Is Ottawa Still Evolving? API Specifications and Conductivity in 2003
Bibliographic record
Abstract
Abstract Proppant mesh size is arguably the most important characteristic for controlling and describing the quality of a particular propping material. More importantly the mesh size relates to the permeability performance of the proppant. For many years now, a series of American Petroleum Institute Recommended Practices have existed for testing the quality of the numerous proppants available. Along with testing procedures, these documents contain suggested typical proppant sizes, such as 20/40 mesh, and the size specifications they should meet both at the source and at the point of application. In addition to other size criteria, it has long been accepted that if a batch of proppant has at least 90% of its mass between the designating mesh sizes, it passes an acceptable quality control target. However, it is possible to have two samples of 20/40 proppant that are both 90% in-size but could, for example, have a two-fold difference in permeability due to differences in distribution. In this case would the median diameter be a more informative description of the proppant size? With conductivity as the final goal, does the mesh size have much relevance other than as a guide to performance? In many reservoirs, the success of a fracturing treatment often depends upon a sufficient permeability contrast between the fractured formation(s) and the proppant placed. However, other factors that influence the fracture conductivity, such as polymer damage, multiphase flow and non-Darcy effects, can greatly reduce the significance of the baseline permeability. For some reservoirs, operators consider proppant size to be extremely important to the overall success of a fracturing treatment and demand tight quality control at the wellsite. In contrast, there are reservoirs where operators can pump non-typical proppant sizes or even those that do not meet API specifications. Also, in recent years the industry has seen the introduction and acceptance of several products that are not typically sized, such as 14/30 mesh deformable proppants for flowback control and, most recently, a broad-mesh, intermediate-strength proppant. So are industry attitudes changing and becoming more open to new ways of achieving fracturing success?
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.010 |
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".