High Resolution Acoustic Imaging of Plug Related Casing Damage in Hydraulically Fractured Horizontal Wells
Bibliographic record
Abstract
Abstract While assessing post-hydraulic-fracture perforation growth using solid-state, high-resolution acoustic imaging tools, it was noted that plug failures were occurring at a high frequency. Though plug failures can be observed from hydraulic fracture surface pressure and flowrate data, the aggregate frequency, causes, and severity of the resulting erosional damage at plug locations was not previously well understood and highly speculative. The sub-millimetric three-dimensional imagery generated from high resolution solid-state acoustic tools significantly improved the industry's awareness of plug failure frequency, mechanisms of failure, and the resulting impact to stimulation efficiency. These acoustic tools helped to uncover the causes and explore possible solutions to failing plugs. This paper presents aggregate data encompassing casing wall loss at over 2700 plug locations and presents emerging trends that appear across the broader dataset. In addition, this paper showcases the usage of high-resolution acoustic imaging in two operator-specific case studies.
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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 | 0.002 | 0.001 |
| 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) | 0.001 | 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".