Geomechanical Considerations in Hydraulic Fracturing Designs
Bibliographic record
Abstract
Abstract The role of geomechanics in design and evaluation of hydraulic fracture stimulations in unconventional reservoirs has become more important than ever. Microcosmic mapping provides a good estimation of fracture geometry and stimulated reservoir volume (SRV); however, without geomechanical considerations, the predictions may not be completely accurate. By understanding reservoir rock mechanics and those parameters that have a major impact on the performance of fracture treatments, more reliable decisions in fracturing design and optimization can be made. This paper presents the results of an analytical model that predicts the changes in stress anisotropy in the neighborhood of the fractures of different designs in an elastic-static medium. Also, a numerical model has been used to investigate the effect of different geomechanical parameters on the geometry of the fractures. Results show that the spacing between fractures has a major impact on the changes in stresses. The effect of well spacing on fracture geometry in modified zipper frac design has been investigated. The results of this study give valuable insight into optimization of fracture placement in newly developed designs of hydraulic fractures in horizontal wellbores.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".