A major leak in a crude oil tank: Predictable and unexpected root causes

Cirimello, Pablo; Otegui, J.L.; Ramajo, Damián E.; Carfi, Guillermo

doi:10.1016/j.engfailanal.2019.02.005

Cited by 21 publications

(9 citation statements)

References 6 publications

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“…In oil tank safety monitoring, GS monitoring is of vital importance for the thin shell structure of oil tanks, to prevent severe damage such as distortion or cracking of the tank walls [ 4 , 12 , 13 ]. The prerequisite requirement of GS monitoring is to establish a stable reference point for comparison with the measurements obtained at various test points.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

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Transfer-Learning-Based Temperature Uncertainty Reduction Algorithm for Large Scale Oil Tank Ground Settlement Monitoring

Liu,

Jiang,

Liu

et al. 2023

Sensors

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Sensors operating in open-air environments can be affected by various environmental factors. Specifically, ground settlement (GS) monitoring sensors installed in oil tanks are susceptible to non-uniform temperature fields caused by uneven sunshine exposure. This disparity in environmental conditions can lead to errors in sensor readings. To address this issue, this study aimed to analyze the impact of temperature on GS monitoring sensors and establish a mapping relationship between temperature uncertainty (fluctuations of measurement caused by temperature variation) and temperature variation. By collecting the temperature information and inferring the temperature uncertainty being introduced, this interference can be removed. However, it is crucial to note that in real-world complex scenarios, the relationship between temperature uncertainty and temperature variation is not always a constant positive correlation, which limits the data available for certain periods. Moreover, the limited availability of data presents a challenge when analyzing the complex mapping relationship. To overcome these challenges, a transfer-learning-based algorithm was introduced to develop a more accurate model for predicting temperature uncertainty based on temperature variation, even with limited data. Subsequently, a practical test was conducted to validate the proposed algorithm’s performance. The results demonstrated that the algorithm outperformed a simple linear fitting model using the least squares method (LSM), achieving an improvement of up to 21.9%. This outcome highlights the algorithm’s potential for enhancing the performance of GS sensors in daytime monitoring and contributing to the safe operation of oil tank facilities and infrastructure health monitoring.

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Section: Theoretical Backgroundmentioning

confidence: 99%

“…Ground settlement in oil tanks is a critical factor that can compromise their structural integrity and service life [ 1 , 2 , 3 , 4 ], as depicted in Figure 1 a. This emphasizes the importance of prioritizing GS monitoring for large scale infrastructures.…”

Section: Introductionmentioning

confidence: 99%

Transfer-Learning-Based Temperature Uncertainty Reduction Algorithm for Large Scale Oil Tank Ground Settlement Monitoring

Liu,

Jiang,

Liu

et al. 2023

Sensors

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“…As it was studied by Cirimello et al [31], such an analysis could be expanded using even the most complicated CFD methods, wherein the authors showed that in the case of a large opening, a 2000 m 3 storage tank of crude oil could be emptied in less than a minute, while the leak flow could pose huge loadings on the containment enclosure. However, in the case study presented in this paper, such secondary effects were not considered and since the full collapse of the storage tank was assumed, fluid dynamics calculations were not necessary for this specific scenario.…”

Section: Consequences Assessmentmentioning

confidence: 99%

Aggregated Risk Assessment and Survey for Risk Reduction in Oil Terminals

et al. 2021

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One of the goals of any oil terminal is to make a business while avoiding hazardous events and harmful effects for both humans and the environment. This can be achieved by creating a safe working place as well as by performing safe and acceptable activities regarding the impact on surrounding objects, including residential and industrial areas. The aim of the hazard analysis of the oil terminal is to assess the risks related to hazardous events or phenomena and to evaluate whether the assessed risks are acceptable. The hazard analysis and assessment of risk are also used for risk reduction while examining and limiting hazardous scenarios that, for instance, involve the loss-of-containment of flammable or combustible material. In this paper, the authors aim to contribute to risk research by providing a comprehensive methodology of risk assessment for oil terminals with case study results and discussion on features of the methodology, risk aggregation, its applicability for risk reduction, and industrial interests. The performed study considered the “Klaipedos Nafta AB” (an operator of the Klaipeda Oil Terminal, Lithuania) case study regarding hazardous materials that might be released from various tanks, devices, and associated pipelines. The performed quantitative risk assessment has enabled the determination of the probability regarding whether releases would ignite and, for instance, cause explosion. In the case study, the estimate of probability, i.e., the frequency, and the possible consequences of the hazardous events were evaluated, and both mitigation and risk reduction measures were also considered.

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“…In work [27] three stages of static storage tank leaks are analyzed and a model is proposed that has been tested on small scale tank leakage for the leak alarm time. The article [28] the reasons for the failure of a tank in a crude oil refinery have been analyzed, and fracture models and hydrodynamic calculations have been developed to identify the causes of failure, as well as to reconstruct the sequence of events.…”

Section: Introductionmentioning

confidence: 99%

Mobile Application Development to Assess the Level of a Safety Warehouse of Petroleum Product

Pelekh

2021

E3S Web Conf.

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The importance of oil for Russia, its storage in warehouses of oil and oil products, as well as the danger associated with the occurrence of accidents and incidents are considered. Examples of accidents that have occurred with the resulting consequences are given. The necessity of carrying out checks using checklists is revealed. Using the modeling method, a mobile application has been designed and developed, which contains a checklist consisting of questions on assessing the industrial safety of an oil product storage warehouse. The mobile application will allow you to conduct a “self-test” of the protected object on all issues of industrial safety, according to the checklist. Notification of upcoming inspections will provide an opportunity to prepare in advance for inspection by regulatory authorities in the field of industrial safety. Notification of violated dead-lines for eliminating the comments and shortcomings identified during the check will allow the management of the facility to respond in a timely manner and thereby ensure reliable protection of the protected object.

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A major leak in a crude oil tank: Predictable and unexpected root causes

Cited by 21 publications

References 6 publications

Transfer-Learning-Based Temperature Uncertainty Reduction Algorithm for Large Scale Oil Tank Ground Settlement Monitoring

Transfer-Learning-Based Temperature Uncertainty Reduction Algorithm for Large Scale Oil Tank Ground Settlement Monitoring

Aggregated Risk Assessment and Survey for Risk Reduction in Oil Terminals

Mobile Application Development to Assess the Level of a Safety Warehouse of Petroleum Product

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