Using Ultrasonic Techniques to Accurately Examine Seal-Surface-Contact Stress in Premium Connections
Bibliographic record
Abstract
Summary One of the most important functions of a tubular connection is sealability. This is especially the case for premium connections that are commonly used in the demanding conditions of high-pressure/high-temperature (HP/HT) and thermal-well applications. Sealability, therefore, also is one of the most important criteria used during connection qualification in which the capability of the connection is verified for the characteristics of the application. During qualification tests, it has been found that breakdown in connection sealability can be traced to damage on the primary seal surface, which can eventually develop into a leak path. Ultrasonic-inspection technology can be used to provide a means to obtain nonintrusive measurements of contact stress between two mating metal surfaces separated by a thin lubricating film. While the technology has a wide scope of potential applications in this respect, the technology has been specifically developed to measure seal-surface-contact stresses inside oilfield tubular premium connections. This application of ultrasonic technology has been used numerous times during connection-qualification programs to assess the quality of the contact-stress band in premium connections. During these analyses, the technology has been able to detect seal-surface damage in premium connections. This paper will cover the basic concepts of premium connection design, along with some of the issues that can affect the sealability of premium connections. As well, this paper will include an overview of the use of ultrasonic technology as a technique to assess the contact stress along the metal-to-metal seal band of a premium connection and methods used to monitor changes in the contactstress profile induced by many installation and service loads.
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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 | 0.001 | 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".