Third-party Damage Research Articles

Multistate Probabilistic Assessment of Third-Party Damage Risk for Oil and Gas Pipelines Based on DEMATEL-ISM-Røed-BN

Multistate Probabilistic Assessment of Third-Party Damage Risk for Oil and Gas Pipelines Based on DEMATEL-ISM-Røed-BN

Analysis of safety and impact probability of subsea Christmas tree impacted by falling objects

At present, there is no clear data to analyze the probability and impact of falling objects on the subsea Christmas tree. However, during the long-term operation in the complex deep-sea environment, objects may fall and hit the tree due to the anchored platform, fishing boat operation or other reasons, the impact of large heavy objects onto the tree can potentially give rise to the development of internal forces higher than those for which the tree was designed to. Therefore, aiming at the risk problem of falling objects, the paper presents the development process and results of an improved impact probability numerical method. And the safety model of falling object impact on the tree is established. Preliminary results indicate that the method offers valuable insight including and beyond a probability estimation of third-party damage, and the safety results were obtained. At the same time, the influencing factors of the tree impacted by falling objects are analyzed, and the serious influencing factors are obtained, which provides theoretical basis for the design and optimization of the protection frame of subsea square equipment.

Risk assessment and simulation of gas pipeline leakage based on Markov chain theory

Gas pipeline leakage may lead to fire, explosion and gas poisoning, thus causing a large number of injuries and property damage. This paper focuses on the chain characteristics presented by the development process of city gas pipeline leakage, based on Markov chain theory, studies the disaster-causing process and the mechanism of disaster chain formation for the leakage, establishes the disaster chain, evaluates the pipeline operation status and quantifies the failure probability of gas pipeline leakage to determine the causes of the leakage. Subsequently, Pipeline Studio is applied to simulate the consequences of gas pipeline leakage to realize the risk analysis. The analysis is based on Markov chain theory to calculate the probability of leakage and disaster-causing causes, analyze the consequences of gas pipeline leakage, and realize the diagnosis of the causes of gas pipeline leakage accidents and the prediction of the accident development trend. Finally, using European gas pipeline accident data to prove the effectiveness of the method, the result shows that gas pipeline leakage accidents are mainly caused by third-party damage and corrosion, which is consistent with the real situation and provides a reference for risk analysis and accident prevention of gas pipeline leakage.

Research on generation paths of production safety accidents in urban gas pipeline networks: A fuzzy set qualitative Comparative analysis (fsQCA) based on Chinese data

The production safety accidents in urban gas pipeline networks of China have shown a frequent trend in recent years, which has become the main obstacle to the high-quality development of urban gas industry. In this paper, based on 38 typical accidents that occurred in mainland China from 2012 to 2022, the fuzzy set Qualitative Comparative Analysis (fsQCA) method was applied to explore the accident generation paths. We identified seven condition variables and one result variable, then six condition configurations were derived through the fsQCA method to classify the accident generation paths into four types: "illegal operation", "Equipment failure", "third-party activities damage", and "multiple risk coupling". The results show that: (1) Interrupting the generation paths of accidents caused by illegal operation and multiple risk coupling not only requires local governments and regulatory departments to strengthen safety supervision, but also requires gas enterprises to improve their safety management organizational structures and safety production management systems; (2) Strengthening daily inspection, maintenance, and risk monitoring of urban gas pipeline networks is the core of curbing accidents caused by equipment failure; (3) Deepening cooperation between gas enterprises and third-party units is the key to prevent and control accidents caused by third-party activities damage; (4) Local governments and gas enterprises should strengthen cooperation to improve the effectiveness of accident prevention and control by building the risk synergetic governance model. This study provides theoretical guidance for preventing production safety accidents in urban gas pipeline networks of China.

Research on the vibration response characteristics of PE gas pipeline aimed for third-party damage monitoring

Third-party damage (TPD) incidents account for over 73% in China, becoming the primary cause of urban buried gas pipeline disruption. Therefore, real-time monitoring of TPD holds significance. This passage introduces a novel method for third-party damage monitoring of urban gas pipeline networks without excavation. The approach involves installing acoustic sensors in the pipeline to detect abnormal signals caused by construction activities. While the effectiveness of this method has been confirmed for buried steel pipelines, the propagation patterns, frequency characteristics, and the impact of fluid flow within PE pipelines remain unclear. To this end, this study explores these issues through experiments and simulations. According to the research, sound waves are the primary mode of signal propagation. The impact of gas pressure can be disregarded, but if the flow is reversed, the signal will weaken by 26%. The signal energy is concentrated in the 0–2 kHz range, decreasing exponentially as the distance increases. Moreover, a positive linear correlation exists between the signal energy and the load size to the power of 0.1. This research provides theoretical support for studying third-party damage monitoring technology and identifying and localizing damage types.

Experimental study on leakage characteristics of gas-liquid two-phase flow in a horizontal pipe

Oil and gas pipeline leakage accidents caused by aging and third-party damage have increased, resulting in polluting the ecological environment and jeopardizing life and property safety. A detailed and systematic investigation on the leak characteristics of oil and gas two-phase pipelines is significantly urgent. The leak experiments were performed on a horizontal tube with a diameter of 32 mm. There was a 3 mm round leakage hole at the bottom of the tube. The distance of the leakage hole from the pipe inlet was 4.8 m. Three inlet flow patterns, including stratified flow, slug flow, and annular flow via adjusting the gas superficial velocity (1.73 m/s ≤ USG ≤ 24.19 m/s) and liquid superficial velocity (0.017 m/s ≤ USL ≤ 0.415 m/s), were obtained. The conclusions point out that the type of leakage, whether it is mainly liquid or both gas and liquid, depends on the USG. The degree of phase separation in stratified flow is the greatest among the three inlet flow patterns, with a maximal phase separation efficiency (η) of 0.403. Slug flow has the least phase separation degree. Interestingly, the η is directly proportional to the inlet mass fraction only for slug flow. The harmonic frequency that appeared in the power spectral density curves for the pressure difference of leakage hole in slug flow, indicates that leakage is not a standard periodic event. The liquid velocity loss is primarily related to the gas leakage mechanism. These findings can provide new insights into two-phase pipeline leak detection and accident consequence prediction.

Comparing the risk of third-party excavation damage between natural gas and hydrogen pipelines

Existing natural gas pipelines can facilitate low-cost, large-scale hydrogen transportation and storage, but hydrogen may entail safety challenges. These challenges stem from hydrogen’s different properties compared to natural gas, such as higher ignition probability, different flame behavior, and potential for hydrogen embrittlement. Although risk assessments for hydrogen pipelines are increasing, the impact of hydrogen on the risk of third-party excavation damage (TPD), the major cause of pipeline incidents in the U.S., has received little attention. This work presents the SHyTERP model for Safe Hydrogen Transportation and Excavation Risk Prevention for Pipelines. The model incorporates causal models, excavation damage and pipeline failure statistics, and validated physical models of hydrogen and natural gas release and jet flame behavior. Through four case studies, the model compares the TPD risks of hydrogen and natural gas pipelines, offering insights and recommendations for the safe implementation of hydrogen in existing pipelines.

Evaluation of disaster-bearing capacity for natural gas pipeline under third-party damage based on optimized probabilistic neural network

Third-party damage has become a significant factor leading to pipeline failures and leaks, resulting in severe ecological damage and human casualties. Traditional safety risk analysis methods in the past have focused on severing the causal chain of accidents, while neglecting the unique characteristics of different pipeline segments and environmental factors on their ability to bearing disasters. This paper presents a framework for evaluating the disaster-bearing capacity of natural gas pipeline third-party damage based on probabilistic neural networks. A comprehensive disaster-bearing capacity index system for evaluating third-party damage to natural gas pipelines has been constructed by analyzing the causal factors and potential consequences of third-party damage risk incidents. Next, the cluster analysis and indicator weighting information is used for achieving the comprehensive disaster-bearing capacity assessment. Finally, the data samples are constructed with the index levels and comprehensive disaster-bearing capacity levels of each evaluation unit. An optimization algorithm, Particle Swarm Optimization (PSO), is utilized to improve the parameter selection process of the Probabilistic Neural Network (PNN) model, in order to evaluate the disaster-bearing level of each unit. A typical long-distance natural gas pipeline in Zhejiang Province was selected as the case study, and a total of 200 research units were obtained through pipeline analysis. Furthermore, 14 indicator data were obtained by leveraging multiple sources of data surrounding the pipeline. With the utilization of cluster analysis, it was determined that Gaussian mixed model clustering method ultimately identified a total of 5 different levels of disaster-bearing capacity. The optimal smoothing factor can be accurate from 0.5 to 0.588 by using the PSO-PNN model, and the final accuracy rate is improved from 88% to 98%, which is obviously the introduction of PSO optimization algorithm in the PNN model can improve the accuracy of the model. This represents a significant improvement in accuracy when compared to traditional PNN models. The proposed evaluation method can provide scientific basis for the prevention and control of third-party damage in oil and gas pipelines and pipeline planning.

Dynamic risk assessment model for third-party damage to buried gas pipelines in urban location class upgrading areas

Buried gas pipeline leakage accidents caused by third-party interference in urban location class upgrading areas are time-varying and can cause serious consequences. This study proposed an integrated dynamic risk assessment model to address this issue. First, a bow-tie model combining a fault tree (FT) with an event tree (ET) was used to construct an overall evolutionary process from basic events to accidents and thus mapped into a Bayesian network (BN). The prior probabilities of basic events in FT and safety barriers in ET were determined by four types of methods, and the critical basic events were identified by sensitivity analysis. By integrating the Hierarchical Bayesian analysis method with time-varying precursor data, the dynamic probability updating of critical basic events and safety barriers was achieved, enabling adaptation of accident probabilities using BN. Then, a dynamic calculation method for accident consequences was proposed by integrating the appropriate leakage rates with a new time-varying method for calculating fatalities. Finally, a new risk matrix method was proposed to dynamically evaluate the risk level by integrating the accident probabilities with the consequences. A case study showed that the proposed model could dynamically evaluate the integrated accident risk, providing explicitly quantified support for risk management and emergency rescue of buried gas pipeline networks in urban location class upgrading areas.

Numerical investigation on the migration of leaked pollutants after liquid pressurized pipeline leakage regarding oil and gas parallel pipelines situation

Buried parallel pipelines may cause environmental pollution and explosive accidents after leakage due to corrosion, third-party damage or other factors. Here, an actual oil pipeline in-situ is employed as a prototype to establish a two-dimensional incompressible leakage and diffusion model. The model was applied to analyze the effects of different parameters including pipe diameters, burial depths and flat spacing to other pipelines on the diffusion distance of spilled diesel fuel in porous media. The results show that the existence of natural gas pipeline can change both of the polluted shape and the distance range. The natural gas pipeline can effectively inhibit the diffusion range of diesel with the increase of pipe diameter and the decrease of buried depth. A smaller spacing between parallel transmission pipelines, also results in a reduced horizontal diffusion rang. Meanwhile, the dimensionless formulas are fitted based on the Π theorem regarding diesel diffusion range versus diameter of gas pipeline, buried depth, and spacing between parallel pipelines. This study can develop appropriate protocols for detecting and recovering contaminants from paralleling pipeline.

Early Detection and Identification of Damage in In-Service Waterworks Pipelines Based on Frequency-Domain Kurtosis and Time-Shift Coherence

Buried pipelines, such as waterworks pipelines, are critical for transmitting essential resources and energy in modern cities, but the risk of pipeline failure, especially due to third-party interference, is a major concern. While various studies have focused on leak detection in waterworks pipelines, research on preventing impact damage is limited. To address this issue, this study proposes a novel algorithm that utilizes energy and similarity measurements for impact detection and compares it theoretically to existing leak-detection methods. The proposed algorithm utilizes frequency-domain kurtosis to determine the frequency band on which the energy of the impact signals is concentrated, along with a time-shift coherence function to measure the similarity of the signals. The application of the source location using the filtered signals enables accurate detection of the location of third-party interference. The proposed algorithm aims to ensure the safety and to prevent failures of buried pipelines. To verify the feasibility of the proposed algorithm, an excavation experiment using a backhoe was conducted on an in-service waterworks pipeline with a diameter of 2200 mm and a burial depth of 3 m. This experiment confirmed the effectiveness of the proposed algorithm in preventing failures of buried pipelines and demonstrated its practical applicability in the field. The experiment also validated the algorithm’s ability to detect third-party interference damage at various points.

Effects of Pipeline Pressure on Diffusion Characteristics of Leaked Natural Gas in Tunnel Space.

Pipeline transportation has become the main mode of natural gas transportation. Due to inevitable aging, corrosion, and third-party damage, natural gas pipeline leakage accidents occur frequently. Leakage in the tunnel will lead to the leakage and accumulation of natural gas, and the potential explosion risk will threaten the tunnel's safety. It is significant to elaborate on the diffusion behavior of leaked natural gas in tunnel space for the traceability of leakage points and the formulation of safety technical measures. In this paper, a scale-down experimental platform for natural gas pipeline leakage in the tunnel is built, and the influence of pipeline pressure on natural gas diffusion characteristics is described. The results show that the diffusion process of leaked natural gas in the tunnel space shows obvious segmentation characteristics, and the concentration of natural gas reaches the maximum at the end of the continuous leakage stage. The increased pipeline pressure promotes natural gas diffusion, and the concentration of natural gas under 1.0 and 1.2 MPa rises sharply. First dangerous time (FDT) and maximum accumulated concentration (MAC) have a negative correlation with the leakage distance, while FDT and MAC have a good exponential and linear relationship with the pipeline pressure (0.2-1.2 MPa), respectively.

Evaluation of Methane Emissions in Daily Operations and Accidents: A Case Study of a Local Distribution Company in China

As the second-largest contributor to historical global warming, methane emissions must be controlled to slow down temperature increase and achieve climate benefits. Due to a lack of knowledge about the specific sources and processes, a quantitative approach will lead to inaccurate estimation. In this paper, a typical local distribution company with more than 100 years of operation history was chosen. Detailed procedures of pipeline constructions and accidents were investigated, and critical steps leading to methane emissions were clarified. Then emission quantification methodologies for all processes were proposed, including a new pipeline connection, new regulator connection, emergency repair and third-party damages. As a basis for emission estimation, the distribution of parameters, such as diameter, length and pressure, was counted. Then the emission rates of all projects were calculated, and emission factors were established. The average emission rates of the new pipeline connection, new regulator connection, emergency repair, third-party damage (medium pressure) and third-party damage (low pressure) were 234 kg, 147 kg, 217 kg, 17,282 kg and 62 kg, respectively. In addition, the total methane emission in China from these sources was estimated to be about 5 × 104 t, which is large enough to attract attention. The work in this paper aims to establish a reasonable framework to evaluate venting methane emissions from the distribution process of natural gas.

Dynamic Bayesian network risk probability evolution for third-party damage of natural gas pipelines

Failure and leakage of natural gas pipelines can lead to serious ecological losses and casualties. Third-party damage has become an important cause of pipeline failure and leakage, which urgently needs an accurate risk assessment method to assess the risk. Conventional qualitative risk analysis methods can only point out the critical events of failure accidents but fails to predict the failure probability. This paper proposes a dynamic risk probability analysis method based on Dynamic Bayesian network (DBN), which is validated by a third-party damage case under uncertainty. First, human factors are taken as the main analysis object in the risk analysis, by which two subcategories of intentional and unintentional factors are classified. A complete risk factor analysis is performed by combining expert recommendations with the fault tree analysis method and developing a coupled model with the event sequence diagram. Second, in order to deal with the uncertainty of risk factors, the coupled model is mapped to a DBN model. The prior probabilities of the input DBN model are obtained by database, fuzzy set theory, and Dempster-Shafer evidence theory. Weibull distribution is applied to construct the probability transfer process between time segments, which better fits the characteristics of third-party disruptive factors in onshore pipelines. Finally, the practicality and advantages of the proposed method are demonstrated by a real case study, which identifies 6 critical events and predicts the probabilistic information in different time slices. Furthermore, the method predicts the probability of failure events and potential consequences by processing the time series information, and it is found that the probability of structural damage and explosion is higher than other consequences. In this way, some risk management countermeasures are proposed in a targeted manner. The results show that compared with the conventional BN model which only performs probabilistic inference once, the DBN model can perform temporal dynamic inference to achieve the prediction of failure probability, and it can effectively achieve the numerical prediction of risk failure probability.

Study on risk prevention and control of third-party construction damage of underground pressure pipelines

The utilization scale of underground pressure pipelines such as gas, heat and water supply pipelines is increasing, and pipeline accidents occur frequently, among which the third-party construction damage has become one of the main factors, so it is crucial to prevent and control the risk of third-party construction damage. This paper probes into the risk prevention and control measures for the third-party construction damage of underground pressure pipelines from four aspects of management, laws and regulations, science and technology and culture. The research results show that only by taking into account the standardized management, restriction of laws and regulations, scientific and technological support, and cultural publicity, can the third-party construction damage risks of underground pressure pipelines be effectively prevented and controlled.

An integrated risk assessment methodology based on fuzzy TOPSIS and cloud inference for urban polyethylene gas pipelines

Due to the superior performance of polyethylene (PE) gas pipes, an increasing number of PE pipelines are being used in urban areas. However, PE gas pipelines are basically located in densely populated areas with high consequences. Once a leak occurs, combustion and explosion accidents can easily happen causing a major threat to human life and property. Furthermore, the assessment results of the common risk assessment methods often have great uncertainty and deviation. It is difficult to accurately identify the main indicators that need priority management. To address these problems, this paper proposes a novel methodology by integrating a fuzzy TOPSIS model and cloud inference for conducting risk assessments of urban PE gas pipelines. The developed methodology is composed of two branches. In the first branch, a rapid risk assessment model for PE pipelines is established to determine whether there are some special emergency situations, which can be directly identified as high risk. In the second branch, a detailed risk assessment process is adopted to obtain the final result, which mainly includes risk factor analysis, risk status assessment and risk classification. Among them, risk factor analysis is used to establish a risk index system and develop a risk index management strategy by means of mathematical statistics and the fuzzy TOPSIS analysis method. The risk status assessment is used to determine the final risk value based on the virtual cloud and fault tree analysis, which is mainly realized by the triangular fuzzy number, structural entropy weight method and backward cloud transformation algorithm. Finally, the risk assessment results of PE gas pipelines are clearly presented in the form of cloud inference, and the final risk classification is determined. The case study shows that the pipeline in this section is at the medium risk level, and the management of time-related indicators and third-party damage is given priority. The result is consistent with the actual situation, which verifies the effectiveness and practicability of the methodology.

Third-Party Damage Model of a Natural Gas Pipeline Based on a Bayesian Network

Natural gas plays an important role in the transition from fossil fuels to new energy sources. With the expansion of pipeline networks, there are also problems with the safety of pipeline network operations in the process of transportation. Among them, third-party damage is a key factor affecting the safety of pipelines. In this paper, the risk factors of third-party damage are analyzed, and an evaluation model of natural gas pipeline damage is established using the GeNIe Modeler. Through Bayesian network reverse reasoning and a maximum cause chain analysis from the four aspects of personnel, environment, management, and equipment, it was found that the top five factors that have significant influence on third-party damage, are safety investment, the completeness of equipment, safety inspection frequency, the management of residents along the pipeline, and safety performance, with the posteriori probability in the model of 97.3%, 95.4%, 95.2%, 95.1%, 95.1%, respectively. Consequently, it is necessary for pipeline operation companies to secure investment on safety, to make sure that the safety equipment (system) works and is in a good condition, to maintain the safety inspection frequency in an organization, to build a management system for residents along the pipeline, and to conduct routine safety performance assessments accordingly.

Acoustic Pressure Simulation for Fluid Piping Leakages

Pipelines laid over long distances in the onshore environment may be affected by excessive straining, corrosion, the collapse of soil and other third-party damages. Small chronic leaks may cause severe safety and environmental effects if left undetected for a long time. Any potential onshore leaked water source may not be detected for a long time and could lose a considerable water source volume under the ground. Thus, this study aims to determine the leakage pipeline based on the acoustic analysis. Three different models of leakage pipeline had modelled: single leakage with 110mm in pipe diameter, single leakage with 185mm in pipe diameter and two leakages with 110m in pipe diameter. The computational fluid dynamic method was used to simulate the acoustic effect on the leakage pipeline. The results showed that the differential pressure to the leakage pipeline has a significant impact on the sound pressure level and turbulence kinetic energy. Furthermore, the turbulence kinetic energy was proportional to the sound pressure level through the comparison made for each model. Thus, this study manages to enrich the knowledge on the acoustic as well as facilitate understanding the behaviour of leakage pipes for future leaks detection analysis.

Risk Classification of Shale Gas Gathering and Transportation Pipelines Running through High Consequence Areas

Shale gas gathering and transportation pipeline poses significant risk due to special geographical conditions and different climatic conditions in high consequence areas such as Sichuan and Chongqing. The risks become critical as gas pipelines run through high consequence areas such as hospital, market, and scenic areas. This study presents a risk classification method for the pipelines running through high consequence areas. The proposed method considers different failure scenarios including third-party damage, corrosion, design and construction defects, mis-operation, and natural disasters. The method uses subjective and objective data from different sources. To minimize the subjectivity and data uncertainty, an improved fuzzy analytic hierarchy process was used to process data. The estimated risk is used to classify different risk zones. After the failure of shale gas pipelines in HCAs, in order to reduce the adverse impact of emergencies, personnel should immediately organize an evacuation to a safe area, focusing on the diagnosis and analysis of risk factors that are more likely to lead to pipeline leakage. The developed classes are verified using field data. The study observes that risk levels classified using the proposed method provide realistic assessments of hazard zoning. Risk zoning will help develop effective risk management strategies.

An efficient adaptive combined filtering method for pipeline bending strain based on inertial in-line inspection

Long-distance high-pressure oil and gas pipelines are threated by various external forces, such as earthquakes, landslides, and other third-party damages. These additional stresses will cause the pipeline to move and bend, which not only causes the pipeline to undergo a large bending strain, but will also causes the pipeline to fail in severe cases. In-line inspection (ILI) based on strapdown inertial navigation technology has become an effective inspection method for long-distance pipelines in recent years. However, the cups or support wheels of the ILI tool encounter the pipe wall, girth or spiral welds, and other features that lead to minor oscillations and vibration during the inspection. The attitude information computed by the inertial measurement unit (IMU) is affected by these noises, and the computation of pipeline bending strain (PBS) is inaccurate. In this paper, an efficient adaptive combined filtering method based on wavelet transform with Savitzky–Golay (S-G) is proposed, which is adaptable to the variation of attitude information for the ILI tool during a long distance and time inspection. Experiments were conducted to demonstrate the effectiveness of the optimization for PBS. The average relative deviation decreased from 38.3% to 18.3%.