Experiments on Fluid Placement in a Confined Pipe: Fluid Mechanics Analysis for Plug and Abandonment Applications
Bibliographic record
Abstract
Abstract Plug and abandonment (P&A) of oil and gas wells is an essential process to prevent the oil and gas reservoir fluids migration over time and possibly contaminating other formations and also fresh water resources. In order to plug and abandon a well, a high quality cement plug placement is required. One of the most common methods of cement plug placement is the dump bailing method. In this method, a fixed volume of cement is dumped using a bailer on a mechanical plug in the wellbore. The cement slurry occupies the wellbore and also the annular region outside the dump bailer. In the processes of cement slurry placement, an extensive range of Newtonian or non-Newtonian fluids is used to remove the in-situ fluid (drilling fluid or water) in the wellbore. Based on the large number of parameters such as the density and viscosity differences between the fluids, the geometry type (pipe, annulus, etc.), the operation conditions (velocity, geometry inclination, dumping height), various kinds of placement and mixing flows can occur, and different flow regimes (e.g. inertial, viscous) can develop. In this paper, we experimentally study the placement of a heavy fluid to replace an in-situ light fluid in an inclined closed-end pipe (representative of the dump bailing method). The two fluids are Newtonian and miscible, and they have the same viscosity. We investigate the effects of some of the flow parameters such as the dumping height, the pipe inclination, and the inflow velocity of the heavy fluid on the degree of mixing and the placement quality and efficiency. Our results show that the the most efficient displacement happens with the shortest dumping height and at lower inclination from vertical. Also, a high inflow velocity displaces the light fluid promptly with more mixing in comparison with a low inflow rate. The results can help us to develop strategies for improving the dump bailing method in the P&A of the oil and gas wells.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".