Kinetic energy evolution of abrasive waterjet perforation in sandstone reservoirs: Toward enhanced efficiency
Bibliographic record
Abstract
Abrasive water jet (AWJ) rock perforation, commonly used in underground engineering, involves a complex multi-scale fluid-structure interaction process. Enhancing perforation efficiency depends on improving utilization of the jet kinetic energy for rock breaking. In this study, the kinetic energy evolution during AWJ rock perforation is investigated through a combination of macroscopic perforation experiments, microscale simulations of abrasive-water impact on rock, and in-hole flow field simulations bridging the macroscopic and microscopic scales. Results reveal that sand pad formation and internal turbulence are the primary factors limiting jet energy utilization. As the jet transitions from entering to exiting the perforation, a velocity stagnation zone forms at the bottom of the hole, consisting of water and sand pads. The sand pad blocks most abrasives from directly impacting the rock, leading to substantial kinetic energy loss. Additionally, a large velocity gradient between the inflow and backflow jets induces intense turbulence, further reducing jet velocity and rock-breaking effectiveness. Increasing the hole diameter helps mitigate turbulence, while increasing hole depth exacerbates it. As jet time increases, hole depth grows significantly more than diameter, intensifying turbulence, attenuating jet velocity, and diminishing water’s contribution to rock breaking—ultimately reducing kinetic energy utilization. However, the use of reciprocating nozzles can effectively reduce jet energy losses caused by sand pads and turbulence, thereby significantly enhancing perforation efficiency. These findings provide a theoretical foundation for optimizing AWJ energy utilization in underground rock engineering.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".