Are Preflushes Really Contributing to Mud Displacement During Primary Cementing?
Bibliographic record
Abstract
Abstract During a primary cementing operation, it is most of the time necessary to prevent direct contact between the drilling mud and the cement slurry that is to be placed in the wellbore. The reason is that these two fluids are usually incompatible. This incompatibility can manifest itself either as an accelerating effect, the drilling mud/cement mixtures having a shorter thickening time than the cement itself, which is obviously not acceptable, or as a viscosifying effect, the drilling mud/cement mixtures being more or much more viscous than any of the two uncontaminated fluids, which can be detrimental to the displacement process. To keep the drilling fluid and the cement slurry separated, low density and low viscosity fluids, that will be referred to as preflushes, are often pumped ahead of the cement slurry. Examples of such fluids are water, oil, or more advanced formulations which are usually called chemical wash. It was recognized relatively early that, to be efficient, preflushes should be in turbulent flow in the annulus for a minimum amount of time. In the early 90s the criteria for turbulence was refined by taking into account the eccentricity of the annulus on the flow regime. The objective of this paper is to illustrate what fluid displacement modeling is telling us about the efficiency of these preflushes. It will be shown that, in a number of cases, preflushes are not as effective as one would think at preventing direct contact between the drilling fluid and the cement slurry, even when industry accepted rules are used to design them. In such circumstances the cement slurry is actually displacing the drilling fluid, but there are risks associated with this situation as explained above. It is therefore suggested that preflushes should be used with more caution and replaced by weighted spacers, in particular in circumstances where good cement quality is mandatory up to the top of the cement column.
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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 | 0.001 | 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".