Pipeline Risk Assessment Research Articles

A BN-based risk assessment model of natural gas pipelines integrating knowledge graph and DEMATEL

As one of the most essential process facilities, the natural gas pipeline may be affected by various hazards and result in frequent accidents. Although Bayesian Network (BN) and other methods have been applied for risk assessment of gas pipelines, most attempts rely on experts instead of data. In this paper, a novel risk assessment model integrating Knowledge Graph (KG), Decision-Making Trial and Evaluation Laboratory (DEMATEL), and BN is proposed to analyze gas pipeline accidents in a data-driven way to minimize the reliance on experts for the current BN-based approach. First, the KG is used to extract and illustrate the causal network from accident reports on the Internet instead of a limited number of experts. Then, DEMATEL is applied to quantify the complex correlations in the causal network to simplify the topology structure and convert it into a BN structure. Moreover, by conducting BN analysis, a probabilistic causation model of gas pipeline accidents is established to identify critical hazards, predict potential consequences and optimize risk reduction strategies. The proposed model can more objectively support the safety management and risk reduction of natural gas pipelines and other process installations in the digital age.

Risk Assessment of Oil and Gas Pipeline Based on Vague Set-Weighted Set Pair Analysis Method

This study focuses on a risk assessment method for oil and gas pipelines. Oil and gas pipelines are usually constructed in a complex geological environment and are potentially dangerous. Risk assessment is a key step for their safety management. Therefore, the present paper establishes a risk indicator system as the risk assessment foundation, and we propose a risk assessment method to obtain a quantitative assessment result for the pipeline based on set pair analysis (SPA) theory. For the weight values of each indicator in the assessment process, this paper presents a calculation method based on vague sets theory. Then, a pipeline in the Yanchang oilfield was taken as a case study to verify the feasibility of the method, and the final assessment result was 2.911, which meant the pipeline was relatively safe. The method could also obtain the risk level of each indicator, showing that geological conditions, extreme weather, and public safety awareness were particularly unsafe, and service time, pipeline deformation, ground activity, and operation training were relatively unsafe. It is expected that the risk assessment result could provide a reference for pipeline safety management.

Pipeline Risk Assessment Using GIS

Long-distance energy pipelines are subject to risks of repeated hazards and posing pipeline safety problems. Hazards that may attack the pipelines are environmental and human activities. In this study, the risks of hazards on pipeline were assessed using Geographic Information System (GIS) as research on pipeline risk assessment using GIS is quite limited. Satellites help to monitor pipelines from space. The study spatially analyzes the risks that a pipeline encounters and the Kurdistan oil pipeline from Taq Taq oil field to Peshkhabur was used as a case study. Six criteria including distance to cities and villages, rivers, roads, slopes, and temperature in cold and hot weather were considered. Weight is given to each criterion; a maximum of 37.5% for human activities and a minimum weight of 12.5% for slope. The calculations were carried out spatially rather than through statistical operations. Three sets of maps were obtained for each criterion with different units. Then the maps were overlayed to represent a single map and the units were standardized using Fuzzy membership. The results show the risk level of each criterion along the 270 km length of the Kurdistan national pipeline.

MODL-08. ESTABLISHING IN VITRO MODELS TO RECAPITULATE PROTEIN-LEVEL PROGNOSTIC CELL PHENOTYPES FROM PRIMARY HUMAN GLIOBLASTOMA

Abstract Glioblastoma (GBM) is a highly aggressive primary central nervous system tumor for which median survival continues to be low, despite multimodal treatment and surgical resection. Heterogeneity at many levels (genomic, cytoarchitectural, and metabolic) likely contributes to these poor outcomes, and single-cell approaches can help to identify prognostically meaningful cells and features within heterogeneous tumors at each of these levels. Recent studies using mass cytometry (CyTOF) and the accompanying analysis pipeline Risk Assessment Population Identification (RAPID) measured per-cell protein levels in > 2 million cells from 28 IDH1/2-wildtype primary glioblastoma tumors and identified 2 phenotypes within these tumors that are present in different abundances across patients and have contrasting prognostic value. Increased abundance of Glioblastoma Negative Prognostic (GNP) cells within these tumors is predictive of shorter overall survival (OS HR = 1.07 [95% CI 1.02–1.12], p = 0.003), while the converse is true for Glioblastoma Positive Prognostic (GPP) cells (OS HR = 0.93 [0.87–1.0], p = 0.05). To effectively study these phenotypes, reproducible in vitro models are needed that recapitulate the total protein expression and phosphorylation events that distinguish GNP and GPP cells. Using available RNA transcript data, a candidate subset of glioma stem cell models were identified and are now being profiled using standardized mass-tagged antibody panels. These culture models will be quantitatively compared against established GNP and GPP populations in patient tissue samples using the Marker Enrichment Modeling statistic as well as other machine learning tools. Development of these models will be critical to future experiments aimed at identifying possible mechanistic therapies that effectively eliminate each of these identified populations, as well as aligning these protein-level phenotypes to other genomic and functional data in glioblastoma samples and models.

A novel approach to touch voltage risk assessment for gas pipelines in shared transmission corridors

Touch voltages are more likely to appear on long-distance pipelines that lie in shared corridors with transmission lines. The touch voltage level varies with soil resistivity and can become hazardous while maintenance is being undertaken, necessitating risk assessment. Therefore, a novel approach is proposed that achieves better accuracy in the risk assessment of hazardous touch voltages appearing on pipelines than current approaches. The proposed approach incorporates soil resistivity measurements taken over a 1-year period, allowing for the derivation of soil models, touch voltage hazard profiles versus time and, thus, a probability reduction factor that can be integrated into a probabilistic risk calculation. Using a probability reduction factor is a key aspect to improving the accuracy of risk assessment, allowing pipeline asset operators to clearly identify whether or not, risk mitigation action is required. Further, the proposed approach allows appropriate risk mitigation actions to be identified. The efficacy and significance of the proposed approach are demonstrated through a case study on an area of land near a shared gas pipeline and transmission line corridor. The case study results show how appropriate safety levels can be achieved by adjusting the number of work day per year and temporary protection settings.

A Characterisation of Benthic Currents from Seabed Bathymetry: An Object-Based Image Analysis of Cold-Water Coral Mounds

Seabed sedimentary bedforms (SSBs) are strong indicators of current flow (direction and velocity) and can be mapped in high resolution using multibeam echosounders. Many approaches have been designed to automate the classification of such SSBs imaged in multibeam echosounder data. However, these classification systems only apply a geomorphological contextualisation to the data without making direct assertions on the velocities of benthic currents that form these SSBs. Here, we apply an object-based image analysis (OBIA) workflow to derive a geomorphological classification of SSBs in the Moira Mounds area of the Belgica Mound Province, NE Atlantic through k-means clustering. Cold-water coral reefs as sessile filter-feeders benefit from strong currents are often found in close association with sediment wave fields. This OBIA provided the framework to derive SSB wavelength and wave height, these SSB attributes were used as predictor variables for a multiple linear regression to estimate current velocities. Results show a bimodal distribution of current flow directions and current speed. Furthermore, a 5 k-means classification of the SSB geomorphology exhibited an imprinting of current flow consistency which altered throughout the study site due to the interaction of regional, local, and micro scale topographic steering forces. This study is proof-of-concept for an assessment tool applied to vulnerable marine ecosystems but has wider applications for applied seabed appraisals and can inform management and monitoring practice across a variety of spatial and temporal scales. Deriving spatial patterns of hydrodynamic processes from widely available multibeam echosounder maps is pertinent to many avenues of research including scour predictions for offshore structures such as wind turbines, sediment transport modelling, benthic fisheries, e.g., scallops, cable route and pipeline risk assessment and habitat mapping.

Simulation Analysis of External Damage and Repair of the Gas Transmission Pipeline

External damage and repair of a gas transmission pipeline were often encountered in industrial production. The damage of the gas transmission pipeline and the evaluation after repair could be solved by the finite element simulation method. Damage assessment and postrepair assessment were carried out for an external damage example of a gas transmission pipeline in an oil field based on finite element software ABAQUS. Ideally, the finite element simulation results were modified by using the theoretical calculation results of the gas transmission pipeline. Then, the simulation analysis of the defective gas transmission pipeline was carried out, and the corresponding maintenance suggestions were put forward. Finally, the B-type sleeve repair and carbon fiber composite repair were simulated and analyzed, respectively, and the bearing and stress of two kinds of repair were compared and analyzed. It was concluded that the repair effect of the carbon fiber composite was better than that of B-type sleeve. The research results could provide a new evaluation mechanism for pipeline defects and pipeline defects after repair and laid a foundation for quantitative risk assessment and repair of gas transmission pipelines.

Risk assessment of interstate pipelines using a fuzzy-clustering approach

Interstate pipelines are the most efficient and feasible mean of transport for crude oil and gas within boarders. Assessing the risks of these pipelines is challenging despite the evolution of computational fuzzy inference systems (FIS). The computational intricacy increases with the dimensions of the system variables especially in the typical Takagi–Sugeno (T–S) fuzzy-model. Typically, the number of rules rises exponentially as the number of system variables increases and hence, it is unfeasible to specify the rules entirely for pipeline risk assessments. This work proposes the significance of indexing pipeline risk assessment approach that is integrated with subtractive clustering fuzzy logic to address the uncertainty of the real-world circumstances. Hypothetical data is used to setup the subtractive clustering fuzzy-model using the fundamental rules and scores of the pipeline risk assessment indexing method. An interstate crude-oil pipeline in Egypt is used as a case study to demonstrate the proposed approach.

Risk assessment of submarine pipelines: A case study in Turkey

The risk assessment of submarine pipeline is carried out considering vertical and horizontal displacements under hydrodynamic forces. The stability of the pipeline is assessed according to limit-state functions using Monte Carlo (MC) simulation. The effects of subsea topography, hydrodynamic loads of waves and currents, pipe-soil interaction, and characteristics of hazardous materials carried by the pipeline were examined. The failure probability obtained by the MC simulation was defined by the exceedance probability of the displacement limit state. The novel part of this paper is the MC simulation which is coupled with a 3-D hydrodynamic numerical model (Hydrotam-3D) developed by Balas (Balas and Ozhan, 2000). The effects of pipe-soil interactions and environmental parameters such as wave-induced currents can be obtained by this model coupling. The most important parameters that affect the results of the simulations are obtained. Hydrodynamic loads that depend on the combined actions of waves and currents are obtained by the hydrodynamic numerical model (Hydrotam-3D) and they are used in the MC simulation, to increase the reliability of the pipeline design.

Prediction of rupture and perforation limits of pressurised X80 pipelines using BP neural networks and generalised additive models

Impact resistance of in-service pressurised X80 pipelines is one of the top safety priorities in the petrochemical industry. Based on impact limits, including the rupture and perforation limits, the failure threshold can be identified and the impact resistance of target structures can be assessed. In this study, backpropagation neural networks (BPNNs) and generalised additive models (GAMs) were developed to predict the rupture and perforation limits of pressurised X80 pipelines. First, an explicit dynamic model was established to provide comprehensive training datasets considering the effects of various dominant parameters. Interdependencies between the impact limits and various dominant parameters were analysed using the Pearson correlation coefficient. Then, BPNN models optimised by the backpropagation algorithm and neuron numbers were trained to predict the impact limits. Based on the optimal smooth functions and smoothing coefficients, the GAMs then provided two integrated regression functions for impact limits. Finally, the predictive stabilities of the BPNN and GAM on impact limits were discussed using a random dataset. The BPNNs and GAMs were in a strong agreement with the expectations, and the predictive accuracy of the BPNNs was approximately three times that of GAMs. The findings of this study can be used as guidelines for protection design and risk assessment of pressurised X80 pipelines.

A safety management system for natural gas pipeline in subsidence area of coal mine

ABSTRACT As one of the main ways to transport natural gas, pipeline safety is of great significance to maintaining social stability and ensuring the national energy supply. Aiming at the safe operation of natural gas pipelines in subsidence areas of coal mine, this work proposes a safety management system for condition monitoring and control. This system contains three technical modules: the surface and pipeline displacement monitoring, the risk assessment index system, and early warning model. Firstly, the collected data of site topography and pipeline conditions are transmitted to the database remotely. Second, multi-source data are collected to form data reports and conduct in-depth analysis and mining. Then, according to the analysis results, the pattern of surface and pipeline displacement is explored, the risk assessment system of gas pipelines is constructed, and the pipeline strain is monitored. Real-time computing and other technologies are developed to form a safety management system for gas pipelines in subsidence areas. Taking Shanxi Province in China as an example, based on the system developed by the technical modules, the application of surface and pipeline displacement monitoring, risk assessment, and pipeline stress-strain monitoring technology in subsidence areas is achieved. The results show that the risk score of the area where the pipeline is located is 82, which is a high-risk level. In addition, in the process of strain monitoring, the measured stress at the most unfavorable position is 140.207 MPa, which meets the allowable stress requirements. This safety management system can provide important support for decision-making of risk prevention, assessment, and management of natural gas pipelines in subsidence areas of coal mine.

A novel fuzzy approach to gas pipeline risk assessment under influence of ground movement

The gas transport infrastructure is frequently localized in areas subjected to anthropogenic movements and strains. The potential impact of the ground movements on the gas pipeline in the aspect of its damage can be properly assessed e.g. by predicting strains, taking into account the causes of terrain movement. On the other hand, the hazard is also related to technological factors like design of the pipeline. The presented method is based on artificial intelligence methods allowing for evaluation of probability of failure risk in gas supply pipeline sections. The Mamdani fuzzy inference was used in this study. Uncertainty of variables characterizing the resistance of the gas pipeline and predicted continuous deformations of ground surface were accounted for in the model by using triangular-shaped membership functions. Based on the surface deformations and gas pipeline resistance and the inference model one can make prediction when the gas pipeline is hazarded. There were estimated two the most hazarded parts for two pipelines. We proved that the proposed model can contribute to the protection, costoptimization of the designed pipelines and to the repairs of the existing gas pipelines.

Improved quantitative risk assessment of a natural gas pipeline considering high-consequence areas

Currently, quantitative risk assessment is often used for pipeline safety analysis. However, the low probability of pipeline failure may produce a false safety evaluation result because high-consequence areas with high population densities cannot be effectively identified. Furthermore, nearly half of the gas leakage accidents in China have occurred in densely populated areas. Therefore, an improved quantitative risk assessment method is proposed. First, we establish two models: (1) a failure probability model based on improved historical failure and disaster derivation probabilities and (2) a risk consequence model considering potential direct and indirect losses based on the probability of disaster evolution. Considering the concept of human rights equality and the social model of “life is first” in China, a method to correct the loss value of life according to population density is proposed, which can effectively avoid the hidden phenomenon of high-consequence areas mentioned above. A pipeline in China is evaluated using this improved method. Compared with traditional evaluation results, the new evaluation method can effectively identify a high-consequence area and obtain more reasonable results. Thus, a pipeline maintenance plan can ensure the interests of enterprises and fully respect the lives of individuals threatened by the potential risk of the pipeline.

Multidimensional risk assessment and categorization of hydrogen pipelines

The use of hydrogen has been shown to be an efficient form of producing energy and meeting society's demands for energy. In this perspective, pipelines are known as the safest and most economical transportation mode for hydrogen. However, accidents in this type of structure lead to multiple consequences of losses such as those related to people, the environment and properties. From this perspective, decision-makers are required to tackle the likelihood of these and to make suitable decisions that can prevent accidents from happening. Multicriteria methods have played an important role in addressing multiple risk problems when there is a need to assign priorities to risk-based decisions. This paper puts forward a multidimensional risk model to categorize hydrogen pipeline sections according to levels of risks based on Utility Theory and the ELECTRE TRI method. A probabilistic modeling is proposed so as to incorporate elements of risk analysis into the evaluation of situations such as accidental scenarios, their probabilities and consequences. An application of the model is presented for a hydrogen pipeline. The results demonstrate that measures to prevent and mitigate risks can be sharpened by taking into account the human, environmental and financial risks dimensions of impacts. Thus, the sections of the pipeline studied are sorted into categories of risks, where 4 out of 10 sections are assigned to the high-risk category, 1 to the medium-risk category, and 5 sections to the low-risk category. A local sensitivity analysis was conducted which varied the weights of the dimensions. Varying the weights by 20% showed that the risk of 3 sections increases to the medium-risk category and 1 section changes to the high-risk one. Moreover, this paper indicates visualization tools that are efficient at communicating information on the levels of risk and the categories of the sections, thus contributing to assessing models that categorize risk in hydrogen pipelines. By doing so this paper supports the process of prioritizing resources for pipeline sections, the aim being to minimize multiple losses.

CO2 Pipeline risk assessment and comparison for the midcontinent United States

A comprehensive quantitative risk assessment for the construction and operation of CO2 transportation networks considered for the Midcontinent United States was conducted. The results showed risks associated with CO2 pipelines were significantly less than those of other pipeline types. The assessment used four conceptual pipelines of different lengths to discuss risks operators may see. The assessment evaluated the risk associated with construction and operation using data from the US Occupational Safety Health Administration to determine the risk of injury or death for pipeline workers and data from the US Pipeline and Hazardous Materials Safety Administration for CO2, natural gas distribution, natural gas transmission/gathering, and non-CO2 hazardous liquid pipelines to develop quantitative likelihood and severity values leading to risk values. The data for the assessment covered incidents from 2010 to 2017 for CO2 pipelines. The average risk for construction and 30 years of operation for four CO2 pipeline configurations ranging between 79 and 1,546 miles in length was found. The construction and operational risk averaged between $1,400,521 (approximately $0.02/tonne of CO2) for the shorter pipeline (79 miles) and $27,481,939 (approximately $0.10/tonne of CO2) for a longer pipeline (1,546 miles). The largest risks of fatality for CO2 pipelines comes from vehicle transport. The largest operational risk to the pipeline was due to leakage. Public pipeline opposition is also a significant risk; it was not quantified but is addressed.

Earthquake Risk of Gas Pipelines in the Conterminous United States and Its Sources of Uncertainty

Relatively little research has been conducted to systematically quantify the nationwide earthquake risk of gas pipelines in the US; simultaneously, national guidance is limited for operators across the country to consistently evaluate the earthquake risk of their assets. Furthermore, many challenges and uncertainties exist in a comprehensive seismic risk assessment of gas pipelines. As a first stage in a systematic nationwide assessment, we quantify the earthquake risk of gas transmission pipelines in the conterminous US due to strong ground shaking, including the associated uncertainties. Specifically, we integrate the US Geological Survey 2018 National Seismic Hazard Model, a logic tree–based exposure model, three different vulnerability models, and a consequence model. The results enable comparison against other risk assessment efforts, encourage more transparent deliberation regarding alternative approaches, and facilitate decisions on potentially assessing localized risks due to ground failures that require site-specific data. Based on the uncertainties approximated herein, the resulting sensitivity analyses suggest that the vulnerability model is the most influential source of uncertainty. Finally, we highlight research needs such as (1) developing more vulnerability models for regional seismic risk assessment of gas pipelines; (2) identifying, prioritizing, and measuring input pipeline attributes that are important for estimating seismic damage; and (3) better quantifying seismic hazards with their uncertainties at the national scale, for both ground failures and ground shaking.

Risk assessment of buried gas pipelines based on improved cloud-variable weight theory

Various risk factors of urban gas pipelines will lead to leakage, significantly impacting the environment, assets, and life safety, thus making pipeline risk prevention and control crucial. However, existing methods cannot sufficiently model the uncertainty in the pipeline risk evaluation process. In addition, the calculation method of factor weights may lead to unrealistic results. In this study, variable weight theory and cloud theory are introduced. Then, a novel method of cloud-variable weight function is proposed to analyze the pipeline's risk level and critical risk factors by establishing a pipeline risk assessment index system. The proposed method fully considers the uncertainty in the evaluation process, resolves the contradiction of existing methods to model the fuzzy concepts accurately, optimizes the weight distribution, and obtains a more scientific and reasonable assessment result. A case study is conducted on a pipeline in Beijing City. The results illustrate that the proposed method is beneficial for helping pipeline operators determine the pipeline risk status and weak links in the pipeline system, thereby providing a basis for risk control and rehabilitation.

Application of Kent Muhlbauer Method to Risk Assessment of Urban Gas Pipelines

AbstractOil and gas revenues play an important role in the Iranian economy and are the main source of government spending and a major part of commodity exports. Therefore, safe transport of these p...

Retraction Note: Oil spill risk assessment of submarine oil pipeline based on fuzzy comprehensive evaluation and accounting

Retraction Note: Oil spill risk assessment of submarine oil pipeline based on fuzzy comprehensive evaluation and accounting

The risk assessment of a crude oil pipeline using fuzzy and bayesian based bow-tie analysis

Cross country pipelines are one of the major modes of transportation of petroleum products. Due to external and internal factors, the failure probability of pipeline is increasing over the past decades. The failure of pipelines can cause fires, which can result in environmental damage, loss of materials and further resulting into casualties. Effective risk assessment is vital to prevent and mitigate such potential incidents. In this work, an efficient tool that makes use of Bayesian approach along with Bow-tie analysis is used to obtain the failure frequencies of all the identified causes that may lead to failure of the selected pipeline located in Kerala, India. Bayesian networks can perform effective dynamic risk analysis by considering the conditional dependencies between various basic events leading to pipeline failure. The fuzzy logic and expert elicitation method are incorporated to determine the prior failure frequencies of all the identified causes of pipeline failure. The effectiveness of Bayesian network in performing forward analysis to determine the probabilities of pipeline failure consequences is demonstrated. This study also identifies the weak links associated with the occurrence of particular consequences, so that adequate measures can be taken to rectify them.