Translation of New Experimental Test Methods for the Evaluation and Design of Shaped Charge Perforators to Field Applications
Bibliographic record
Abstract
Abstract Perforation performance evaluation has come under scrutiny in several recent publications. For most shaped charge perforators sold, performance is evaluated in cement targets, from which downhole performance is extrapolated. This method has been shown to generally over-predict downhole performance, with broad implications for perforating systems and shaped charge design, and well completion design. Advanced test methodologies are an order of magnitude more complex than the simplified cement penetration tests. This paper details a set of experimental shaped charge development programs with specific geometry and/or flow performance requirements and examples of their corresponding field performance. Tests have been performed with full simulation of single shot perforation, and simplified perforating simulations into stressed rock. Results are reported for shale, sandstone, and high permeability sandstone targets. Designs tested include both conventional and reactive shaped charges. In one example from 2008-2009, CNX completed fourteen wells using both conventional and reactive perforating systems to evaluate any impact on completion performance. Stimulation and production data have been analyzed for 81 stimulation stages. When comparing wells perforated with reactive shaped charges to conventionally perforated offsets, a reduction in breakdown pressure gradient of between 13% and 29% is observed. Subsequent treating pressures are reduced by 6% to 15%. The wells perforated with reactive shaped charges have also exhibited significantly slower productivity decline over the first nine months. In addition, near-perforation permeability has been mapped using advanced digital imaging techniques. This allows the grain structure and permeability distribution of a perforated rock target to be accurately measured as a function of radial distance away from the perforation wall and longitudinal position along the perforation tunnel. The paper describes important improvements in our understanding of perforation damage distribution, and provides techniques for use in conjunction with API RP 19B Section 2 and 4 tests to design perforating shaped charges and systems.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".