Safety Length Simulation of Natural Gas Pipeline Subjected to Transverse Landslide

The safety of natural gas pipeline is often severely threatened by the transverse landslide. At home and abroad, it is the first time to study the safe length of the pipeline when affected by landslide, and take the safe length of the pipeline as an engineering practical index. Therefore, it is of great significance to study the influence of transverse landslide affecting the safety of natural gas pipeline when a certain length of pipeline is thrusted, and to establish practical index and simulation method for prediction and prevention of the landslide hazards to gas pipeline. Based on the current research results, this study could be divided into three steps: First of all, with the help of ANSYS finite element software, the model of transverse landslide acting on the gas pipeline can be set up, then the length value of gas pipeline safely withstanding transverse landslide can be calculated;Secondly, using the strength reduction method, which is commonly used in the research of landslide stability, can establish three-dimensional model of the landslide and pipes in the ABAQUS finite element software, next, under the same landslide pushed length, the calculation results will be obtained;Finally, to draw reliable conclusions, all calculated results of the former two methods will be linked to synthetically and comparatively analyze, then the length value of common X80 gas pipeline safely bearing transverse landslide can be got. All results can provide some references for engineering and design.

Improved AHP–TOPSIS model for the comprehensive risk evaluation of oil and gas pipelines

A comprehensive and objective risk evaluation model of oil and gas pipelines based on an improved analytic hierarchy process(AHP)and technique for order preference by similarity to an ideal solution(TOPSIS)is established to identify potential hazards in time.First,a barrier model and fault tree analysis are used to establish an index system for oil and gas pipeline risk evaluation on the basis of five important factors:corrosion,external interference,material/construction,natural disasters,and function and operation.Next,the index weight for oil and gas pipeline risk evaluation is computed by applying the improved AHP based on the five-scale method.Then,the TOPSIS of a multi-attribute decision-making theory is studied.The method for determining positive/negative ideal solutions and the normalized equation for benefit/cost indexes is improved to render TOPSIS applicable for the comprehensive risk evaluation of pipelines.The closeness coefficient of oil and gas pipelines is calculated by applying the improved TOPSIS.Finally,the weight and the closeness coefficient are combined to determine the risk level of pipelines.Empirical research using a long-distance pipeline as an example is conducted,and adjustment factors are used to verify the model.Results show that the risk evaluation model of oil and gas pipelines based on the improved AHP–TOPSIS is valuable and feasible.The model comprehensively considers the risk factors of oil and gas pipelines and provides comprehensive,rational,and scientific evaluation results.It represents a new decision-making method for systems engineering in pipeline enterprises and provides a comprehensive understanding of the safety status of oil and gas pipelines.The new system engineering decision-making method is important for preventing oil and gas pipeline accidents.

A liquid loading prediction method of gas pipeline based on machine learning

The liquid loading is one of the most frequently encountered phenomena in the transportation of gas pipeline,reducing the transmission efficiency and threatening the flow assurance.However,most of the traditional mechanism models are semi-empirical models,and have to be resolved under different working conditions with complex calculation process.The development of big data technology and artificial intelligence provides the possibility to establish data-driven models.This paper aims to establish a liquid loading prediction model for natural gas pipeline with high generalization ability based on machine learning.First,according to the characteristics of actual gas pipeline,a variety of reasonable combinations of working conditions such as different gas velocity,pipe diameters,water contents and outlet pressures were set,and multiple undulating pipeline topography with different elevation differences was established.Then a large number of simulations were performed by simulator OLGA to obtain the data required for machine learning.After data preprocessing,six supervised learning algorithms,including support vector machine(SVM),decision tree(DT),random forest(RF),artificial neural network(ANN),plain Bayesian classification(NBC),and K nearest neighbor algorithm(KNN),were compared to evaluate the performance of liquid loading prediction.Finally,the RF and KNN with better performance were selected for parameter tuning and then used to the actual pipeline for liquid loading location prediction.Compared with OLGA simulation,the established data-driven model not only improves calculation efficiency and reduces workload,but also can provide technical support for gas pipeline flow assurance.

Risk analysis and maintenance decision making of natural gas pipelines with external corrosion based on Bayesian network

Buried natural gas pipelines are vulnerable to external corrosion because they are encased in a soil environment for a long time.Identifying the causes of external corrosion and taking specific maintenance measures is essential.In this work,a risk analysis and maintenance decision-making model for natural gas pipelines with external corrosion is proposed based on a Bayesian network.A fault tree model is first employed to identify the causes of external corrosion.The Bayesian network for risk analysis is determined accordingly.The maintenance strategies are then inserted into the Bayesian network to show a reduction of the risk.The costs of maintenance strategies and the reduced risk after maintenance are combined in an optimization function to build a decision-making model.Because of the limitations of historical data,some of the parameters in the Bayesian network are obtained from a probabilistic estimation model,which combines expert experience and fuzzy set theory.Finally,a case study is carried out to verify the feasibility of the maintenance decision model.This indicates that the method proposed in this work can be used to provide effective maintenance schemes for different pipeline external corrosion scenarios and to reduce the possible losses caused by external corrosion.

Development of an integrated dynamic model for supply security and resilience analysis of natural gas pipeline network systems

An integrated dynamic model of natural gas pipeline networks is developed in this paper.Components for gas supply,e.g.,pipelines,junctions,compressor stations,LNG terminals,regulation stations and gas storage facilities are included in the model.These components are firstly modeled with respect to their properties and functions and,then,integrated at the system level by Graph Theory.The model can be used for simulating the system response in different scenarios of operation,and evaluate the consequences from the perspectives of supply security and resilience.A case study is considered to evaluate the accuracy of the model by benchmarking its results against those from literature and the software Pipeline Studio.Finally,the model is applied on a relatively complex natural gas pipeline network and the results are analyzed in detail from the supply security and resilience points of view.The main contributions of the paper are:firstly,a novel model of a complex gas pipeline network is proposed as a dynamic state-space model at system level;a method,based on the dynamic model,is proposed to analyze the security and resilience of supply from a system perspective.

State of art of seismic design and seismic hazard analysis for oil and gas pipeline system

The purpose of this paper is to adopt the uniform confidence method in both water pipeline design and oil-gas pipeline design.Based on the importance of pipeline and consequence of its failure,oil and gas pipeline can be classified into three pipe classes,with exceeding probabilities over 50 years of 2%,5% and 10%,respectively.Performance-based design requires more information about ground motion,which should be obtained by evaluating seismic safety for pipeline engineering site.Different from a city's water pipeline network,the long-distance oil and gas pipeline system is a spatially linearly distributed system.For the uniform confidence of seismic safety,a long-distance oil and pipeline formed with pump stations and different-class pipe segments should be considered as a whole system when analyzing seismic risk.Considering the uncertainty of earthquake magnitude,the design-basis fault displacements corresponding to the different pipeline classes are proposed to improve deterministic seismic hazard analysis(DSHA).A new empirical relationship between the maximum fault displacement and the surface-wave magnitude is obtained with the supplemented earthquake data in East Asia.The estimation of fault displacement for a refined oil pipeline in Wenchuan MS8.0 earthquake is introduced as an example in this paper.

A novel fuzzy approach to gas pipeline risk assessment under infuence 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 artifcial 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.

Reliability analysis of large-diameter high-grade-steel natural gas pipelines under fault action

There are a lot of researches on qualitative aseismatic measures for buried gas pipeline crossing movable faults.But a few of them are quantitative,especially in the size and shape of the trench.The paper first established the finite element model of the strain of buried pipeline crossing a fault which effected by the size and shape of the trench.And it obtained new soil spring stiffness which considered different buried depth,bottom width of trench,trench slope and elastic modulus of soil.The mechanical analysis model of pipeline is established,and the limit state equation of pipeline is fitted.The reliability and sensitivity of the natural gas pipeline under fault action are analysed by a Monte Carlo method,and the error and accuracy are verified.When the pipeline is under tension,the sensitivity from large to small is buried depth,sand friction angle,pipe diameter,pipeline displacement,trench bottom width,trench depth,clay cohesion,trench slope and clay friction angle;when the pipeline is under pressure,the trench depth and clay cohesion have great influence.The findings of this study provide a reference for pipeline design and safety evaluation under fault action.

Numerical evaluation of the effectiveness of frost heave mitigation strategies for chilled arctic gas pipelines

To prevent the thawing of ice-rich permafrost,it is suggested that gas should be transported in a chilled state(below the freezing temperature)in pipelines buried in permafrost.However,frost heave occurs when water migrates towards the chilled pipeline and ice lenses grow underneath the pipe.This might endanger the integrity of the pipeline and the environment as well.Therefore,innovative frost heave mitigation measures are required when designing the pipeline,especially those sections in discontinuous permafrost or near the compressor stations.The ground temperature field in response to the operation of a proposed chilled gas pipeline traversing permafrost regions in Alaska was simulated by a pipe-soil thermal interaction geothermal model.Frost heave mitigation measures,including insulation around the pipe,flat slab insulation under the pipe,and heating cables combined with slab insulation,were evaluated for chilled pipeline operation in seasonally varying ambient temperatures.The numerical results show that the minimum temperature of the observation point at 2.5 m below the pipe bottom increases by 17%,29%,and 48%when the thermal conductivity of the outer insulation layer is 0.1,0.05,and 0.02 W/(m K),respectively.For flat slab insulation,the thermal field is less sensitive to varying slab thicknesses than to varying thermal conductivity,implying the thermal conductivity,not the thickness,is the crucial factor.Additionally,the heat flow could be redirected from vertical to horizontal by flat slab insulation.The electrical heating cables could be regarded as a new heat source to balance the heat removal rate of the soil around the chilled pipe.The minimum temperature of the observation point at 1.1 m below the bottom of the pipe increases from-15.2℃to-3.0,1.5,and 7.5℃,corresponding to the heating cable power of 20,30,and 40 W,respectively,with the power of 30 W deemed appropriate for the study case.It is concluded that heating cables in combination with insulation slabs could be adopted to regulate the temperature field around the chilled pipeline efficiently and economically.The advantages of this combination include redirecting the heat flow and eliminating frost in the soil underlying the pipe.These approaches could be considered for applications in gas pipeline projects in arctic and alpine/high-plateau permafrost regions.

Analysing Delay Impact from Potential Risk Factors on Project Delivery of Oil and Gas Pipeline:A Case Study in IRAQ

The aim of this paper is to present the design and specifications of an integrated Delay Analysis Framework(DAF),which could be used to quantify the delay caused by the Risk Factors(RFs)in Oil and Gas Pipelines(OGPs)projects in a simple and systematic way.The main inputs of the DAF are(i)the potential list of RFs in the projects and their impact levels on the projects and the estimated maximum and minimum duration of each task.Monte Carlo Simulation integrated within@Risk simulator was the key process algorithm that used to quantify the impact of delay caused by the associated RFs.The key output of the DAF is the amount of potential delay caused by RFs in the OGP project.The functionalities of the developed DAF were evaluated using a case study of newly developed OGP project,in the south of Iraq.It is found that the case study project might have delayed by 45 days if neglected the consideration of the RFs associated with the project at the construction stage.The paper concludes that identifying the associated RFs and analysing the potential delay in advance will help in reducing the construction delay and improving the effectiveness of the project delivery by taking suitable risk mitigation measures.

Social and Economic Bene-fits of the West-East Gas Pipeline Project

On July 4 2002, a project attracting world attention, i.e., the West-East Gas Pipeline Project was declared in full-scale commencement. The project will write history with its enormous social and economic benefits.

China has Stepped into World Market in the Cause of Natural Gas Pipeline

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CNPC/EXXON/MITSUBISH Jointly Signing of Natural Gas Pipeline Study agreement

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