Diagnosis of the single leakage in the fluid pipeline through experimental study and CFD simulation

Fu, Hao; Lu, Yang; Liang, Huirong; Wang, Sai; Ling, Kegang

doi:10.1016/j.petrol.2020.107437

Cited by 37 publications

(18 citation statements)

References 41 publications

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“…The flow parameters monitored in this method are flow rate, pressure, and other fluid flow parameters. Pipeline leak detection using transient-based leak detection approach has been extensively adopted in the research community (Araújo et al, 2013;Araújo et al, 2014;Lazhar et al, 2013;De Sousa and Romero, 2017;Fu et al, 2020;Ranawat and Nandwana, 2021), and it has been shown to be successful in detecting and locating pipeline leak position.…”

Section: Related Workmentioning

confidence: 99%

Numerical study of pipeline leak detection for gas-liquid stratified flow

Adegboye

Karnik

Fung

2021

Journal of Natural Gas Science and Engineering

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Section: Related Workmentioning

confidence: 99%

Numerical study of pipeline leak detection for gas-liquid stratified flow

Adegboye

Karnik

Fung

2021

Journal of Natural Gas Science and Engineering

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“…Fedotov et al (2021) studied the detection band of laser fluorescence sensor to detect oil pipeline leakage. Fu et al (2020) established the relationship between pressure distribution and leakage parameters through simulation and verified it through experiments. Adegboye et al (2021) systematically analyzed the effects of leak size, longitudinal leak location, multiple leaks, and axial leak locations on the pressure gradient, flow rate and volume fraction in the pipeline.…”

Section: Introductionmentioning

confidence: 95%

Leakage simulation and acoustic characteristics based on acoustic logging by ultrasonic detection

Wan

Wang

et al. 2022

Adv. Geo-Energy Res.

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The detection of casing leakage in oil and gas wells or water injection wells is an important element of wellbore integrity management. Ultrasonic technology is suitable to detect and identify the position of leakage in oil and gas well shafts, providing engineering guidance for subsequent treatment. In this paper, the finite element calculation model of casing leakage in oil and gas wells is established by using the computational fluid dynamics method, and the large eddy simulation model and Ffowcs Williams-Hawkings acoustic model are utilized to simulate the casing leakage condition. The acoustic pressure signals of each monitoring point on the inner axis of the pipeline are obtained, and the influences of the pipeline pressure difference, the leakage hole diameter and the pipeline fluid on the leakage acoustic field are analyzed. The simulation results indicate that the acoustic pressure level measured on the pipeline axis rises with the increase of pipeline pressure difference and leakage hole diameter. The size and variation rule of acoustic pressure level also vary with the type of pipeline fluid. Overall, the results obtained show that ultrasonic logging can accurately locate and detect tubing leakage, and they provide theoretical guidance for practical casing leakage detection, assisting with wellbore integrity management.

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“…Pipelines are an important isuue in this field in its structure and transporting it with safety ways in [4][5][6] alot of methods has discussed to structure the piplines with perfect way and in limited sizes with effeciency work. Transforming is the last phase after extraction oil to make it ready for use and it depends on alot of factors that affect on it such as high temprature that oil properities must handled with that high temprature and alot of challenges that will be faced, an insulating oil is used to make the transformer so cold to operate safely and using a specific materials with exact temprature for each material by secure transfering of these materials and energies [7,8].…”

Section: Introductionmentioning

confidence: 99%

A survey on predicting oil spills by studying its causes using deep learning techniques

Nasr

Al-Sheref

Elwahab

2021

IJEECS

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<span>It’s so easy to know the accidents as it’s already happened and solving these accidents is immediately handled, but searching for a solution for these accidents, don’t deny the existence of reasons that made accidents happen. Knowing the source of accidents will help in avoiding them to occur in the future. It’s an important field in searching as some human lives depend on the safety of such a field, so it’s so important to use a powerful technique to define these reasons as the research point in spill accidents and predicting accidents and to predict the occurrence of the accident before its happening depending on its reasons that lead to that accident in past times so with similar conditions it might happen an accident but it needs a sufficient data and a powerful technique such as deep learning techniques that give very precise results and by using this tool an Intelligent Model will build to predict oil spilling. In this survey paper, related work will be discussed to enhance that work.</span>

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Diagnosis of the single leakage in the fluid pipeline through experimental study and CFD simulation

Cited by 37 publications

References 41 publications

Numerical study of pipeline leak detection for gas-liquid stratified flow

Numerical study of pipeline leak detection for gas-liquid stratified flow

Leakage simulation and acoustic characteristics based on acoustic logging by ultrasonic detection

A survey on predicting oil spills by studying its causes using deep learning techniques

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