Sand Control Testing for Steam Injection Wells
Bibliographic record
Abstract
Abstract Injector wells in thermal field developments in Western Canada are usually completed by slotted liners. The purpose of liner installation is preventing sand production after a shut-in, keeping a stable wellbore, and providing an appropriate steam distribution. The objective of this paper is to quantify the role of slot width and slot density on the sanding performance of the liner in cycles of injection and shut-in in a SAGD injection well, through a series of laboratory sand control tests. A large-scale sand retention testing facility was developed and employed to conduct a series of tests on slotted liner coupons with different slot widths and densities. These tests were tailored to simulate steam injection and backflow during the shut-in. Three representative particle size distributions for the McMurray Formation were used in this study ranging from coarse to fine sand. The experimental set-up allows to measure the amount of produced sand. Since the produced sand in steam injection wells is not usually cleaned out, the acceptable threshold for sand production in the injector should be more conservative than the same for producer wells. Testing results indicate that the sand control performance of the liner is governed by the slot width and density, and formation particle size distribution. Results indicate a negligible amount of produced sand with gas backflow for a properly designed liner even at very high gas velocities. Historically, there has been little attention to the sand control design for injector wells. This work highlights the significance of slot density and slot width in the sand control performance for steam injection wells. The paper provides the basis for the proper design of an effective sand control in SAGD injectors.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".