Stress Analysis of Perforated Casing in Shale Formation using Staged Finite Element Method
Bibliographic record
Abstract
At present, collapse of perforated casing of some wells in shale formation during high-pressure fluid injection of massive hydraulic fracturing has been commonly observed. In order to accurately predict the stress state of the perforated casing during shale fracturing and identify the key factor affecting the perforated casing stress, a finite-element-method (FEM) mechanical model of perforated casing in anisotropic formation was established through staged finite element method (FEM). With this model, this study analysed the mechanism underlying the effects of injection fluid temperature, internal casing pressure, and cement properties on the stress of the perforated casing. Results show that thermal loading significantly affects the stress of perforated casing. The wellbore temperature decreases by 80 C, and the stress of perforated casing increases by 11.9 % correspondingly. The reduction in internal casing pressure and appropriate increase in cement stiffness can greatly reduce the perforated casing stress. The appropriate Young's modulus of the cement for field operations ranges from 30 GPa to 45 GPa. Variations in in-situ stress and pore pressure slightly influence the stress of perforated casing. Moreover, the stress of perforated casing decreases with increasing Young's modulus of formation. The stress of perforated casing reduces by 24 % when the anisotropy index reaches 1.2. The findings of this study can be used for the risk evaluation of the perforated casing failure during hydraulic fracturing, and also provide theoretical guidance for parameter optimization of field practices in cementing and hydraulic fracturing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".