Influence of Increasing Mean Stress on Fatigue Properties of Shale during Pulsating Hydraulic Fracturing
Bibliographic record
Abstract
During pulsating hydraulic fracturing (PHF), reservoir rock can be subjected to constant amplitude, constant mean stress (CACMS) cyclic loading or constant amplitude, increasing mean stress (CAIMS) cyclic loading. The influence of increasing mean stress on rock fatigue strength, fatigue lifetime, fatigue damage, and energy evolution of shale is rarely investigated, and which type of cyclic loading is more efficient for PHF has not been determined and demonstrated. In this Article, a series of uniaxial compression tests under these two types of cyclic loading are first conducted. A fatigue lifetime model for CAIMS is established. The shale strength and fatigue lifetime for CACMS and CAIMS are then compared. Their differences are explained by their dissipated energy density evolution and damage evolution. Finally, a nonlinear damage accumulation model to predict damage evolution for CAIMS cyclic loading is proposed. It is suggested that CAIMS is a better cyclic loading type when its amplitude is higher than 30% UCS (uniaxial compressive strength) of rock. This provides a meaningful amplitude threshold for CAIMS parameter optimization in the PHF construction. In this case, compared with CACMS cyclic loading, CAIMS cyclic loading significantly decreases the shale strength by up to 20% UCS and the fatigue lifetime from over 500 to 9. Different from an inverted-S-shaped damage evolution for CACMS cyclic loading, damage evolution for CAIMS cyclic loading exhibits a monotonic increasing trend. The damage variable growth rates of CACMS and CAIMS both show a three-stage trend: (1) their growth rates both decrease; (2) the growth rate for CACMS remains stable, while for CAIMS its growth rate slowly increases; and (3) their growth rates both increase sharply. Correspondingly, the dissipated energy density evolutions for CACMS and CAIMS show a similar three-stage trend. It can be concluded that during the second stage, for CAIMS microfractures and plastic deformation inside specimens are developed and accumulated more and faster than those for CACMS cyclic loading. This explains the phenomenon that the fatigue lifetime and strength of CAIMS cyclic loading are less than those of CACMS. The nonlinear damage accumulation model proposed in this Article can well fit experimental results. This model can be used for accurately describing reservoir rock mechanical property degradation during hydraulic fracture simulation induced by PHF.
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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".