Analytical analysis of fracture conductivity for sparse distribution of proppant packs
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Bibliographic record
Abstract
Conductivity optimization is important for hydraulic fracturing due to its key roles in determining fractured well productivity. Proppant embedment is an important mechanism that could cause a remarkable reduction in fracture width and, thus, damage the fracture conductivity. In this work a new analytical model, based on contact mechanics and the Carman–Kozeny model, is developed to calculate the embedment and conductivity for the sparse distribution of proppant packs. Features and controlling factors of embedment, residual width and conductivity are analyzed. The results indicate an optimum distance between proppant packs that has the potential to maintain the maximum conductivity after proppant embedment under a sparse distribution condition. A change in the optimum distance is primarily controlled by closure pressure, the rock elastic modulus and the proppant elastic modulus. The proppant concentrations and the poroelastic effect do not influence this optimum distance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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.
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