Operation Of Gas Pipelines Research Articles

Precision and uncertainty in natural gas calorific value estimation: advanced combinatorial predictive models for complex pipeline systems

Abstract In recent years, natural gas pipelines have been characterized by multiple intake points, the mixing of different gas sources, and significant variations in gas quality. The existing volumetric measurement system is no longer suitable for the development and operation of natural gas pipelines in China. To ensure accurate and equitable implementation of natural gas measurement, there is a gradual shift towards energy measurement. However, due to numerous measurement interfaces, installing chromatographs at all measurement stations would lead to substantial investment costs. Therefore, predicting the calorific value of natural gas is a key technology for energy measurement. In view of the issues existing in the current methods of obtaining natural gas calorific value, different prediction models of natural gas calorific value are constructed. According to the influencing factors of natural gas calorific value, the uncertainty evaluation is carried out, and the accuracy of different calorific value prediction models is analyzed by case data. The maximum error of regression equation (RE), response surface analysis (RSA), BP neural network and genetic algorithm (GA) prediction model is 2.29%, 0.43%, 0.59% and 0.45% respectively. However, the combined calorific value (CCV)prediction model is 0.41%. The results indicate that the predicted value calculated by the CCV prediction model is closer to the actual value and has higher prediction performance, which provides a new method for the calorific value prediction and measurement management of natural gas.

Study on the mechanical properties of X80 pipeline steel under pre-charged high-pressure gaseous hydrogen

Hydrogen embrittlement (HE) is a significant challenge to the safe operation of hydrogen-blended natural gas pipelines. The mechanical properties of X80 steel were studied after H2 pre-charging followed by mechanical properties tests and fracture morphologies observation. Results indicated that the hydrogen saturation time of X80 steel was roughly 48 h. H2 pre-charging induced a decline in strength, plasticity, and fatigue properties, while hydrogen-assisted fatigue crack growth occurred during the early stage of fatigue crack growth rate tests. Additionally, the fracture morphologies transited from primary microvoid coalescence to a mixed mode characterized by ductile dimples and quasi-cleavage planes with increasing hydrogen. The HE susceptibility increased with increasing hydrogen partial pressure and decreasing loading frequency, but there existed a critical value (6 × 10−7 s−1) for the strain rate effect on the HE susceptibility. Under H2 pre-charging conditions, the predominant HE mechanism was the hydrogen-enhanced local plasticity (HELP) mediated hydrogen-enhanced decohesion (HEDE) mechanism.

Assessment of hydrogen-induced material degradation using electromagnetic testing technology

The production, transport and use of green hydrogen are key issues for the efficient use of renewable energies. Hydrogen is able to compensate for both temporal and spatial fluctuations that naturally occur in the production and consumption of renewable energies, regardless of weather conditions, and thus can act as an efficient energy storage medium. The use of existing gas pipelines in a dynamically operated pipeline network offers particular potential for the transport of green hydrogen with regard to sustainability, resource conservation and economic efficiency. In this context, dynamic means that pressure fluctuations are permissible to a certain extent in the operation of gas pipelines. However, a hydrogen-induced degradation of the mechanical material properties can lead to brittle fracture and manifest itself in sudden material failure. Such failure must be excluded in safetyrelevant infrastructures. Hence, it would be beneficial to detect fatigued or degraded areas in the material at an early stage, especially in the context of possible increased crack growth rates associated with hydrogen embrittlement. In addition to fatigue data, which are crucial in the calculation and design of gas pipelines, non-destructive inspections are particularly important in subsequent operation to monitor the current condition of the pipelines. Non-destructive testing focuses primarily on defects such as cracks that have already developed or on visible corrosion attack. The fatigue condition, i.e., the probability of crack initiation and crack propagation is hard to evaluate. However, this can be addressed by an electromagnetic test method capable of evaluating the current state of the material. In the presented paper, an electromagnetic test method is presented, which is able to detect and evaluate hydrogen-induced material degradation. In subsequent stages, such a method can then be used as an electromagnetic monitoring system in fatigue tests, thus providing new potential for condition assessment.

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.

Study on the effect of microstructure on toughness dispersion of X70 steel girth weld

The girth weld metal impact toughness would affect the safe operation of long transmission oil and gas pipeline. In order to further clarify toughness law of pipeline steel girth weld, the Charpy impact toughness of X70 steel girth weld at −10 °C was studied by standard impact method, and the impact energy range was determined to be 18–95 J. The impact energy range of girth welds varied significantly, and the toughness was discrete. The impact toughness of the different microstructures in the girth weld at −158 °C was studied by the small specimen impact test. The root weld metal mainly consisted of ferrite and a small amount of pearlite, and its impact toughness was low. The large effective grain size and dislocation density difference between large lath bainite (LB) and coarse granular bainite (GB) increased the strain heterogeneity during impact deformation. In fine GB, effective grain size reduction and uniform distribution of Martensite austenite (M–A) components reduced the local strain, resulting in more uniform deformation. Therefore, the sample with the fine GB had higher impact the toughness and ductile fracture mode. For the standard Charpy impact samples, the main reason for toughness dispersion was change of fine GB proportion. The fine GB proportions of P6-2, P3-3 and P3-2 were 46.7 %, 40.8 %, and 29.5 %, respectively. Simultaneously, the influence of position change on the impact energy was considered.

Composition tracking of natural gas–hydrogen mixtures in pipeline flow using high-resolution schemes

A transient pipeline flow model with gas composition tracking is solved for studying the operation of a natural gas pipeline under nonisothermal flow conditions in a hydrogen injection scenario. Two approaches to high-resolution pipeline flow modeling based on the WENO scheme are presented and compared with the implicit finite difference method. The high-resolution models are capable of capturing fast fluid transients and tracking the step changes in the composition of the transported mixture. The implicit method assumes the decoupling of the flow model components in order to enhance calculation efficiency. The validation of the composition tracking results against actual gas transmission pipeline indicates that both models exhibit good prediction performance, with normalized root mean square errors of 0.406% and 1.48%, respectively. Under nonisothermal flow conditions, the prediction response of the reduced model against a high-resolution flow model, with respect to the mass and energy linepack, is at most 3.20%.

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.

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.

Numerical analysis of the effect of hydrogen doping ratio on gas transmission in low-pressure pipeline network

In the context of a global shift towards clean energy, the integration of hydrogen into existing natural gas pipeline networks is essential for facilitating the energy transition. Specifically, low-pressure natural gas pipeline networks are crucial for transporting gas efficiently and with minimal losses from the source to end-users in nearby cities. The physical properties of hydrogen differ significantly from those of natural gas, which implies that introducing hydrogen into the pipeline network will modify operational parameters and impact the safety and efficiency of gas transmission. Therefore, this study concentrates on the efficiency of transporting and scheduling hydrogen-blended natural gas through existing low-pressure direct pipelines. Utilizing the BWRS (Benedict-Webb-Rubin-Starling) equation of state, mathematical models were developed to calculate gas properties and to simulate both the steady and transient states of hydrogen-blended natural gas networks. These models were then validated with TGNET software. This study examines a low-pressure natural gas transmission and distribution network that transports gas directly from a production site in Sichuan to urban areas. It conducts simulations of hydrogen blending and analyzes the impact of various hydrogen blend ratios on the transport and scheduling responses of the network. Research suggests that maintaining the hydrogen blend below 30% ensures the safe operation of low-pressure gas pipelines and prevents the transmission pressure from exceeding 3 MPa. Additionally, under a fixed energy flow output, blending hydrogen intensifies the challenges associated with pressure drops and temperature increases due to high flows in small diameter pipes, and further complicates the management of interruptions resulting from faults. Therefore, it is recommended that the hydrogen blend ratio be maintained at no more than 30%, and that accident handling procedures be established in advance to control pressure variations following a shutdown.

FORMALIZATION OF THE PRINCIPLE, METHOD AND METHOD OF DEVELOPING A DIGITAL IMAGE OF THE LINEAR PART OF THE MAIN GAS PIPELINE

Uninterrupted gas supply to consumers and ensuring the design volume of pumping provides for the absence of accidents and incidents. Accidents during the operation of main gas pipelines lead to significant social, environmental and material losses. Due to the long-term operation and expiration of the resource of sections of gas pipelines operated on the territory of the Russian Federation, an urgent task is to increase their reliability and reduce accidents. At the same time, one of the prevailing conditions is the reliability of the linear part, which is formed at the design stage, provided and maintained during operation. To ensure reliable and trouble-free operation of the main gas pipeline, many different measures are carried out, as well as the systems necessary to assess and maintain the specified technical condition parameters are used. In order to reduce the industrial operation of main gas pipelines by reliably assessing the technical condition of the linear part and identifying potentially dangerous sections, a digital model is being developed that allows to accurately assess the technical condition of the pipeline section under examination.

A transient gas pipeline network simulation model for decoupling the hydraulic-thermal process and the component tracking process

The metering mode is gradually changing from volumetric metering to energy metering under the open-access operation of gas pipelines. The gas component tracking by operating simulation is an effective method to realize the energy metering of gas networks. In this paper, coupling and decoupling transient component tracking models of gas networks are proposed. The pipeline governing equations, compressor equations, valve equations, and node relationship equations are considered in the proposed models. The implicit central difference method and the damped Newtonian method are adopted to solve the models. The coupling model considers the component tracking part and hydraulic-thermal simulation as a whole, while the decoupling model splits the whole process into the gas component tracking part, the parameters calculation part, and the hydraulic-thermal simulation part. In the component tracking part, the spatiotemporal variation of the gas mass fraction and density can be obtained through the input velocity of each node. Then, the parameters in the gas state equation can be solved, the hydraulic-thermal simulation can be performed, and the new velocity of each node can be calculated. The iteration for each time step ends if the deviation of flow velocity in the component tracking process and the hydraulic-thermal process satisfies the requirements. Two cases are studied to verify the effectiveness of the proposed models, and the boundary condition adaptability of the transient simulation models is analyzed. The proposed models can efficiently simulate the spatiotemporal variation of the operating variables and gas components, providing a reference in the operation of natural gas pipeline networks.

Predicting maximum pitting corrosion depth in buried transmission pipelines: Insights from tree-based machine learning and identification of influential factors

Pitting corrosion is a primary type of external corrosion that poses a critical challenge in the oil and gas industry, potentially leading to severe environmental, health, and economic consequences if left unaddressed. Researchers have attempted to comprehend and forecast it through diverse methods, including machine learning and artificial intelligence. However, achieving a precise estimation of pitting growth while considering the influence of various environmental and operational factors remains a concern. This study aims to develop a model by employing tree-based machine learning algorithms, including Decision Tree, Random Forest, LightGBM, CatBoost, and XGBoost, to enhance the prediction accuracy of the maximum depth of pitting corrosion in buried transmission pipelines while also facilitating interpretability. The Random Forest model is found to be the best-performing model with a mean absolute error (MAE) of 0.588. Beyond prediction accuracy, the present analysis contributes practical insights for industry application. First, the model identifies pipes at high risk of severe pitting corrosion under challenging environmental conditions, enabling targeted preventive measures. Secondly, the model's interpretation, utilising game-theoretic Shapely values and permutation importance, informs strategic decisions on the burial of new pipes, ultimately extending their operational lifespan. These applications emphasise the potential of our findings to significantly improve the safety, reliability, and risk mitigation strategies in oil and gas pipeline operations.

A Real-Time Multifactor Risk Monitoring Method for the Gas Pipeline Operation Process Based on Mix-Supervised Target Recognition

A Real-Time Multifactor Risk Monitoring Method for the Gas Pipeline Operation Process Based on Mix-Supervised Target Recognition

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.

Characterization of the evolution of leakage and variation of in-pipe parameters in a full-size ethane high-pressure pipeline

There is a risk of leakage of ethane during high-pressure pipeline transportation. In order to investigate the effects of leakage conditions on the free-field ethane concentration distribution, temperature and pressure evolution, a full-size ethane high-pressure gas pipeline experimental platform was constructed, and high-pressure ethane leakage experiments were carried out with different diameters and leakage directions to investigate the effects of different leakage directions and diameters on the free-field ethane diffusion, temperature and pressure inside the pipeline. The experiment results show that in the free field, when the leakage direction is ≥45° to the horizontal plane, the near-surface ethane concentration is close to 0. When the horizontal leakage occurs, compared with the 15 mm leak diameters, the peak concentration of the 25 mm leak diameters rises by 17.7%, and the explosion danger range rises by 75%, and the explosion danger time is extended by 78.6%. It is worth mentioning that the initial pressure drop rate and the overall temperature drop in the pipeline increase and then decrease with the increase of leak diameters during the high-pressure ethane leakage process, and there is a critical diameter, which is 15 mm in this experiment. The results of the study provide a reference for the safe operation of the high-pressure ethane gas pipeline.

Dynamic risk assessment of gas pipeline operation process by fusing visual and olfactory monitoring

With the rapid increase in urban gas consumption, the frequency of maintenance and repair of gas pipelines has escalated, leading to a rise in safety accidents during these processes. The traditional manual supervision model presents challenges such as inaccurate monitoring results, incomplete risk factor analysis, and a lack of quantitative risk assessment. This research focuses on developing a dynamic risk assessment technology for gas emergency repair operations by integrating the monitoring outcomes of artificial olfactory for gas leakage information and video object recognition for visual safety factor monitoring data. To quantitatively evaluate the risk of the operation process, a three-dimensional risk assessment model combining gas leakage with risk-correlated sensitivity was established as well as a separate three-dimensional risk assessment model integrating visual risk factors with predictable risk disposition. Furthermore, a visual risk quantification expression mode based on the risk matrix-radar map method was introduced. Additionally, a risk quantification model based on the fusion of visual and olfactory results was formulated. The verification results of simulation scenarios based on field data indicate that the visual-olfactory fusion risk assessment method can more accurately reflect the dynamic risk level of the operation process compared to simple visual safety factor monitoring. The outcomes of this research can contribute to the identification of safety status and early warning of risks related to personnel, equipment, and environmental factors in emergency repair operations. Moreover, these results can be extended to other operational scenarios, such as oil and gas production stations and long-distance pipeline operations.

Hydrate formation due to moisture, occuring by mixing natural gas streams of dewatering different degrees

The key problem during transporting natural gas through gas pipelines is to ensure reliable, safe transportation and supply of gas to consumers. Reliable operation of the main gas pipeline depends on transported gas quality. Under production conditions, gas is saturated with moisture vapor to an equilibrium state, and when thermodynamic conditions (pressure, temperature) change, its condensation occurs. Due to the heterogeneity of the fields, the problem of gas quality control is the key reliability criterion, especially such as the moisture content in the gas. The main complication is the formation of hydrate plugs, which lead to an increase in hydraulic resistance and a decrease in pipeline capacity, which contributes to the occurrence of emergency situations. Therefore, before supplying natural gas to main gas pipelines, the gas is dried to its dew point, which prevents condensation of water from the gas.

Change of location class in gas pipelines from a regulatory perspective

AbstractLocation class is an essential factor in the gas pipeline project because it considers factors such as population density and the number of buildings along the gas pipeline route. As these parameters change, the pipeline operator needs to review the location class, also requiring a possible assessment of changes in allowable pipeline operating pressure. Brazilian regulations related to the safety of pipeline processes are defined in the Onshore Pipeline Technical Regulation and this document indicates the application of the requirements of the ASME B31.8 standard for changing the location class. Although there are preventive and mitigating measures in the ASME B31.8 standard, they are seen as overly conservative. Other international standards have different concepts, with evaluation criteria based on risk analysis. The issue has also been a challenge for other countries, which are reviewing their regulations and developing guidelines for gas pipeline operators. The main objective of this study is to carry out a survey of international practices related to changing the location class of gas pipelines and to propose a criterion based on the best international practices based on risk management, allowing a more comprehensive view of this subject.

Quantitative research on stress failure risk assessment for girth welds with unequal wall thickness of the X80 pipeline under lateral load

The cumulative length of the X80 steel pipeline extends to 17,000 km, with a predominant portion traversing mountainous terrains characterized by intricate geological formations. Recurrent geological hazards significantly impede the safe operation of oil and gas pipelines. Landslides can induce substantial axial forces on steel pipelines, significantly increasing the risk of pipeline failure. Moreover, as a result of sudden changes in mechanical structure, the pipeline's unequal wall thickness leads to local stress concentration, making it more vulnerable to external loads than the steel pipeline itself. Therefore, to analyze the mechanical response of steel pipelines under different working conditions, we establish a smooth particle hydrodynamics, finite element transverse landslide pipeline model for girth welds with unequal wall thickness and investigate a tearing accident caused by a lateral landslide in a section of the large-diameter natural gas pipeline. The landslide volume is found to be the main controlling factor for the failure of pipeline circumferential welds. According to the genetic algorithm backpropagation neural network, the von Mises stress of the most dangerous section of the pipeline is calculated based on pipeline and landslide parameters, and the error is 11.67 %. According to the API RP 581–2016 Risk-Based Inspection Methodology, a failure risk assessment matrix is established using the pipeline statute as an evaluation indicator to evaluate the landslide risk to pipelines in different regions. A variable-wall-thickness girth weld on the ZG pipeline was selected for application. This method has good applicability for evaluating the failure risk of circumferential welds with wall thicknesses of 12.8/15.3 mm under the action of small landslides.

Modeling Pipe to Soil Potentials From Geomagnetic Storms in Gas Pipelines in New Zealand

AbstractGas pipelines can experience elevated pipe to soil potentials (PSPs) during geomagnetic disturbances due to the induced geoelectric field. Gas pipeline operators use cathodic protection to keep PSPs between −0.85 and −1.2 V to prevent corrosion of the steel pipes and disbondment of the protective coating from the pipes. We have developed a model of the gas pipelines in the North Island of New Zealand to identify whether a hazard exists to these pipelines and how big this hazard is. We used a transmission line representation to model the pipelines and a nodal admittance matrix method to calculate the PSPs at nodes up to 5 km apart along the pipelines. We used this model to calculate PSPs resulting from an idealized 100 mVkm−1 electric field, initially to the north and east. The calculated PSPs are highest are at the ends of the pipelines in the direction of the applied electric field vector. The calculated PSP follows a characteristic curve along the length of the pipelines that matches theory, with deviations due to branchlines and changes in pipeline direction. The modeling shows that the PSP magnitudes are sensitive to the branchline coating conductance with higher coating conductances decreasing the PSPs at most locations. Enhanced PSPs produce the highest risk of disbondment and corrosion occurring, and hence this modeling provides insights into the network locations most at risk.