Optimal Perforation Location and Limited Entry Design for Promoting Simultaneous Growth of Multiple Hydraulic Fractures
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Bibliographic record
Abstract
Abstract The objective of achieving uniform stimulation of a reservoir through hydraulic fracturing from a horizontal well typically depends upon the ability to generate a uniform array of hydraulic fractures from multiple entry points. However getting all the hydraulic fractures in an array to grow simultaneously is a challenge. The challenge apparently arises not only due to reservoir variability, but also in a substantial part due to the stress interaction among growing hydraulic fractures. This phenomenon, referred to as a stress shadowing, inhibits the growth of inner fractures and favors the growth of outer fractures in the array. Recently, we created a new hydraulic fracture simulator which simulates the growth of an array of hydraulic fractures in 10−6–10−5 of the computation time required for fully coupled 3D simulations of multiple parallel planar hydraulic fracture growth. Using a novel energetic approach to account for the coupling among the hydraulic fractures and through judicious use of asymptotic approximate solutions, the simulation enables designs reducing the negative effects of stress shadow by balancing the interaction stresses through non-uniform perforation cluster spacings. Furthermore, so-called limited entry approaches are thought to be capable of promoting greater uniformity among simultaneously growing hydraulic fractures as long as the number and diameters of the perforations in each cluster are appropriately designed. In order to enable such optimizations and designs, we add perforation loss into to the approximate, energy-based simulator. Our results show the potential of choosing the proper perforation diameter and number to double the fracture surface area generated by a given injected fluid volume though minimizing the negative effect of interaction. The usefulness of the new simulator is demonstrated by development of example limited entry designs and optimal spacings for different numbers of entry points.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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