External corrosion of oil and gas pipelines: A review of failure mechanisms and predictive preventions

Journal of Natural Gas Science and Engineering, Journal Year: 2022, Volume and Issue: 100, P. 104467 - 104467

Published: Feb. 9, 2022

Language: Английский

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A Review of Distributed Fiber–Optic Sensing in the Oil and Gas Industry

Journal of Lightwave Technology, Journal Year: 2021, Volume and Issue: 40(5), P. 1407 - 1431

Published: Dec. 15, 2021

Fiber–optic sensors have been widely deployed in various applications, and their use has gradually increased since the 1980 s. Distributed fiber–optic sensors, which enable continuous real–time measurements along entire length of an optical fiber cable, undergone significant improvements underlying industries. In oil gas industry, distributed can provide significantly valuable information throughout life cycle a well monitor pipelines transporting hydrocarbons over great distances. Here, we review deployment Rayleigh–based acoustic sensing (DAS), Raman–based temperature (DTS), Brillouin–based strain (DTSS) industry. particular, describe operation principle basic experimental setups DAS, DTS, DTSS, highlighting applications upstream, midstream, downstream sectors We further developed prototype hybrid DAS–DTS system that simultaneously measures vibration multimode (MMF). The reported was tested operational well. This work also discusses challenges might hinder growth market petroleum point out future directions related research.

Language: Английский

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Evaluation of deep learning approaches for oil & gas pipeline leak detection using wireless sensor networks

Engineering Applications of Artificial Intelligence, Journal Year: 2022, Volume and Issue: 113, P. 104890 - 104890

Published: May 9, 2022

Language: Английский

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Modeling and analysis of internal corrosion induced failure of oil and gas pipelines

Reliability Engineering & System Safety, Journal Year: 2023, Volume and Issue: 234, P. 109170 - 109170

Published: Feb. 13, 2023

Language: Английский

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Review of Prediction of Stress Corrosion Cracking in Gas Pipelines Using Machine Learning

Machines, Journal Year: 2024, Volume and Issue: 12(1), P. 42 - 42

Published: Jan. 8, 2024

Pipeline integrity and safety depend on the detection prediction of stress corrosion cracking (SCC) other defects. In oil gas pipeline systems, a variety corrosion-monitoring techniques are used. The observed data exhibit characteristics nonlinearity, multidimensionality, noise. Hence, data-driven modeling have been widely utilized. To accomplish intelligent enhance control, machine learning (ML)-based approaches developed. Some published papers related to SCC discussed ML their applications, but none works has shown real ability detect or predict in energy pipelines, though fewer researchers tested models prove them under controlled environments laboratories, which is completely different from work field. Looking at current research status, authors believe that there need explore best technologies identify clear gaps; critical review is, therefore, required. objective this study assess status learning’s applications detection, gaps, indicate future directions scientific application point view. This will highlight limitations challenges employing for also discuss importance incorporating domain knowledge expert inputs accuracy reliability predictions. Finally, framework proposed demonstrate process condition assessments pipelines.

Language: Английский

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Resilience assessment of a subsea pipeline using dynamic Bayesian network

Journal of Pipeline Science and Engineering, Journal Year: 2022, Volume and Issue: 2(2), P. 100053 - 100053

Published: March 22, 2022

Microbiologically influenced corrosion (MIC) is a serious concern and plays significant role in the marine subsea industry's infrastructure failure. A probabilistic methodology introduced present study to assess system's resilience under MIC. Conventionally, risk-based models are constructed using characteristic features. This helps decision-makers understand how system operates failed can be recovered. The needs designed with sufficient maintain performance time-varying interdependent stochastic conditions. paper presents dynamic Bayesian network-based approach model as function of time. An industry-based application pipeline studied demonstrate efficiency effectiveness proposed for assessment. will assist considering design operation.

Language: Английский

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Risk analysis on corrosion of submarine oil and gas pipelines based on hybrid Bayesian network

Ocean Engineering, Journal Year: 2022, Volume and Issue: 260, P. 111957 - 111957

Published: Aug. 4, 2022

Language: Английский

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Recurrent neural network-based model for estimating the life condition of a dry gas pipeline

Process Safety and Environmental Protection, Journal Year: 2022, Volume and Issue: 164, P. 639 - 650

Published: June 24, 2022

Language: Английский

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Failure probability estimation of natural gas pipelines due to hydrogen embrittlement using an improved fuzzy fault tree approach

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 448, P. 141601 - 141601

Published: March 5, 2024

Language: Английский

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Structural health monitoring of oil and gas pipelines: Developments, applications and future directions

Ocean Engineering, Journal Year: 2024, Volume and Issue: 308, P. 118293 - 118293

Published: June 5, 2024

Language: Английский

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