Validation of Predicted Cumulative Sand and Sand Rate Against Physical-Model Test
Bibliographic record
Abstract
Summary This paper presents a numerical model to study the onset and rate of sand production and compares its predictions against physical-model testing data on Salt Wash South (SWS) sandstone. A reliable sand-prediction tool is essential in sand-production management. It enables engineers to improve well-completion design, with the aim of maximizing well productivity without compromising well integrity. A sanding test on a weakly consolidated sandstone sample was numerically simulated using a finite-difference-based numerical model. The model is based on erosional mechanics in which coupling between fluid flow and mechanical deformation captures some of the key mechanisms that are involved in sand production. Sand is assumed to be produced when the material is fully degraded and hydrodynamic forces are high enough to remove the particles. The outcome of the numerical model shows a reasonable agreement against perforation-test results in terms of the onset and rate of sand production. The model shows that sand production initiates from the perforation tip and propagates to the top and sides of the perforation cavity. The sanding rate increases at higher flow rates. Furthermore, the model predicts external deformations of the sample, which are in close agreement with the experimental observations.
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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 | 0.002 | 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) | 0.000 | 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".