Modified Fracture Mechanics Approach for Hydraulic Fracturing Stress Measurements
Bibliographic record
Abstract
Hydraulic fracturing (HF) test has been widely used to determine in situ stress. The use of a conventional continuum method for this purpose has raised considerable controversies concerning field tests, particularly in the determination of the maximum horizontal principal stress under preexisting fractures. Fracture mechanics methods are very promising when considering preexisting cracks. However, most fracture mechanics methods do not include the effects of confinement on fracture parameters that depend on confining stress. In the present paper, we proposed a modified approach based on fracture mechanics for stress determination considering the relation between fracture toughness and confining stress based on the Rummel and Abou-Sayed methods. Then, we conducted true triaxial hydraulic fracturing tests under different stress ratios for granite and sandstone specimens to verify the proposed approach. The observed typical pressure-time curves indicate that in the conducted hydraulic fracturing tests, the steady fracture growth was attained. Moreover, we demonstrated that the stress ratios influence crack orientations. The horizontal maximum principal stresses determined using the modified Rummel method achieve the lowest relative error compared with other considered stress estimation approaches. This modified fracture mechanics method could be used as a potential alternative approach to obtain a considerably more precise estimation of the maximum horizontal stress in hydraulic fracturing stress determination.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".