PIPE CONDITION PREDICTION MODELS FOR OIL AND GAS PIPELINES USING ARTIFICIAL NEURAL NETWORKS
Pipelines are like a lifeline that is vital to a nation's economic sustainability; as such, pipelines need to be monitored to optimize their performance as well as reduce the product losses incurred in the transportation of petroleum chemicals. A significant number of pipes would be underground...
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| Format: | Thesis |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | http://utpedia.utp.edu.my/id/eprint/24698/1/Nagoor%20Basha%20Shaik%20%2816000473%29.pdf http://utpedia.utp.edu.my/id/eprint/24698/ |
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| Summary: | Pipelines are like a lifeline that is vital to a nation's economic sustainability; as such, pipelines need to be monitored to optimize their performance as well as reduce the product losses incurred in the transportation of petroleum chemicals. A significant number of pipes would be underground; it is of immediate concern to identify and analyze the level of corrosion and assess the quality of a pipe. The condition of these pipelines is unpredictable and is interconnected with time by different parameters. The task of determining under which conditions the most appropriate repair or replacement initiatives are continually being faced by pipeline operators. Also, oil and gas producers have always placed their equipment as the highest priority for operations, but unfortunately, a study shows that many failures in the facility associated with piping systems lead to billions loss. |
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