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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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Main Author: SHAIK, NAGOOR BASHA
Format: Thesis
Language:English
Published: 2021
Subjects:
TJ Mechanical engineering and machinery
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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id oai:utpedia.utp.edu.my:24698
record_format eprints
spelling oai:utpedia.utp.edu.my:246982023-07-18T02:08:53Z http://utpedia.utp.edu.my/id/eprint/24698/ PIPE CONDITION PREDICTION MODELS FOR OIL AND GAS PIPELINES USING ARTIFICIAL NEURAL NETWORKS SHAIK, NAGOOR BASHA TJ Mechanical engineering and machinery 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. 2021-07 Thesis NonPeerReviewed text en http://utpedia.utp.edu.my/id/eprint/24698/1/Nagoor%20Basha%20Shaik%20%2816000473%29.pdf SHAIK, NAGOOR BASHA (2021) PIPE CONDITION PREDICTION MODELS FOR OIL AND GAS PIPELINES USING ARTIFICIAL NEURAL NETWORKS. Doctoral thesis, UNSPECIFIED.
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
SHAIK, NAGOOR BASHA
PIPE CONDITION PREDICTION MODELS FOR OIL AND GAS PIPELINES USING ARTIFICIAL NEURAL NETWORKS
description 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.
format Thesis
author SHAIK, NAGOOR BASHA
author_facet SHAIK, NAGOOR BASHA
author_sort SHAIK, NAGOOR BASHA
title PIPE CONDITION PREDICTION MODELS FOR OIL AND GAS PIPELINES USING ARTIFICIAL NEURAL NETWORKS
title_short PIPE CONDITION PREDICTION MODELS FOR OIL AND GAS PIPELINES USING ARTIFICIAL NEURAL NETWORKS
title_full PIPE CONDITION PREDICTION MODELS FOR OIL AND GAS PIPELINES USING ARTIFICIAL NEURAL NETWORKS
title_fullStr PIPE CONDITION PREDICTION MODELS FOR OIL AND GAS PIPELINES USING ARTIFICIAL NEURAL NETWORKS
title_full_unstemmed PIPE CONDITION PREDICTION MODELS FOR OIL AND GAS PIPELINES USING ARTIFICIAL NEURAL NETWORKS
title_sort pipe condition prediction models for oil and gas pipelines using artificial neural networks
publishDate 2021
url http://utpedia.utp.edu.my/id/eprint/24698/1/Nagoor%20Basha%20Shaik%20%2816000473%29.pdf
http://utpedia.utp.edu.my/id/eprint/24698/
_version_ 1772814001017716736
score 13.222552

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