Developing a geomechanical model to predict breakdown pressure in a vertical borehole using failure analysis: a case study
Bibliographic record
Abstract
Breakdown is an important process in geomechanics; a very complex process in hydraulic fracturing which has been the subject of extensive research in the literature. There exist several models in the literature for predicting the breakdown pressure. In this research, the breakdown pressure for hydraulic fracturing in a vertical borehole was modeled using 2D and 3D failure analysis. In the geomechanical model constructed in this case study, elastic moduli were obtained using petrophysical data as well as data extracted from core analysis. The in-situ stress state of the reservoir was obtained by poroelastic horizontal strain model and was then validated by field data. To test the accuracy of the horizontal strain model, several models were used to obtain the minimum horizontals stress. At the end, the induced principal stresses inside the borehole were modeled by Kirch Equations. Four failure criteria, namely Mohr–Coulomb, 2D Hoek–Brown, Hubbert-Willis and 3D Mogi-Coulomb were used to obtain the breakdown pressure for the target reservoir. Based on the prediction results of these failure criteria, it was obtained that 2D Hoek–Brown, Hubbert-Willis, and 3D Mogi-Coulomb criteria resulted in seemingly unrealistic breakdown pressures with respect to the minimum horizontal stress gradient. The Mohr–Coulomb criterion produced lower breakdown pressure gradients, yet closer to the minimum horizontal stress values, even though it neglects the effect of intermediate stress.
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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".