Design for Reliability: Purpose Driven Sand Control Methods for Cased and Perforated Wells
Bibliographic record
Abstract
Abstract The historical challenges and high failure rate of using standalone screen in cased and perforated wellbores pushed several operators to consider cased hole gravel packing or frac-packing as the completion of the choice. Despite the reliability of these options, they are more expensive than standalone screen completion. Since several developments are not designed for cased hole gravel pack or frac-pack, purpose-driven sand control methods for cased and perforated wells are recommended. This paper employs a combined physical lab testing and Computational Fluid Dynamics (CFD) for lab scale and field scale to assess the potential use of the standalone screen in completing the cased and perforated wells. The aim is to design a fit-to-purpose sand control method in cased and perforated wells and provide guidelines in perforation strategy and investigate screen and perforation characteristics. More specifically, the simultaneous effect of screen and perforation parameters, near wellbore conditions on pressure distribution and pressure drop are investigated in detail. A common mistake in completion operation is to separately focus on the design of the screen based on the reservoir sand print and design of the perforation. If sand control deemed to be required, the perforation strategy and design must go hand in hand with sand control design. Several experiments and simulation models were designed to better understand the role of perforation density, the fill-up of annular gap between the casing and screen, perforation collapse and screen plugging on pressure drop. The experiments consisted of a series of step rate tests to investigate the role of fluid rate on pressure drop and sand production. There is a critical rate in which the sand filled annular gap will fluidize and also sanding would be different for different fluid density. Both test results and CFD simulation scenarios comparatively allow to establish the relation between wellbore pressure drop with screen and perforation parameters and determine the optimized design. The results of this study highlight the workflow to optimize the standalone screen design for the application in cased and perforated completion. The proper design of standalone screen and perforation parameters allows maintaining cost-effective well productivity. Results of this work could be used for choosing the proper sand control and perforation strategy, rather than using gravel packing and frac-packing methods in cased and perforated completions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".