Study on Matching Ability Between Cement Particle Size and Permeability in the Process of Oil Reservoir Plugging
Bibliographic record
Abstract
In order to satisfy the plugging demands of injecting the cement plugging agent into reservoirs with different radial depths, the technical studies of cement particle size optimization should be conducted. Through indoor experiment, the relationship between cement particle size and permeability was investigated by both macroscopic and microcosmic analysis. It is observed that the reservoirs which permeabilities are within 50~200mD are matching well with the cement agents which particle sizes are less than 5μm. And the permeabilities within 200~400mD are matching well with the cement agents which particle sizes are within 5~10μm, the permeabilities within 400~700mD are matching well with the cement agents which particle sizes are within 10~20μm, the permeabilities are above 700mD are matching well with the cement agents which particle sizes are more than 20μm. The plugging success rates of all the matching experiments are exceeding 90%. This research result is important to direct the plugging operation in the field. Key words : Plugging off and channeling prevention; Cement particle size; Permeability; Matching relationship; Experimental study
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".