Accounting for Safety Barriers Degradation in the Risk Assessment of Oil and Gas Systems by Multistate Bayesian Networks

Dimaio, F.; Scapinello, Oscar; Zio, Enrico; Ciarapica, C.; Cincotta, Salvatore; Crivellari, Anna; Decarli, Luca; Larosa, L.

doi:10.1016/j.ress.2021.107943

Cited by 33 publications

(9 citation statements)

References 47 publications

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“…In (Di Maio et al 2021), the health state of each barrier is defined as a multistate variable which can assume values "High" ("H"), which indicates that the barrier is in a as-good-as-new condition, "Medium" ("M"), which indicates that the barrier is moderately degraded, and "Low" ("L"), which indicates that the barrier is in a critical condition that may cause it to cease its function. A probability is assigned to each health state of the barrier , , by defining barrierspecific Key Performance Indicators (KPIs), , .…”

Section: Estimation Of the Performance Of The Barriersmentioning

confidence: 99%

“…Finally, a method for estimating the performance of the safety barriers is developed. It builds up on the method proposed in (Di Maio et al 2021), which estimates the performance of a given barrier using dedicated key performance indicators computed considering the number and severity of the PSEs occurred in a given interval of time. The novel method exploits the capability of the developed NLP technique of identifying the PSE events containing keywords associated to a specific barrier.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Method based on Natural Language Processing for Periodically Estimating Variations of Performance of Safety Barriers in Hydrocarbon Production Assets

Valcamonico,

Baraldi,

Zio

et al. 2023

Proceeding of the 33rd European Safety and Reliability Conference

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This work develops a methodology for estimating the performance of safety barriers of hydrocarbon production assets using reports of Process Safety Events (PSEs). We address the challenge of dealing with assets that evolve, e.g., due to degradation of components or maintenance interventions, so that also the performances of the safety barriers vary in time. The proposed methodology combines a taxonomy of the words used in the reports, a method of Natural Language Processing (NLP) for the extraction of the keywords, which takes into account the time of occurrence of the PSEs, and a technique for estimating the barrier performance from the number and severity of PSEs involving the barrier. The proposed methodology is validated using a repository of reports of PSEs in hydrocarbon production plants.

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Section: Estimation Of the Performance Of The Barriersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Method based on Natural Language Processing for Periodically Estimating Variations of Performance of Safety Barriers in Hydrocarbon Production Assets

Valcamonico,

Baraldi,

Zio

et al. 2023

Proceeding of the 33rd European Safety and Reliability Conference

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“…(2) data-driven [39], and (3) mapped from other models like the fault-tree, event-tree, or bow-tie models [40][41][42]. The third approach is adopted in this study, where the potential accident scenarios of a system are first determined by a fault tree, which is then mapped into a BN according to the method shown in Figure 3.…”

Section: Mapping To Bayesian Network From Fault Treementioning

confidence: 99%

Failure Risk Assessment of Coal Gasifier Based on the Integration of Bayesian Network and Trapezoidal Intuitionistic Fuzzy Number-Based Similarity Aggregation Method (TpIFN-SAM)

Liu

Wang

Liu³

et al. 2022

Processes

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The coal gasifier is the core unit of the coal gasification system. Due to its exposure to high temperatures, high pressures, and aggressive media, it is highly susceptible to serious accidents in the event of failure. Therefore, it is important for the gasifier to perform failure-risk assessment to understand its safety status and provide safety measures. Bayesian networks (BNs) for risk analysis of process systems has received a lot of attention due to its powerful inference capability and its ability to reflect complex relationships between risk factors. However, the acquisition of basic probability data in a Bayesian network is always a great challenge. In this study, an improved Bayesian network integrated with a trapezoidal intuitionistic fuzzy number-based similarity aggregation method (TpIFN–SAM) is proposed for the failure-risk assessment of process systems. This approach used the TpIFN–SAM to collect and aggregate experts’ opinions for obtaining the prior probabilities of the root events in the BN. In the TpIFN–SAM, the intuitionistic fuzzy analytic-hierarchy-process method (IF-AHP) was adopted to assign the expert weights for reducing subjectivity or the bias caused by individual differences. To clarify the suitability of the proposed method, a case study of a coal gasifier was demonstrated, and both prediction and diagnosis analyses of the BN were performed; finally, the weak links of the gasifier were identified.

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“…As shown in Table 2, Bowtie analysis is used as a part of the hybrid method for risk assessment along with other types of quantitative tools, such as the Bayesian network, the probabilistic method, and human reliability assessment in four separate articles. 4,12,15,54 The LOPA method was only applied in one article along with the use of the Bayesian network method as part of the study in the past 15 years of literature review. 20 F I G U R E 3 Distribution of articles reviewed that is applied within the offshore industry.…”

Section: Scopes Of Risk Assessment In Offshore Facilitiesmentioning

confidence: 99%

ALARP demonstration in management of change using quantitative Bowtie analysis risk assessment tool for an offshore gas platform

Aziz

Said

2022

Process Safety Progress

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In this study, a framework for a quantitative Bowtie analysis based on the layer of protection analysis (LOPA) approach in the management of change (MOC) process flow was developed. The proposed tool can be used as a quantitative risk analysis method in supporting decisions when layers of protection or safeguards are unavailable. The proposed tool can quantify the frequency of the causes of a particular hazard via Fault Tree Analysis and identify the multiple consequences of the impact of the hazards with quantitative end events for risk analysis. The practicality of the proposed tool was demonstrated in a selected case study from the MOC database from Company A's offshore gas platform, where the consequences and impacts of the hazards to the people, environment, assets, and reputation were assessed. The LOPA quantification was introduced into the Bowtie diagram using a reliability database to determine the failure rates and probability of failure of the affected equipment. The risk tolerance level was subsequently determined.The outputs of risk analysis from the proposed quantitative Bowtie were then compared with the previous qualitative risk evaluation of the selected case study.Potential opportunities for further use of the proposed quantitative Bowtie tool were recommended.

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Accounting for Safety Barriers Degradation in the Risk Assessment of Oil and Gas Systems by Multistate Bayesian Networks

Cited by 33 publications

References 47 publications

A Method based on Natural Language Processing for Periodically Estimating Variations of Performance of Safety Barriers in Hydrocarbon Production Assets

A Method based on Natural Language Processing for Periodically Estimating Variations of Performance of Safety Barriers in Hydrocarbon Production Assets

Failure Risk Assessment of Coal Gasifier Based on the Integration of Bayesian Network and Trapezoidal Intuitionistic Fuzzy Number-Based Similarity Aggregation Method (TpIFN-SAM)

ALARP demonstration in management of change using quantitative Bowtie analysis risk assessment tool for an offshore gas platform

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