Size Degradation of Granular Lost Circulation Materials
Bibliographic record
Abstract
Abstract Lost circulation is a major cause of drilling non-productive time with significant cost implications for many locations throughout the world. Increased attention on the performance of lost circulation materials and engineered solutions to lost circulation, such as wellbore strengthening and the recycling lost circulation materials, has brought about the need to use materials which do not size-degrade rapidly. Little mechanical property data or shear degradation information is available for most lost circulation materials as they are normally not highly engineered materials, and standard test methods have not been developed. In addition, lost circulation materials are often sourced locally to reduce cost, and logistics are such that they may not come from sources with consistent quality. Anecdotal information about which materials size-degrade most is common in the industry but little scientific information is available. Field data has conclusively shown that lost circulation materials degrade in size with time. A laboratory procedure has been developed and used to study the relative reduction in particle size of the most common granular products. Laboratory and field data are presented to demonstrate the relative size degradation rates for several common lost circulation materials. This data on the relative degradation in the particle size distribution of granular lost circulation materials will provide improved understanding of their performance for more efficient application of the materials. This will lead to improvements in wellbore strengthening and lost circulation material recycling applications.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".