Parent‐Child, Multilateral Well and Fracture Flow Interactions
Bibliographic record
Abstract
Advances in hydraulic fracturing that have supported resurgences in oilfield activity. High permeability conduits created in the formation have accelerated the production of oil just about everywhere. The U.S. shale sector is expected to drill about 20,000 horizontal wells in 2019. The impetus for an engineering overhaul is being forced by the prevalent well-to-well fracture interactions or frac hits. These events are the subject of intensifying study by U.S. and Canadian shale producers that have attributed them to lowering oil recovery factors from new child wells by 20-40% while inflicting even higher losses on older, yet less productive, parent wells. A rigorous, easy-to-use Darcy flow simulator that allows rapid, convenient and rigorous model for problems containing heterogeneities, general drive models, arbitrary systems of vertical, horizontal and multilateral wells, liquids and gases, is not readily available in the industry, until now. This book fills that void.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".