Experimental Correlations for the Performance and Aperture Selection of Wire-Wrapped Screens in Steam-Assisted Gravity Drainage Production Wells
Bibliographic record
Abstract
Summary Wire-wrapped screens (WWSs) are one of the most-commonly used devices by steam-assisted gravity drainage (SAGD) operators because of the capacity to control plugging and improve flow performance. WWSs offer high open-to-flow area (OFA) (6 to 18%) that allow a high release of fines, hence, less pore plugging and accumulation at the near-screen zone. Over the years, several criteria have been proposed for the selection of aperture sizes on the basis of different industrial contexts and laboratory experiments. Generally, existing aperture-sizing recommendations include only a single point of the particle-size distribution (PSD). Operators and academics rely on sand-control testing to evaluate the performance of sand-control devices (SCDs). Scaled laboratory testing provides a straightforward tool to understand the role of flow rate, flowing phases, fluid properties, stresses, and screen specifications on sand retention and flow impairment. This study employs large-scale prepacked sand-retention tests (SRTs) to experimentally assess the performance of WWSs under variable single-phase and multiphase conditions. The experimental results and parametric trends are used to formulate a set of empirical equations that describe the response of the WWS. Several PSD classes with various fines content and particle size are tested to evaluate a broad range of PSDs. Operational procedures include the coinjection of gas, brine, and oil to emulate aggressive conditions during steam-breakthrough events. The experimental investigation leads to the formulation of predictive correlations. Additional PSDs were prepared to verify the adequacy of the proposed equations. The results show that sanding modes are both flow-rate and flowing-phase dependent. Moreover, the severity or intensity of producing sand is greatly influenced by the ratio of grain size to aperture size and the ability to form stable bridges. During gas and multiphase flow, a dramatic amount of sanding was observed for wider apertures caused by high multiphase flow velocities. However, liquid stages displayed less-intense transient behaviors. Remarkably, WWSs rendered an excellent flow performance even for low-quality sands and narrow apertures. Although further and more complete testing is required, empirical correlations showed good agreement with experimental results.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".