Natural Gas Pipeline Operations Research Articles

Optimization research on energy consumption and carbon emissions in hydrogen-blended natural gas pipeline networks considering compressor performance - A case study of the west-east gas pipeline (line 1)

The blending of hydrogen into natural gas can utilize existing natural gas pipeline infrastructure to achieve long-distance, large-scale, and cost-effective hydrogen transportation. However, the introduction of hydrogen poses a series of new technical and safety challenges to the operation of natural gas pipelines. Addressing these issues, this paper focuses on minimizing compressor station energy consumption and carbon emissions as objective functions, conducting a comprehensive analysis of station operation modes. Incorporating the characteristics of the model, the soft frost search strategy, the hard frost penetration mechanism, and the positive greedy selection mechanism are introduced to propose the IRIME algorithm. Comparisons are made with well-performing optimization algorithms using classical test functions to evaluate algorithm performance. To further validate the algorithm's accuracy, the West-East Gas Pipeline (Line 1) is considered, comparing the convergence speed and precision of the IRIME algorithm, leading to its selection for solving the model. Furthermore, consider analyzing the impact of different hydrogen blending ratios on the performance curves and operating points of compressors. Results indicate that compared to conditions without hydrogen blending, the compressor outlet temperature and pressure drop increase for hydrogen blending ratios of 5%, 10%, 15%, and 20%; as the hydrogen blending ratio increases, the efficiency of fuel-driven compressors, efficiency of electrically driven compressors, and average efficiency of compressor units decrease; with an increase in hydrogen blending ratio, carbon emissions from fuel-driven compressors and electric-driven compressors both decrease. In conclusion, with an increasing hydrogen blending ratio, total energy consumption increases by 3.14%, 5.69%, 8.68%, and 10.90%, while total carbon emissions decrease by 2.99%, 5.36%, 8.32%, and 10.68%. These findings provide valuable insights for operational guidance in the field.

Automatic response framework for large complex natural gas pipeline operation optimization based on data-mechanism hybrid-driven

In recent years, the scale of gas transmission networks has been continuously expanding, and the operational conditions are becoming increasingly complex. This poses higher requirements for the centralized control of the pipeline network operation. Relying solely on the experience of scheduling personnel may not comprehensively address the operational issues within the network. There is an urgent need for efficient automatic response methods (ARM) to assist in formulating operation schemes and ensuring the safe and stable operation of the pipeline network. Therefore, this paper proposes an automatic response framework of large complex natural gas pipeline operation optimization based on data-mechanism coupling to provide operation schemes that ensure safety, stability, and economic benefits. First, two ARM is proposed, namely the Data-Based ARM using operation scheme database, and the Opti-Model ARM based on optimization modeling. Subsequently, the rapid response features of Data-Based ARM and the optimal response characteristics of Opti-Model ARM are combined to establish the Integrated ARM. Finally, these three ARMs are compared and analyzed through a regional natural gas pipeline network in China. The result indicates that the Data-Based ARM can quickly produce a variety of matched solutions but cannot ensure economic optimality. Response solutions obtained through Opti-Model ARM reduce the compressor energy costs by 4.6-10.8% compared to on-site operational schemes, but they take longer in response time. In contrast, the economic attributes of solutions derived from the Integrated ARM are on par with Opti-Model ARM, but with a 58.7% improvement in response speed. The proposed Integrated ARM can swiftly and accurately offer economically viable operation schemes tailored to the varying needs of pipeline operators, which can help to address the energy demand challenges of the future, fostering sustainable development.

Numerical Research on Leakage Characteristics of Pure Hydrogen/Hydrogen-Blended Natural Gas in Medium- and Low-Pressure Buried Pipelines

To investigate the leakage characteristics of pure hydrogen and hydrogen-blended natural gas in medium- and low-pressure buried pipelines, this study establishes a three-dimensional leakage model based on Computational Fluid Dynamics (CFD). The leakage characteristics in terms of pressure, velocity, and concentration distribution are obtained, and the effects of operational parameters, ground hardening degree, and leakage parameters on hydrogen diffusion characteristics are analyzed. The results show that the first dangerous time (FDT) for hydrogen leakage is substantially shorter than for natural gas, emphasizing the need for timely leak detection and response. Increasing the hydrogen blending ratio accelerates the diffusion process and decreases the FDT, posing greater risks for pipeline safety. The influence of soil hardening on gas diffusion is also examined, revealing that harder soils can restrict gas dispersion, thereby increasing localized concentrations. Additionally, the relationship between gas leakage time and distance is determined, aiding in the optimal placement of gas sensors and prediction of leakage timing. To ensure the safe operation of hydrogen-blended natural gas pipelines, practical recommendations include optimizing pipeline operating conditions, improving leak detection systems, increasing pipeline burial depth, and selecting materials with higher resistance to hydrogen embrittlement. These measures can mitigate risks associated with hydrogen leakage and enhance the overall safety of the pipeline infrastructure.

GTFE-Net-BiLSTM-AM: An intelligent feature recognition method for natural gas pipelines

The recognition of pipeline features contributes to its safe management by preventing severe consequences such as leakage resulting from bending deformation and denting under external pressure. However, extracting features of such a facility is complex and challenging when machine learning techniques are applied to feature recognition. Hence, this paper proposes a feature recognition technique for gas pipelines based on Gramian Time Frequency Enhancement Net (GTFE-Net), Bi-directional Long Short-Term Memory (BiLSTM) and attention mechanism (AM), namely GTFE-Net-BiLSTM-AM. Specifically, GTFE-Net is applied to enhance the time-frequency input bending strain signal, which is subsequently incorporated with the BiLSTM model to extract spatio-temporal features. The attention mechanism computes the corresponding weight of output features. The results show that the proposed method's recognition accuracy reaches 93.7%. The comparison study with the existing models validates the proposed method's superiority and shows that its accuracy is higher than that of the existing models (more than 0.9%) or their combined models (more than 1.1%). Overall, the proposed method contributes to the safety, reliability, and operation of natural gas pipelines.

Leak Detection in Natural Gas Pipelines Based on Unsupervised Reconstruction of Healthy Flow Data

Summary Timely detection of leak accidents plays an essential role in the safe operation and risk assessment of natural gas pipelines. However, the scarce leak data and complex operating conditions lead to small samples, data imbalance, and problems with confusing operating conditions. The reliance on leak data limits the recognition performance of the artificial intelligence classification method for leakage operating conditions. A leak detection method based on the unsupervised reconstruction of healthy flow data is established to address these problems. First, an unsupervised neural network is established to reconstruct healthy flow data from real natural gas pipelines. And a model update strategy based on active learning is designed to improve the model’s adaptability for time-varying pipelines. Next, a dynamic alarm threshold strategy that accounts for the knowledge of the experience and statistical characteristics of the data segments is suggested to prevent false alarms caused by ambiguous operating conditions. Finally, unlike most recent work that only considers simulated data or laboratory data, this paper conducts a leak case study on an actual natural gas pipeline in service to improve the robustness of the proposed method in the actual operating environment. The findings of this paper can be used as a reference to analyze pipeline behavior analysis based on pipeline flow trend characteristics and early alarm management.

BI-IEnKF coupling model for effective source term estimation of natural gas leakage in urban utility tunnels

As an effective way to facilitate the increasing demand for reliable infrastructure, energy supply and sustainable urban development, underground utility tunnels have been developed rapidly in recent years. Due to the widespread distribution of utility tunnels, the safe operation of natural gas pipelines accommodated in utility tunnels has caused great concern considering fire, explosion, and other coupling consequences induced by the gas pipeline leakage. However, the limited information on leakage source terms in accidental leakage scenarios could preclude timely consequence assessment and effective emergency response. In this study, a BI-IEnKF coupling source term estimation (STE) model is developed, with the combination of gas dispersion model, Bayesian inference (BI) and iterative ensemble Kalman filter (IEnKF) method, to achieve the effective source term estimation (including leakage location and leakage rate) and gas concentration distribution prediction. The newly developed model is first evaluated by the twin experiment with good reliability and accuracy. Furthermore, three contributing factors affecting the performance of the developed BI-IEnKF coupling STE model were investigated to assist parameter selection for practical use. Additionally, the novel application of mobile sensors serving as an alternative for fixed sensors is explored, and an application framework is sequentially given to guide the deployment of the developed coupling model in utility tunnels. The results show that the developed model has great performance in accuracy, efficiency and robustness, as well as the potential to be applied in actual utility tunnel scenarios. This study can provide technical supports for safety control and emergency response in the case of natural gas pipeline leakage accidents in utility tunnels. Also, it could be helpful to reasonable references for gas lekage monitoring system design.

Failure analysis and control of natural gas pipelines under excavation impact based on machine learning scheme

Third-party excavation operations pose a serious threat to the safe operation of natural gas pipelines, and quantifying the failure conditions of pipelines can effectively identify the hazards of excavation operations. Considering the current lack of test data on the full-size critical conditions of pipelines under different failure modes, to make the research results have better field application, this study aims to develop a failure prediction model, which is adopted for predicting the failure modes of the pipeline under different excavation conditions in order to propose control strategies. In this work, finite element analysis is combined with machine learning algorithms. The finite element analysis process derives the critical loads for different failure modes of the pipe and establishes the failure condition data set. Correlation analysis and sensitivity analysis were employed to investigate the influence pattern of the features. The prediction performance of different machine learning combination algorithms was tested, and a hybrid data-driven prediction model was established and combined with the excavation equipment parameters to determine the risk level of the excavation equipment and the risk area of the operation. The results demonstrate that the critical load value for failure grows when the strength of the pipe increases. The four features of yield strength, strength limit, pipe diameter, and wall thickness exhibit the highest importance scores. The bucket tooth wedge angle only influences the magnitude of the puncture critical load, with correlation and sensitivity coefficients being 0.315 and 0.116, respectively. In the test of the combined algorithm, the RFECV-CSVR-NSGAIII algorithm built in this study has the highest generalization performance, the mean absolute error percentage (MAPE) is lower than 0.0476, the coefficient of determination R2 reaches over 0.9960, and the prediction model has excellent accuracy. The prediction model was subjected to case studies to obtain rapid identification of risk levels and operational risk areas of excavation equipment.

Risk Prioritization in a Natural Gas Compressor Station Construction Project Using the Analytical Hierarchy Process

Recently, the seamless construction and operation of natural gas pipelines has become even more critical, while the oil and gas industry’s capability to operate effectively with acceptable risks and hazardous situations is mainly dependent on safety. As a result, it is very important to have a wide knowledge of effective management tactics for enhancing implementation of safety regulations and procedures. The problem of assuring workers’ health and safety in the workplace is a crucial component in the endeavor to raise the productivity of labor and the level of competitiveness of building projects. To promote the health, safety, and well-being of workers, issues that are embedded within the concept of sustainability, we propose in this study a safety risk-assessment process that uses the analytical hierarchy process for assigning priorities to risks on construction worksites. This process uses a popular multicriteria method. The success of this strategy was shown by its application to the building of a natural gas compressor plant in Greece. The main contribution of this study is the application of a well-known multicriteria method for assessing risks in a natural gas compressor station construction project and prioritizing hazards to allocate budget for risk-mitigation measures.

Dependence of flow coefficient on the cone angle and relative opening of natural gas control ball valves

Natural gas control ball valves are fluid control devices that regulate the flow and direction of the medium in a natural gas transportation system, and nowadays the requirements for valve intelligence are increasing. To implement the intelligent control of the valve system, the precise acquisition of the operating parameters of the control ball valve was studied in this paper. A numerical simulation of the internal flow field of a V-shaped ball valve was conducted based on a finite volume method and an renormalization group (RNG) k–ε turbulence model. A valve performance test bench was established, and the pressures at the inlet and outlet of the valve at various relative openings were measured, in which the accuracy of the numerical model was verified. Through numerical simulations, the internal flow characteristics at various relative openings and spool cone angles were studied. By comparing the influence of three different relative openings on the valve internal flow field, it was found that the valve showed better flow characteristics under the relative opening of 80%, and the increase of the cone angle effectively improved the unstable flow in the valve. An accurate expression between the external parameters of the valve operating condition and the internal flow was established, and the expression is the theoretical basis to implement intelligent control. This study provides strong technical support for an efficient operation of natural gas pipelines.

Exploration on Centralized Monitoring and Management Operation of Long-distance Natural Gas Pipeline

Exploration on Centralized Monitoring and Management Operation of Long-distance Natural Gas Pipeline

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.

Study on influencing factors and monitoring cycle of wall thickness at key locations of natural gas station

In recent years, the safe and stable operation of natural gas pipeline has become the focus of the whole society. Long distance natural gas pipelines are mostly large-diameter and high pressure pipelines, so their safe operation is particularly critical. In the high-pressure natural gas pipeline transportation industry, the wall thickness of key points (elbows and tees) will be thinned due to long-term erosion of gas, resulting in serious consequences. Therefore, its wall thickness monitoring is a key work of long-distance natural gas pipeline operation units. At present, most of them adopt off-line monitoring, but the standardized monitoring cycle cannot be effectively determined, and there are no relevant standards in the industry. The author uses fluent simulation software to establish the model, and then modifies the model combined with the field data. Then, the model is used to analyze the influencing factors of key points (elbow and TEE) one by one, and select more important influencing factors to formulate the monitoring cycle of different points. The monitoring cycle can provide reference for the daily work of on-site operators, and then ensure the safe and stable operation of long-distance natural gas pipeline.

Comparison of finite-volume method and method of characteristics for simulating transient flow in natural-gas pipeline

In this study, two numerical methods of modeling transient flow in a single natural-gas pipeline are analyzed and compared. Specifically, the pressure-based finite-volume method (FVM)—which uses a collocated mesh with the total variation diminishing (TVD) scheme—and the conventional implicit method of characteristics (iMOC)—which uses an inertial multiplier—are considered. Network analysis is an essential part of the design and operation of natural-gas pipelines. Studies have been conducted on various numerical methods to analyze the transient flow of natural-gas pipelines, but comparative studies on the characteristics and relative advantages and disadvantages of the methods are inadequate; therefore, it is necessary to analyze and compare the underlying numerical methods to ensure their reliability. Accordingly, two test cases are considered: slow transient flow validated with experimental data, and fast transient flow with an artificial problem including valve stroking. The two methods are examined quantitatively and qualitatively. The order of accuracy, determined using the grid-convergence index, and the computational cost are evaluated for quantitative analysis. Overall, the pressure-based FVM with the TVD scheme outperforms iMOC for both slow and fast transient problems.

Environmental analysis for the selection of long-distance natural gas pipeline routes using MACBETH

PurposeReliable operation of natural gas pipeline (NGP) is a critical factor in Iran’s economic development. NGP projects go through different ecosystems and considerably affect the environment. Environmental analysis is an essential step toward sustainable development. Tackling the challenges, this paper aims to develop a framework to systematically assess the environmental impact of NGPs.Design/methodology/approachThis study proposes a comprehensive framework for environmental impact analysis of NGPs using Measuring Attractiveness by a Categorical-Based Evaluation Technique (MACBETH). MACBETH protocol is used to calculate the overall environmental scores of projects.FindingsThe results indicate that the impact of implementing NGPs on protected areas is of the highest priority, while the impact on vegetation covers is of least priority for assessing the environmental impact of NGP.Practical implicationsThe practicality and validity of the model in the case of three candidate routes for the Polkale-Neizar project in Iran are examined. According to the results, the third alternative is selected based on its non-interference in protected areas and less environmental impacts. The proposed model can be modified and applied to perform environment appraisal of other linear projects such as energy, road and railway networks.Originality/valueThis model addresses a range of environmental impacts of implementing NGPs at two levels, with the second level being non-additive. The novelty of this study translates into considering the qualitative and quantitative features of each evaluation criterion applied to linear projects simultaneously using a multi-criteria value measurement.

Numerical investigation of gas-liquid hydrodynamics during trapped-liquid displacement from low sections of high-pressure gas pipelines

Assuring the displacement of trapped liquids from low sections by gas flow is essential for a proper operation of high-pressure natural gas pipelines. Numerical investigation of the associated transient turbulent high-pressure gas-liquid flow can provide understanding of the involved two-phase flow phenomena. To this aim, the numerical tool OpenFOAM has been used for simulating the gas-liquid flow encountered in a pipeline of a long shallow upward inclined section connected to a horizontal section by an elbow. Effects of various system parameters (e.g., gas pressure, liquid properties, up-comer inclination, elbow radius of curvature) on the gas-liquid flow dynamics are studied. Since 3D transient numerical simulations are more challenging, results obtained by 2D and 3D numerical simulations are compared to identify the similarities, sources of discrepancies, and their significance. Quantitative integral flow characteristics and the associated local flow phenomena are examined. 3D simulations verify the main findings of 2D simulations concerning the flow pattern, the associated critical gas velocity for purging the liquid and liquid propagation rate at supercritical gas velocities. The critical gas flow rate required to purge out the accumulated liquid is associated with that required to mobilize the liquid film tail along the up-comer. The main differences between 3D and 2D simulation results were captured near the elbows. The 3D effects, which result from the centrifugal force acting on the gas during its flow through the elbow, affect the downstream axial gas velocity profile and the secondary flow pattern (i.e., Dean vortices). The resulting higher interfacial shear exerted by the gas on the liquid film tail is the source of the deviations between the 3D and 2D simulation results. However, 2D simulations are sufficient for representing the gas-liquid dynamics out of the elbows’ influence region, where their effects on the flow fade out.

Reliability analysis of gas pipeline with corrosion defect based on finite element method

PurposeGas pipelines are facing serious risk because of the factors such as long service life, complex working condition and most importantly, corrosion. As one of the main failure reasons of gas pipeline, corrosion poses a great threat to its stable operation. Therefore, it is necessary to analyze the reliability of gas pipelines with corrosion defect. This paper uses the corresponding methods to predict the residual strength and residual life of pipelines.Design/methodology/approachIn this paper, ASME-B31G revised criteria and finite element numerical analysis software are used to analyze the reliability of a special dangerous section of a gas gathering pipeline, and the failure pressure and stress concentration of the pipeline under three failure criteria are obtained. Furthermore, combined with the predicted corrosion rate of the pipeline, the residual service life of the pipeline is calculated.FindingsThis paper verifies the feasibility of ASME-B31G revised criteria and finite element numerical analysis methods for reliability analysis of gas pipelines with corrosion defect. According to the calculation results, the maximum safe internal pressure of the pipeline is 9.53 Mpa, and the residual life of the pipeline under the current operating pressure is 38.41 years, meeting the requirements of safe and reliable operation.Originality/valueThe analysis methods and analysis results provide reference basis for the reliability analysis of corroded pipelines, which is of great practical engineering value for the safe and stable operation of natural gas pipelines.

Analysis of a model of a natural gas pipeline—a transfer function approach

Abstract A framework for natural gas pipelines is developed in a context similar to the theory of electric transmission lines. The system of semi-linear partial differential equations describing the time-dependent flow of natural gas is linearized around the steady-state flow. Additional approximations lead to a constant coefficient linear system that is equivalent to an electrical circuit that is analytically solvable and admits an ABCD matrix representation of input and output. The sinusoidal steady-state operation of natural gas pipelines is analysed including the distortion of waves. It is shown that the timing of the propagation of phases and other events is accurately represented in the approximation. The quantitative accuracy for flux and gas density of the approximation depending on different operating scenarios and depending on the frequency of the disturbances is documented.

Investigation on strain characteristic of buried natural gas pipeline under longitudinal landslide debris flow

In order to ensure the safe operation of buried natural gas pipeline (BNGP) under landslide debris flow (LDF), a model is established to investigate the strain characteristic of BNGP. The influence of longitudinal LDF morphology is analyzed for the elliptic deformation rate, tensile and compression strain of BNGP. The results show that the influence area of LDF is about 5 m from the upstream and downstream position of active area, respectively. The peak value of elliptic deformation rate is mainly impacted by the thickness and length of LDF, and will increase linearly with that. The maximum value of axial strains will also increase linearly with length, thickness and breadth of LDF. It will decrease with the angle of mountain slope and depth of BNGP. The fracture failure of BNGP may be occurred at the active area of LDF and upstream position of that. But the local yield or fold failure of BNGP will be occurred at the active area of LDF and downstream position of that. At the same time, a method is proposed to estimate the maximum value of elliptic deformation rate and axial strains of BNGP under longitudinal LDF. The deviations between the prediction results and simulation data are less than ±10%.

Microstructure Design and Properties of X100 Gas Line Pipe

The microstructure evolution process of X100 pipeline steel is analysed, and the influence of different alloy composition and accelerated cooling process on microstructure evolution is studied in this article. It is obtained that acicular ferrite microstructure can make the yield strength of steel reach 650 MPa through micro alloying and thermo-mechanical control process(TMCP) with the comprehensive reinforcement effect of grain refinement, micro-alloying element precipitates and dislocation substructure. Acicular ferrite has the characteristics of fine grain, cross distribution, large angle grain boundary and presence of sub structure and high density movable dislocation. Test results of product quality also show that X100 pipeline steel which adopts Mn-Nb-Ti component system with a small amount of Ni (V), Mo alloy addition and TMCP process has obvious characteristics of fine grain. The Matrix is consisted of granular bainite and appropriate amount of MA as dispersion phase, which makes the tensile strength reach more than 800 Mpa. At the same time, the X100 pipeline steel has the characteristics of high toughness and good weldability, which is beneficial to ensure the safe operation of high pressure natural gas pipeline.

Event classification for natural gas pipeline safety monitoring based on long short-term memory network and Adam algorithm

Hydrate plugging and pipeline leak can impair the normal operation of natural gas pipeline and may lead to serious accidents. Since natural gas pipeline safety monitoring based on active acoustic excitation can detect and locate not only the two abnormal events but also normal components such as valves and pipeline elbows, recognition and classification of these events are of great importance to provide maintenance guidance for the pipeline operators and avoid false alarm. In this article, long short-term memory (LSTM) network is introduced and applied to classify detection signals of hydrate plugging, pipeline leak, and elbow. Adaptive moment estimation (Adam) algorithm is introduced and utilized to accelerate the long short-term memory network convergence in training. Experimental results demonstrate that the network with three layers and 64 units per cell performs the best. The cross-entropy loss in training is 0.0005, and classification accuracies are all 100% in training, validation, and testing which verify the validity of the long short-term memory network. Therefore, the method based on the long short-term memory network and adaptive moment estimation algorithm can work efficiently on pipeline events classification and has great guiding significance for safety assurance of natural gas transmission.