Pipeline Risk Management Research Articles

Safety Assessment of Gas Pipelines Crossing River through Hydrodynamic Analysis

Gas pipelines are buried and installed across rivers to supply the gas necessary for daily life. When crossing rivers, gas pipelines are typically installed on bridges; however, when installation on bridges is not feasible, the pipelines are buried in riverbeds. This study utilized both a one-dimensional model (HEC-RAS) and two-dimensional models (SMS) to simulate river flow and estimate the potential for scour and deposition around buried pipelines. The hydrodynamic simulations considered critical factors, including sediment transport, river discharge, and geological characteristics, to derive the maximum scour depth and assess the risk of pipeline exposure. The findings from the long-term and short-term simulations confirmed that riverbed changes due to natural hydrological events do not exceed the minimum burial depth standards, thereby ensuring pipeline safety. In addition, the study proposed specific reinforcement measures tailored to local site conditions, addressing concerns of continuous subsidence and ensuring long-term structural stability. This research offers important insights into pipeline risk management and contributes to the development of more effective regulatory standards for gas pipelines buried in riverbeds, enhancing both their safety and environmental sustainability

Risk-based maintenance strategy for oil transfer pipelines using an intuitionistic fuzzy computational approach

The safety and reliability of oil transfer pipelines are crucial, as pipeline failures can severely affect the environment. As pipeline risk management is dynamic and uncertain, traditional maintenance approaches often fall short. This research paper proposes an Intuitive Fuzzy Computational Approach (IFCA) for oil transfer pipeline maintenance (RBM). To develop a targeted and nuanced maintenance plan, Failure Modes and Effects Analysis (FMEA) is employed. Pipeline equipment is hierarchically organised according to their failure mode criticality, which guides maintenance design. This paper leverages the context of an Interval Valued Intuitionistic Fuzzy (IVIF) environment to streamline the hierarchical classification of oil transmission pipeline instruments. The objectives are threefold: (1) to develop an intuitionistic fuzzy risk assessment model, (2) to design a modified algorithm for maintenance prioritisation, and (3) to develop a decision support system. Additionally, the research incorporates the IVIF-SWARA method to enable flexible adjustments in the alignment of the pipeline instruments. By addressing the specific challenges of oil transfer pipelines, this research aims to contribute to advancing the field of pipeline maintenance and risk management. The proposed RBM strategy, underpinned by the IFCA framework, is expected to enhance pipeline reliability and mitigate the risks associated with pipeline failures. Abbreviations: RBM: Risk-Based Maintenance; IFCA: Intuitionistic Fuzzy Computational Approach; FMEA: Failure Modes and Effects Analysis; IVIF: Interval Valued Intuitionistic Fuzzy; SWARA: Stepwise Weight Assessment Ratio Analysis; RCM: Reliability-Centered Maintenance; RBI: Risk-Based Inspection; CBM: Condition-Based Maintenance; IFS: Intuitionistic Fuzzy Set; HFPR: Hesitant Fuzzy Preference Relation; IVIFPHA: Interval-Valued Intuitionistic Fuzzy Power Heronian Aggregation; MCDM: Multi-Criteria Decision-Making; S C O i : Accuracy Function of Occurrence; S C S i : Accuracy Function of Severity; K ( a ~ ) : Failure Probability Index; L W D : Minimum Allowable Weight of The Failure Detection Index; WS, WO, WD: Weight Assigned to The Failure Outcome; RP V j : Relative Priority Value; OREDA: The Offshore Reliable Data Handbook; IVIFPWHA: Interval-Valued Intuitionistic Fuzzy Power Weight Heronian Aggregation

The Effect of Location Class Category and Pipe Wall Thickness on Risk Level Onshore Pipeline Oil

Pipelines are essential infrastructure for efficient oil and gas production operation, necessitating their continuous and reliable functionality in all locations and circumstances. Nevertheless, the pipeline can fail during operation due to multiple detrimental variables. This study evaluated the impact of the location classification category and pipe wall thickness on the risk level of onshore pipelines. The risk assessment method employed was a semiquantitative approach derived from the reference "Pipeline Risk Management Manual" by W. Kent Muhlbauer. The distributing crude oil pipeline, which spans a distance of 18 kilometers and has a diameter of 6 inches, was evaluated. The evaluation yielded a pipeline relative risk score of 0.91, classifying the pipeline as belonging to risk category 1B. Following this, the assessment findings were analyzed for all 36 pipeline segments, classifying 26 segments in the 1B category and the remaining 10 segments in the 2B category. From the analysis results, the difference between the two risk categories was produced by differences in location class categories, where the pipeline segment in location class 1 creates a 1B risk category; meanwhile, class 3 produces a 2B risk category. Furthermore, a pipeline with a wall thickness of 5.156 inches is associated with a risk score of 0.81, but a wall thickness of 4.1 inches yields a score of 1.41. These results indicate that the location class category and pipe wall thickness significantly impact the risk of onshore pipelines.

Probabilistic burst pressure prediction model for pipelines with single crack-like defect

While several models have been developed to predict the failure pressure of pipelines with corrosion defects, relatively few models are available for pipelines with cracking defects. The goal of this study is to develop an unbiased and accurate probabilistic burst failure pressure model for thin-walled pipelines containing a single, longitudinally-oriented, crack-like defect. A comprehensive database is first established, consisting of experimental and numerical data collected from literature as well as numerical data obtained from the extended finite element method (XFEM) conducted in this study. The failure pressure prediction model is developed by adding a correction factor to the modified Ln-Secant method, a semi-empirical model previously developed. The correction factor is modeled using a multivariate linear regression that considers the pipe properties and defect characteristics as independent variables. The proposed model delivers unbiased and less variable failure pressure predictions. A case study of an example pipeline with a crack like defect shows that the failure pressure model plays a critical role in the risk management of pipelines through a life-cycle cost analysis.

Application of game theory in risk management of urban natural gas pipelines

This paper presents a game theory methodology for risk management of urban natural gas pipelines, which is a collaborative participation mechanism of the stakeholders, including government, pipeline companies, and the public. Firstly, the involvement proportion of stakeholders in risk management under rational conditions is estimated by the static game theory. Subsequently, the system dynamics (SD) simulation is used to establish an evolution game model of stakeholders in risk management under the irrational conditions, in which the stability of the evolution game process is analyzed. The stakeholders’ involvement proportions from the static game model are utilized as the inputs for the evolution game model to simulate the dynamic evolution behavior of risk management strategies with different involvement proportions of stakeholders. Eventually, the dynamic evaluation game can extract an optimal strategy for risk management of urban natural gas pipelines. A case study is used to illustrate the methodology. In essence, this methodology can be extended for implementing risk management of urban infrastructure.

Physics-based neural network for probabilistic low cycle fatigue and ratcheting assessments of pressurized elbow pipe component

Elbow pipe components are frequently subjected to complicated thermo-mechanical load combinations cyclically in nuclear engineering, facing failures related to cyclic plastic responses, including low cycle fatigue (LCF) and ratcheting. To deal with the risk management of important pipelines, the probabilistic LCF and ratcheting assessments are indispensable to evaluate the reliability of such components considering the uncertain operating parameters. In this study, the new probabilistic Linear Matching Method (pLMM) framework is proposed to address the probabilistic structural integrity assessment, quantitatively predicting the statistical distribution of LCF life and ratchet limit by the surrogate model with the novel Linear Matching Method-driven neural network (LDNN). With the numerical investigations on the elbow pipe structure presented, the probabilistic assessment boundaries and reliability-centred evaluation diagrams in terms of LCF life and ratchet limit are established respectively, which are beneficial to get rid of the conservativeness of the traditional design schemes with safety factor.

A dynamic model for microbiologically influenced corrosion (MIC) integrity risk management of subsea pipelines

A dynamic model for microbiologically influenced corrosion (MIC) integrity risk management of subsea pipelines

Tensile Strain Capacity Prediction Model of an X80 Pipeline with Improper Transitioning and Undermatched Girth Weld.

As an important component of strain-based design, the tensile strain capacity (TSC) concept has been extensively used for pipelines that experience expectable plastic strain for both installation and service. However, some stress-based designed pipelines have experienced unforeseen plastic strain in the past decade that resulted in failure. It seems that the tensile strain capacity has gradually become an important requirement for geohazard risk management and pipeline maintenance of stress-based design pipelines. The tensile strain capacity of an X80 pipeline is investigated. The assessment in this work was based on the fracture initiation–control-based limit state. This limit state corresponds to the onset of stable tearing and generally provides a reasonably conservative estimate. Besides that, factors such as wall thickness, material’s strain hardening capacity, toughness, weld strength mismatch, HAZ (heat-affected zone) softening, pipe wall thickness, high–low misalignment, and internal pressure were also investigated to construct a prediction model of the X80 vintage pipeline.

Numerical Simulation of the Flow Pattern of Spiral Annular Flow with a Guide Strip by Spiral On-Way.

To study the gas–liquid two-phase spiral annular flow pattern and its conversion law in a horizontal tube with twist tape by spiral on-way, a numerical simulation is carried out using the RNG k-ε model, and the DPM model is adopted as the particle motion model. The research results show that three main flow patterns are obtained, which are spiraling churn flow, spiraling annular flow, and spiraling annular twine flow. The ratio of the liquid-phase to gas-phase velocity VL/VG is the main factor that affects the existence of the gas phase. When VL/VG > 1/2, the flow pattern is a spiral cluster flow; when 1/5 < VL/VG< 1/2, the flow pattern is a spiral annular flow; and when VL/VG < 1/5, the flow pattern is a spiral annular flow. Compared with the flow pattern of the local spiral flow pattern of the short twisted band, it was found that the occurrence conditions of annular flow were postponed and a new flow pattern appeared. The research results of this paper have guiding significance for the pipeline risk management of natural gas hydrates and the engineering application of the full rotation of guide strips.

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 CRITIC-VIKOR based robust approach to support risk management of subsea pipelines

The risk factors related to subsea pipeline failure are diversified and dependent. Efficient risk management is critical for preventing subsea pipeline failure accidents. This paper presents a novel approach for effective risk management of subsea pipelines, which can extract the importance of pipeline risk factors and prioritize the risk management of subsea pipelines. This approach integrates CRITIC with VIKOR to capture the internal correlation and inconsistency among pipeline risk factors and accurately quantify the risk of different pipe sections. The pipeline safety factors are identified to build index-based risk evaluation system of subsea pipelines. The failure risk of subsea pipeline varies with the pipe sections, which is divided considering the structural conditions of pipeline and environmental conditions. The CRITIC method is utilized to assign the weight of risk indices, and the VIKOR method is applied to assess the importance of pipe sections in a Multiple criteria decision-making (MCDM) manner, which can help to find the weaknesses of the pipeline and decide the risk of which pipe section should be mitigated prior. A case study is performed to illustrate the application of the proposed methodology, and it is observed that the approach can be a valuable tool to support more effective risk management and decision-making of subsea pipelines.

Development of probabilistic failure pressure models for pipelines with single corrosion defect

Many models have been developed in the past to predict the failure pressure of a pipeline with a single corrosion defect. However, most of the existing models are conservative and may lead to unnecessary repairs and maintenance in the pipeline risk management. The aim of this study is to develop probabilistic failure pressure prediction models that are suitable for risk assessment of corroded pipelines. The proposed models are developed at three levels of pipe ultimate strength based on a comprehensive database (consist of both experimental and numerical data) established in this study. When comparing with the existing models, it is found that the proposed models provide unbiased and more accurate predictions. Also, the results of the reliability analysis of a corroded pipeline with various material properties and corrosion configurations reveal that the performance of a failure pressure prediction model plays a critical role in determining the structural performance of corroded pipelines.

Risk assessment of fire, explosion and release of toxic gas of Siri–Assalouyeh sour gas pipeline using fuzzy analytical hierarchy process

BackgroundRisk assessment of gas pipelines is very important because of various hazards and economic losses. Using fuzzy logic increases the reliability and accuracy of the results. The purpose of this study is to evaluate the fuzzy risk of fire, explosion and release of toxic gas in the pipeline using fuzzy analytical hierarchy process. MethodologyExtraction of all hazards from HAZOP and HAZID was carried out. Fuzzy risk assessment was performed using MATLAB software. Using fuzzy hierarchy process analysis, the weight of each basic risk item (BRI) was summed up in a framework, and the fuzzy risk level was determined with a five-state criterion including highly desirable, favorable, moderate, undesirable and highly undesirable. ResultsThe final risk score was equal to 0.1492, which according to the five-state criterion the risk level is in the favorable area. The highest risk score was related to hot work with open flame item with a risk score of 0.2485. ConclusionsThe final risk score of fire, explosion and release of toxic gas in Siri–Assaluyeh gas pipeline is in the optimal area. Fuzzy risk assessment, compare to conventional risk matrices, provides more data to safety managers about the hazards and their rankings. Accordingly, the results are expected to be applicable to the safety managers while making decisions related to the risk management of gas pipelines.

Deeppipe: A semi-supervised learning for operating condition recognition of multi-product pipelines

Intelligent operating monitoring of pipelines helps to detect anomalies in time to ensure pipeline safe, reducing potential risk. However, the operating conditions of the multi-product pipeline change frequently, and the recognition and monitoring by on-site personnel are easy to cause misjudgment, so the operating conditions of the pipeline cannot be accurately recognized. Noticeably, operating condition recognition is an important part of pipeline safety and risk management. Although ample operating data are stored in SCADA system, these data are lack of corresponding condition labels, making it hard to be mined. In this work, a semi-supervised learning for operating condition recognition is proposed to overcome aforementioned issues. Firstly, the operating parameters of each station are preprocessed and collected to construct into data matrices to overcome transient disturbance considering the pipeline space characteristics and time series of the operating data. Then stacked autoencoder (SAE) is used to pre-train the network parameters of multi-layer neural network (MLNN) based on a large amount of unlabeled operating data. After that, MLNN is fine-tuned based on a small amount of labeled data annotated by referring to the operation log. To verify the effectiveness of the semi-supervised learning, a real multi-product pipeline is taken as an example for operating condition recognition. The accuracy, precision, recall and F1 score is 95 %, 95 %, 80 % and 80 %, respectively. Results show that the condition recognition accuracy of the proposed model is better than other machine learning models. Finally, the sensitivity analysis is conducted to illustrate the importance of SAE in this classification model.

Dynamic probability assessment of urban natural gas pipeline accidents considering integrated external activities

Urban gas pipelines usually have high structural vulnerability due to long service time. The locations across urban areas with high population density make the gas pipelines easily exposed to external activities. Recently, urban pipelines may also have been the target of terrorist attacks. Nevertheless, the intentional damage, i.e. terrorist attack, was seldom considered in previous risk analysis of urban gas pipelines. This work presents a dynamic risk analysis of external activities to urban gas pipelines, which integrates unintentional and intentional damage to pipelines in a unified framework. A Bayesian network mapping from the Bow-tie model is used to represent the evolution process of pipeline accidents initiating from intentional and unintentional hazards. The probabilities of basic events and safety barriers are estimated by adopting the Fuzzy set theory and hierarchical Bayesian analysis (HBA). The developed model enables assessment of the dynamic probabilities of consequences and identifies the most credible contributing factors to the risk, given observed evidence. It also captures both data and model uncertainties. Eventually, an industrial case is presented to illustrate the applicability and effectiveness of the developed methodology. It is observed that the proposed methodology helps to more accurately conduct risk assessment and management of urban natural gas pipelines.

Quantitative assessment of ground deformations for the risk management of petroleum and gas pipelines using radar interferometry

The primary objective of these studies was to quantitatively assess the ground deformation velocities and rates and their natural and man-made controlling factors as the potential risks along the seismically active 70 km section of buried Baku-Tbilisi-Ceyhan Oil, South Caucasus Gas, Western Route Oil and South Caucasus Pipeline Expansion Gas pipelines in Azerbaijan using Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique. PS-InSAR analysis showed that the continuous subsidence was prevailing in the kilometer range of 13-70 of pipelines crossing two active seismic faults. The ground uplift deformations were observed in the pipeline kilometer range of 0-13. The minimum and maximum vertical ground movement velocities were observed to be −21.3 mm/y and 14.1 mm/y along 70 km section of pipelines with 250 m buffer zone. Both of these sites were observed at the range of seismic faults. The spatial distribution of sites with ground deformation velocity less than −15 mm/y and more than 15 mm/y was diverse and random all along 70 km of pipelines without any cumulative spatial patterns. Based on the lower mean, variation and standard deviation of pixel values, the seismic fault in the kilometer range of 21-31 revealed its higher vulnerability to subsidence processes rather than the Seismic Fault in the kilometer range of 46-54. The ground deformation velocities within the range of Seismic Fault KP21-31 revealed the minimum and maximum values of −19.74 mm/y and 14.1 mm/y, respectively whereas at the Seismic Fault KP46-54, the minimum and maximum values were −17.07 mm/y and 9.29 mm/y, respectively. Encouraging level of agreement with the regression coefficients of 0.92 and 0.96 for known subsiding sites at KP28 + 500 and KP52 + 750 and 0.97 and 0.96 for known uplifting sites at KP04 + 900 and KP35 + 050 respectively was observed between the high-precision GPS and PS-InSAR measurements. The diverse spatial distribution and variation of ground movement processes along pipelines demonstrated that general geological and geotechnical understanding of the study area is not sufficient to find and mitigate all the critical sites of subsidence and uplifts for the pipeline operators. The prediction of the potential subsidence or uplift locations based on the field visual verifications holds a lot of uncertainties without broad and detailed scale airborne and satellite space observation technologies. The justification of the budget for the geotechnical maintenance activities along long-range oil and gas pipelines requires sophisticated prioritization and planning of the remediation sites and clear quantitative and qualitative risk assessment proving the activeness of these sites and effectiveness of the remediation measures. This means that the PS-InSAR – based approach outlined in this paper is a significant improvement over current ground-based monitoring practices or can significantly contribute them in the initial phase of risk assessment and prioritization.

Study on the Pipeline Fragility Appraisal Indicators Affected by landslide Based on Numerical Simulation

The completeness of pipelines is tremendous influenced by landslide in unfavorable geological conditions. The quantifying appraisal techniques is a valid means for risk management of pipelines affected by geological disasters. By using the finite element method to simulate going steadily downhill, mechanics characteristic of pipeline and pipe/soil interaction with changes in physical dimension consisted of the landslide area (LA), landslide thickness (LT), pipeline length in landslide (PLL), calibre (CA) and wall thickness (WT) of pipeline, the fragility appraisal system of pipeline affected by landslide can be constructed. The regular pattern of stress and strain variation of pipeline affected by landslide can be acquired with number analysis and computeration. The results show that the physical dimension of landslide and the PLL have strong effect on pipeline fragility, and the effect increases with increasing of the above indicators; the WT has a smaller role of pipeline fragility and the effect can be ignored. In the end, the weighting factors and marks of every fragility appraisal indicator can be given on the basis of the above conclusion.

An integrated methodology to manage risk factors of aging urban oil and gas pipelines

Aging urban oil and gas pipelines have a high failure probability due to their structural degradation and external interference. The operational safety of the aging urban oil and gas pipeline is challenged by different hazards. This paper proposes a novel methodology by integrating an index-based risk evaluation system and fuzzy TOPSIS model for risk management of aging urban oil and gas pipelines, and it is carried out by evaluating the priority of hazards affecting pipeline safety. Firstly, the hazard factors of aging urban oil and gas pipelines are identified to establish an index-based risk evaluation system. Subsequently, the fuzzy TOPSIS model is employed to evaluate the importance of these hazard factors and to decide which factors should be managed with priority. This work measures the importance of a hazard factor from three aspects, i.e. occurrence (O), severity (S) and detectability (D), and the weights of these three parameters are determined by a combination weight method. Eventually, the proposed methodology is tested by an industrial case to illustrate its effectiveness, and some safety strategies to reduce the operational risk of the pipeline are presented. The proposed methodology is a useful tool to implement more efficient risk management of aging urban oil and gas pipelines.

Risk Assessment of Pipeline Failure Based on Fuzzy Analytic Hierarchy Process

Pipeline failure is a serious economic, environmental and safety issue. Risk assessment is an effective method to determine the risk of pipeline failure. This paper proposes an evaluation system. In the evaluation process, the fuzzy concept and method are used to transform the qualitative effect into quantitative fuzzy numbers based on linguistic variables. The weights are calculated by MATLAB software. Calculate the weight result and classify each indicator risk, and finally determine the pipeline failure risk level. Taking a section of the third-line pipeline of the West-East Gas Pipeline as an example, the fuzzy analytic hierarchy process is used for analysis. The two indicators of external corrosion and management system are medium risk grades, and the overall pipeline failure risk level is II (lower). The evaluation results show that the proposed evaluation system and method are effective and objective for evaluating pipeline failure risk. The pipeline failure assessment based on fuzzy analytic hierarchy process can not only objectively assess the risk status of pipelines, but also have a positive effect on improving pipeline risk management.

Risk evaluation of oil and natural gas pipelines due to natural hazards using fuzzy fault tree analysis

Oil and gas sector plays a major role in a country's economy. The development of large transmission pipelines for onshore and offshore gas transport is executed rapidly. These pipelines are vulnerable to natural disasters and can have a serious impact on the environment. The Potential damage to the pipeline infrastructure may contribute to increased risk of spill and thus can have an impact on the environment. Hence, the structural integrity of these pipelines is of great interest to the oil and gas companies, governments, and various stakeholders due to the probable environmental, infrastructural and financial losses in case of a structural failure. Fault tree analysis is an important risk assessment technique which treats the failure probabilities of the components as exact values for estimating the probability of the occurrence of a top event. Due to the lack of historical data for calculating the failure rate of pipelines due to natural hazards, this study aims to analyze the probability of pipeline failure by Fuzzy Fault Tree Analysis (FFTA) with expert elicitation. Fussel-Vesely Importance measures were utilized to rank the cutsets. The proposed FFTA framework was used to analyze the occurrence of top event even in the absence of historical probability data. The results are expected to be helpful to the safety professionals while making decisions related to the risk management of oil and gas pipelines.