Application of Intelligent-Well Technology to an SAGD Producer: Firebag Field Trial
Bibliographic record
Abstract
This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 170153, “Application of Intelligent-Well Technology to an SAGD Producer: Firebag Field Trial,” by Richard M. Stahl and Jennifer D. Smith, Suncor Energy; Scott Hobbs, Halliburton; and Colin M. Clarke, Baker Hughes, prepared for the 2014 SPE Heavy Oil Conference—Canada, Calgary, 10–12 June. The paper has not been peer reviewed. An even temperature conformance along the length of the horizontal well is key in maximizing steam-assisted- gravity-drainage (SAGD) production rates. When temperature logs are run in SAGD producers, temperature variations of greater than 50°C between the hottest and coldest spots are commonly observed. The authors theorize that this temperature distribution is related to an inflow distribution and that production rates could be improved if this temperature variance was narrowed. Introduction The Firebag project in northeastern Alberta uses SAGD to recover bitumen from the McMurray formation. SAGD uses stacked horizontal-well pairs, with the top well (injector) located 4 to 6 m above the bottom well (producer). Steam is injected into the top well, warming the bitumen and decreasing its viscosity to a point at which it will flow by gravity to the bottom well. The bottom well typically uses artificial lift to draw fluid into the wellbore and push it up to the surface facilities. Firebag production wells are designed to promote even temperature conformance to maximize bitumen-production rates. The standard Firebag mechanical-lift design is shown in Fig. 1. Temperature conformance is measured by fiber-optic temperature logging while the production well is shut down for an electrical-submersible-pump (ESP) change. A temperature survey was performed on a typical well, indicating that the coolest temperature (150°C) is located near the heel of the well (approximately 700 m) with a maximum value of 210°C near the midpoint of the well (approximately 1050 m). Field history at Firebag suggests that well conformance and bitumen-production rates could be improved through well design.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".