SAGD Well Pair Spacing Evaluation with Consideration of Central Processing Facility Constraints
Bibliographic record
Abstract
Abstract When developing properties using the steam assisted gravity drainage (SAGD) process, the lateral spacing between horizontal well pair spacing is extensively evaluated during well pad design to optimize resource recovery and economics. However, constraints associated with central processing facilities (CPF) are often not incorporated into the evaluation. With constrained steam supply and fluid processing capacity, the accelerated production that should accompany a reduced well pair spacing scenario may not be realized. In this paper, the economics of developing a SAGD property using 50m, 85m, 100m and 125m well pair spacing are compared within Suncor's MacKay River property. A production development planning tool is used to tie the individual well production profiles to a constrained CPF. While higher oil production rates, a cumulative steam-oil ratio (CSOR) reduction, and slight increase in oil recovery are observed at the well pad level in the 50m well pair spacing scenario, no accelerated oil production is achieved at the CPF level as steam supply and fluid processing capacities are constrained. With larger well pair spacing, the addition of more new pads on an accelerated schedule serves to maximize the CPF capacity utilization and oil production. Hence, the overall oil production at the CPF level is practically the same regardless of well pair spacing. With the areas evaluated in this study, the economics of the 85m, 100m and 125m cases are very close, with the optimum achieved at 100m well pair spacing. The 50m well pair spacing scenario produces the worst economic result as the tighter spacing case requires incremental capital for additional wells to achieve the same resource recovery. Without the accelerated production at the CPF level due to facility constraints or appreciable incremental oil recovery and CSOR reduction overall, there is no increased revenue to offset the increased capital outlay.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".