Saskatchewan Wells
Bibliographic record
Abstract
Abstract Horizontal well drilling for heavy oil cold production in Western Canada was initiated in 1988, and has matured to the extent that over 550 horizontal wells have been drilled into the Cummings/Dina channel trend between Senlac and Winter, Saskatchewan. A significant fraction of the more recent wells have been drilled as infills to enhance reservoir drainage. Reviews of the performance of these wells suggest drilling accuracy in all three dimensions within the horizontal section strongly affects the performance of original wells and the ability to optimize placement of infill horizontal wells between the original wells. Horizontal trajectory control has improved significantly in the last 10 years, the latest improvement being 'inclination at the bit.' Selected wells were analyzed to determine the key factors between horizontal section sinuosity and both production rate and ultimate recovery, and the changes in the effect of these key factors over the last 10 years. Incentive and methodology for development of current flatter wells is discussed, and predictions of improved production are given. Initial spacing in many areas was nominally 75 meters, and several areas are being infill drilled to 37.5 meter spacing to increase reservoir drainage. The heels of the infill wells are placed between the toes of the original wells to avoid expected greater oil depletion and water coning at the heels of the original wells. Several recent infill wells encountered lost circulation and/or magnetic interference from offsetting original wells, indicating the locations of the original wells obtained from MWD data were not accurate. For subsequent infill wells gyros were run in the original wells, and the gyro-based original well locations disagreed with the MWD-based locations. This prompted an examination of existing drilling, MWD, gyro, and magnetic North positioning data and technology. This paper discusses the theoretical and practical aspects of drilling flatter horizontal wells, establishing the locations of existing horizontal wells, and optimum placement of infill horizontal wells between the existing wells in the Senlac/Winter, Saskatchewan pools.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".