Design for Reliability: Experimental and Numerical Simulation of Cased and Perforated Completions with Standalone Screen
Bibliographic record
Abstract
Summary 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 preferred completion. Despite the reliability of these options, they are more expensive than a standalone screen completion. In this paper, we employ a combined physical laboratory testing and computational fluid dynamics (CFD) for laboratory 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 is 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 effect of perforation density, the fill-up of the annular gap between the casing and screen, perforation collapse, and formation and perforation damage 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 at which the sand filling up the annular gap will fluidize. Both test results and CFD simulation scenarios are comparatively capable to establish the relation between wellbore pressure drop 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 completions. 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.
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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 | 0.000 | 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) | 0.000 | 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".