Improving fracture initiation and potential impact on fracture coverage by implementing optimal well-planning and drilling methods for typical stress conditions in the Cooper Basin, central Australia
Why this work is in the frame
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Bibliographic record
Abstract
Drilling conditions involving high mean and deviatory stresses, and natural fractures in the Cooper Basin present challenges in drilling and introduce wellbore rugosities, leaving a damaged wellbore subject to a stress cage effect. Fracture initiations have been problematic in vertical Cooper Basin wells, exhibiting high initiation and treating pressure frac treatments, and with high stress conditions posing greater risks in non-vertical completions. While far-field fracture complexity should be simplified, the near wellbore complexity results in reduced fracture conductivity. The authors believe that present drilling practices and wellbore azimuths may be contributing to sub-optimal hydraulic fracture initiations and complexities. Present analytical modelling methodologies can derive initiation pressures for circular wellbores, but require more complex numerical models to include flaws and ellipticity to represent natural fractures and wellbore rugosities. This study compares initiation pressures and presents graphical results, comparing circular and elliptical wellbore cases with flaws. This extended abstract outlines the criteria used in these models and remarks on areas needing further research and model development. The authors also propose improved drilling techniques to achieve more stable, smoother wellbores, potentially reducing some rugosity and drilling induced fractures. By using data from recent research and other cases with complex stress environments, it is proposed that initiation pressures might be reduced by inclining wells for hydraulic fracturing treatments in a favourable alignment in the maximum horizontal stress direction (sH-Max), and implementing completion techniques that aid better fracture initiation.
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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 | 0.001 | 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 | 0.001 |
| 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