Placing Off-Bottom Cement Plugs: Effects of Domain Geometry
Bibliographic record
Abstract
Abstract Oil wells are often abandoned when they become uneconomic. Normally, several cement plugs should be placed along cased wells to seal the producing formations. Proper placement protocols, especially for off-bottom plugs, are therefore required to prevent the seepage of oil. Often, heavy cement slurry is injected into wells filled with lighter wellbore fluids, through a centralised tube. To form the cement plug successfully, the injected cement slurry should accumulate at the target zone, over wellbore fluids that typically have a lower density. Therefore, the current practices involve a major hydrodynamic challenge that can result in failing plugs. In a previous work, we had shown that injecting cement slurry in wellbore fluids can result in developing a cement finger that advects downstream the well. The finger then breaks and aids the formation of a mixed layer below the injection point. Consequently, the injected cement slurry starts accumulating to form the plug. These flow events were observed in a symmetrical flow domain. In this study, we consider different configurations of the injection process to investigate how the previously observed dynamics change. To that end, we consider different sizes and positions of the injector inside the well. We conduct numerical simulations based on representative hydrodynamic models using OpenFOAM, an open source CFD software. The preliminary results reveal broadly similar dynamics for symmetrical flow domains of different injector sizes. However, marked differences are observed when the injector is not centralized in the well. The injected fluid diverts directly into the gap between the injector and casing walls, with preference to flow through the wider gap side.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".