Effect of fluid penetration on tensile failure during fracturing of an open-hole wellbore
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Bibliographic record
Abstract
It is widely accepted that a fracture can be induced at a wellbore surface when the fluid pressure overcomes the rock tensile strength. However, few models of this phenomenon account for the fluid penetration effect. A rock is a typical permeable, porous medium, and the transmission of pressure from a wellbore to the surrounding rock temporally and spatially perturbs the effective stresses. In addition, these induced stresses influence the fracture initiation pressure. To gain a better understanding of the penetration effect on the initiation pressure of a permeable formation, a comprehensive formula is presented to study the effects of the in situ stresses, rock mechanical properties, injection rate, rock permeability, fluid viscosity, fluid compressibility and wellbore size on the magnitude of the initiation pressure during fracturing of an open-hole wellbore. In this context, the penetration effect is treated as a consequence of the interaction among these parameters by using Darcy’s law of radial flow. A fully coupled analytical procedure is developed to show how the fracturing fluid infiltrates the rock around the wellbore and considerably reduces the magnitude of the initiation pressure. Moreover, the calculation results are validated by hydraulic fracturing experiments in hydrostone. An exhaustive sensitivity study is performed, indicating that the local fluid pressure induced from a seepage effect strongly influences the fracture evolution. For permeable reservoirs, a low injection rate and a low viscosity of the injected fluid have a significant impact on the fracture initiation pressure. In this case, the Hubbert and Haimson equations to predict the fracture initiation pressure are not valid. The open-hole fracture initiation pressure increases with the fracturing fluid viscosity and fluid compressibility, while it decreases as the rock permeability, injection rate and wellbore size increase.
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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 | 0.000 | 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) | 0.000 | 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 it