Simulation on wellbore integrity at casing shoe during fracturing for shale gas wells
Bibliographic record
Abstract
Wellbore integrity is significant to maintain and improve the production performances of shale wells. In Duvernay Canada, casing deformation near the top of Ireton with a few natural faults and cracks is severe during multi-fracturing. It is urgent to reveal the mechanism to reduce the risk of wellbore failure. In this paper, casing deformation and micro-seismic signal at casing shoe is analysed. The maximum deformation of the casing can reach to be 44.4mm. Based on the focal mechanism, it is easy to get the formation slip displacement. Under the condition of geology and wellbore geometry, a three-dimensional stage finite element method considering the whole drilling process is established to simulate the influence of fault on casing deformation. The results indicate that cement sheath at casing shoes intend to be failure during fracturing, where the fracturing fluid will immerse into the formation of Ireton thorough the micro-annulus of cement sheath. When the pore pressure is large enough to activate the natural fault, the micro-seismic signal at the casing shoe is frequent with the magnitude up to 3. Under this condition, the faults slippage can be 55 mm, and the casing deformation will be 34.9 mm. This is consistent with the actual deformation of casing. Along easy-slip formation position, cement property and wellbore structure should be optimized to prevent fracturing fluid entering the formation. Fracturing operation should be optimized to avoid generating high-magnitude seismic signals during the fracturing process, thereby reducing the possibility of casing shear deformation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".