An Investigation into Current Sand Control Testing Practices for Steam Assisted Gravity Drainage Production Wells
Bibliographic record
Abstract
Sand control screens (SCD) have been widely installed in wells producing bitumen from unconsolidated formations. The screens are typically designed using general rules-of-thumb. The sand retention testing (SRT) technique has gained attention from the industry for the custom design and performance assessment of SCD. However, the success of SRT experimentation highly depends on the accuracy of the experimental design and variables. This work examines the impact of the setup design, sample preparation, near-wellbore stress conditions, fluid flow rates, and brine chemistry on the testing results and, accordingly, screen design. The SRT experiments were carried out using the replicated samples from the McMurray Formation at Long Lake Field. The results were compared with the test results on the original reservoir samples presented in the literature. Subsequently, a parametric study was performed by changing one testing parameter at a test, gradually making the conditions more comparable to the actual wellbore conditions. The results indicate that the fluid flow rate is the most influential parameter on sand production, followed by the packing technique, stress magnitude, and brine salinity level. The paper presents a workflow for the sand control testing procedure for designing the SCD in the steam-assisted gravity drainage (SAGD) operations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".