Experiment and FEM Modelling of Stress Shadow Effect in Multi-Stage Hydraulic Fracturing to Optimize the Stimulation
Bibliographic record
Abstract
Abstract The stress shadow effect is well observed in the field operations of multi-stage hydraulic fracturing and it can greatly influence the fracturing effect. In the research documented here, lab experiments were made with the artificial gelatin blocks to visually examine the stress shadow effect during multi-stage hydraulic fracturing process. A related finite element modelling was conducted to understand the changes of the stress distribution after a first-stage hydraulic fracture evolved. The results of the visual fracturing experiments and finite element modelling (FEM) were consistent, which illustrated that a later-stage hydraulic fracture that follows an previous-stage hydraulic fracture may have its orientation and fracturing pressure altered from that of the previous one due to the altered stress distribution in the formation nearby. The experiment observations clearly showed the process of a first-stage hydraulic fracture generated obliquely at the very beginning due to near-wellbore effect and then turned to extend more and more perpendicularly to the direction of the minimum principal stress. After this first-stage fracturing done, a second-stage fracturing started but the fracture evolved towards a different direction that is nearly orthogonal to the first-stage fracture. According to the related FEM modelling, the main stress shadow affected region was within a range that depends on the injection pressure and the principal stresses difference in the formation nearby. If the later-stage hydraulic fracturing is done beyond this range, the fracture will have a similar orientation and fracturing pressure to the previous one. A suitable spacing between each stage as well as the injection pressure should be well designed to optimize the stimulation.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.000 | 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.
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 teacher head, 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".