Third-Party Damage Monitoring: Internal Fiber Optic Installation on a Transmission Pipeline Using a Pig, a Disengagement System and a Pack-Off Hanger
Bibliographic record
Abstract
Abstract The risk associated with third-party damage to transmission pipelines in areas of urban development is high. Distributed monitoring is a modern technique that uses fiber optic cables as sensors to continuously monitor pipeline parameters such as acoustics, vibration, strain and temperature. The fiber optic system notifies the operator in real-time of ongoing events allowing decisions to be made to prevent external interference or quickly address an incident that has already occurred. Traditional methods used to install distributed monitoring systems on pipelines have limitations and are not feasible for all transmission pipelines. For instance, it can be both challenging and expensive to trench in fiber optics in developed areas and other installation techniques require the pipeline to be temporarily taken out of service. SaskEnergy Incorporated’s transmission line subsidiary, TransGas Limited partnered with a Canadian pipeline monitoring service provider to install fiber optics inside of a natural gas transmission pipeline using a pig, steel capillary tubing and a pack-off hanger. A disengagement system was incorporated to release the fiber optics after the desired monitoring distance was reached. It was decided to perform the pilot project on a newly constructed NPS 6 natural gas transmission pipeline located in Humboldt, Saskatchewan. Nitrogen was used as a medium to simulate an in-service pipeline in order to reduce the risks associated with the first attempt of the project designs. The fiber optics were inserted into steel capillary tubing and connected to a disengagement system located at the back of a pig. A pack-off hanger was used to maintain pipeline pressure during and after the installation was completed. The spool holding the steel capillary tubing was stopped once the maximum monitoring distance was reached and the differential pressure activated the disengagement system located at the back of the pig. The pig continued to the receive location and the fiber optics remained in the pipeline for continuous monitoring. The deployment was successful and the fiber optics will remain in the pipeline for a one (1) year monitoring period. The primary limitation to this pilot project was the strength of the steel capillary tubing. The steel capillary tubing’s ultimate tensile strength would have to be higher to accommodate a pipeline with a larger outside diameter, multiple bends, large changes in wall thickness or large elevation changes. In addition, the steel capillary tubing must be removed from the pipeline in order to perform pigging activities.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".