Gas Pipeline Transportation Research Articles

Leakage Failure Analysis of Some Gas Transportation Pipeline Girth Weld

Leakage Failure Analysis of Some Gas Transportation Pipeline Girth Weld

A novel optimization framework for natural gas transportation pipeline networks based on deep reinforcement learning

Natural gas is an emerging and reliable energy source in transition to a low-carbon economy. The natural gas transportation pipeline network systems are crucial when transporting natural gas from the production endpoints to processing or consuming endpoints. Optimizing the operational efficiency of compressor stations within pipeline networks is an effective way to reduce energy consumption and carbon emissions during transportation. This paper proposes an optimization framework for natural gas transportation pipeline networks based on deep reinforcement learning (DRL). The mathematical simulation model is derived from mass balance, hydrodynamics principles of gas flow, and compressor characteristics. The optimization control problem in steady state is formulated into a one-step Markov decision process (MDP) and solved by DRL. The decision variables are selected as the discharge ratio of each compressor. By the comprehensive comparison with dynamic programming (DP) and genetic algorithm (GA) in three typical element topologies (a linear topology with gun-barrel structure, a linear topology with branch structure, and a tree topology), the proposed method can obtain 4.60% lower power consumption than GA, and the time consumption is reduced by 97.5% compared with DP. The proposed framework could be further utilized for future large-scale network optimization practices.

Numerical simulation of hydrate flow in gas-dominated undulating pipes considering nucleation and deposition behaviors

The distribution and deposition of hydrates in deep-water gas transportation pipelines are crucial for safety. Current simulations of hydrate flow based on the population balance model have predominantly focused on water-dominant systems and neglect the nucleation and deposition of hydrates. By establishing a model for a hydrate flow in a gas-dominant system that considers the uneven distribution of the liquid film on the wall, hydrate nucleation, gas–liquid mass transfer, particle adhesion and aggregation, and dynamic deposition, we achieved simulation of the entire process of hydrate formation, aggregation, breakage, and deposition. Simulations in undulating pipelines were carried out to investigate the effects of gas velocity, liquid injection, pressure, and pipeline structure on distribution patterns. The results showed increasing the gas velocity enhanced the dispersion of particles and increasing the pressure increased the rate of aggregation. The formation of blocky aggregates posed significant risk in the rear section of the lower-bend pipe.

Current Status and Analysis of Natural Gas Pipeline Hydrogen Blending and Transportation Development

Hydrogen doping in natural gas pipelines is one of the means to realize large-scale, long-distance and low-cost hydrogen transportation, but hydrogen doping in natural gas pipelines has brought about non-negligible impacts on pipeline operating conditions, safety and maintenance, etc., and has certain potential safety hazards. To this end, the technical research and engineering application of hydrogen doping in natural gas pipelines at home and abroad are discussed, and the main factors affecting the safe transportation of hydrogen doping in natural gas pipelines are discussed, i.e., physical changes of natural gas caused by hydrogen doping, hydrogen failure, and uneven mixing. The results show that the hydrogen doping of natural gas puts new requirements on the existing pipe materials, and relevant experiments need to be carried out in order to reveal the mechanism of hydrogen failure, and whether gas aggregation occurs after the shutdown of hydrogen-doped natural gas pipelines is closely related to whether hydrogen failure occurs in the pipelines or not. The above results clarify the risks of hydrogen-doped transportation, which can provide a reference for the promotion of large-scale hydrogen-doped mixing and transmission projects and practical operation.

Flow corrosion simulation study of local defects in CO2 saturated solution

The inner walls of oil and gas transportation pipelines are prone to the formation of localized pitting defects due to the presence of solid particles in multiphase flow. The continuous flow poses a risk of perforation leakage in the pipe wall. To investigate the development of defects under flow corrosion and assess the impact of flow, a multi-field coupling finite element model incorporating fluid dynamics, reactions, and mass transfer was developed. The flow corrosion of local defects with various depths in a CO2-saturated solution was simulated. The calculation of mass transfer in corrosion is coupled with the precise flow field solved by large eddy simulation (LES) method. It has been observed that the distribution of corrosive substances is significantly affected by the flow due to local defects. Within these defects, the maximum concentration of corrosion product Fe2+ is observed on the upstream surface of defects. While the H+ accumulates at the downstream wall, which affects the corrosion rate. The local turbulent state is influenced by the depth of defects, and the interplay of the turbulence intensity with reflux velocity determines the mass transfer.

The development of high-performance kinetic hydrate inhibitors by introducing N-vinyl caprolactam and vinyl ether homopolymers into PVCap

Low dosage kinetic hydrate inhibitors (KHIs) are a kind of alternative chemical additives to prevent gas hydrate formation in oil & gas production wells and transportation pipelines. In this work, a series of KHIs were experimentally synthesized with N-vinyl caprolactam (N-VCap) and vinyl ether including vinyl ether, vinyl n-butyl ether, vinyl isobutyl ether, triethylene glycol divinyl ether, with the mole ratio ranging from 9:1 to 5:5. The inhibition performance of new-synthesized KHIs on the formation process of methane hydrate were examined and compared with that of commercial N-vinyl caprolactam PVCap. Several ethylenediamine reagents were used as synergists and tested to improve the inhibition capacity of new-synthesized KHIs. The experimental results demonstrate that the introduction of ether groups on PVCap improves the performance of hydrate inhibitors. PVCap-VNBE (N-VCap: vinyl n-butyl ether = 5:5) showed the best inhibition performance for methane hydrate, which could extend the TVO to 1251 min under 6 K subcooling. N,N'-dimethylethylenediamine shows the best synergistic effect for PVCap-VNBE (5:5), and extends the TVO by 2.75 times at 7 K subcooling. Additionally, the relationship between hydrate inhibition performance and interfacial tension of newly-synthesized KHIs under high pressure were studied. It shows that the lower interfacial tension of KHIs would result in longer onset time, exhibiting better inhibition performance.

Study of NO and CO Formation Pathways in Jet Flames with CH4/H2 Fuel Blends

The existing natural gas transportation pipelines can withstand a hydrogen content of 0 to 50%, but further research is still needed on the pathways of NO and CO production under moderate or intense low oxygen dilution (MILD) combustion within this range of hydrogen blending. In this paper, we present a computational fluid dynamics (CFD) simulation of hydrogen-doped jet flame combustion in a jet in a hot coflow (JHC) burner. We conducted an in-depth study of the mechanisms by which NO and CO are produced at different locations within hydrogen-doped flames. Additionally, we established a chemical reaction network (CRN) model specifically for the JHC burner and calculated the detailed influence of hydrogen content on the mechanisms of NO and CO formation. The findings indicate that an increase in hydrogen content leads to an expansion of the main NO production region and a contraction of the main NO consumption region within the jet flame. This phenomenon is accompanied by a decline in the sub-reaction rates associated with both the prompt route and NO-reburning pathway via CHi=0–3 radicals, alongside an increase in N2O and thermal NO production rates. Consequently, this results in an overall enhancement of NO production and a reduction in NO consumption. In the context of MILD combustion, CO production primarily arises from the reduction of CO2 through the reaction CH2(S) + CO2 ⇔ CO + CH2O, the introduction of hydrogen into the system exerts an inhibitory effect on this reduction reaction while simultaneously enhancing the CO oxidation reaction, OH + CO ⇔ H + CO2, this dual influence ultimately results in a reduction of CO production.

Detection of Harmful H2S Concentration Range, Health Classification, and Lifespan Prediction of CH4 Sensor Arrays in Marine Environments

Underwater methane (CH4) detection technology is of great significance to the leakage monitoring and location of marine natural gas transportation pipelines, the exploration of submarine hydrothermal activity, and the monitoring of submarine volcanic activity. In order to improve the safety of underwater CH4 detection mission, it is necessary to study the effect of hydrogen sulfide (H2S) in leaking CH4 gas on sensor performance and harmful influence, so as to evaluate the health status and life prediction of underwater CH4 sensor arrays. In the process of detecting CH4, the accuracy decreases when H2S is found in the ocean water. In this study, we proposed an explainable sorted-sparse (ESS) transformer model for concentration interval detection under industrial conditions. The time complexity was decreased to O (n logn) using an explainable sorted-sparse block. Additionally, we proposed the Ocean X generative pre-trained transformer (GPT) model to achieve the online monitoring of the health of the sensors. The ESS transformer model was embedded in the Ocean X GPT model. When the program satisfied the special instructions, it would jump between models, and the online-monitoring question-answering session would be completed. The accuracy of the online monitoring of system health is equal to that of the ESS transformer model. This Ocean-X-generated model can provide a lot of expert information about sensor array failures and electronic noses by text and speech alone. This model had an accuracy of 0.99, which was superior to related models, including transformer encoder (0.98) and convolutional neural networks (CNN) + support vector machine (SVM) (0.97). The Ocean X GPT model for offline question-and-answer tasks had a high mean accuracy (0.99), which was superior to the related models, including long short-term memory–auto encoder (LSTM–AE) (0.96) and GPT decoder (0.98).

Visual study of hydrate particles agglomeration and rolling characteristic in gas-oil-water phase using a flow loop

Natural gas hydrate blockage always leads to safety problems in oil and gas transportation pipelines. It is important to look for the characteristic of hydrate blockage process. The hydrate blockage was visually investigated under gas-oil-water multi-phase flow conditions in a flow loop in this study. The change of pressure drop with water conversion rate variations were detected. The hydrate particle movements were also observed in the visual pipes at different liquid loadings and water cuts. It was found that the hydrate particles may agglomerate and deposit with an obvious rolling process in low water cut conditions. The oil phase will accelerate particles agglomeration in the contact interface of oil, gas and water, and form a large number of flocculent hydrates. A theoretical hydrate particle rolling model was conducted to analysis the experiment results, and the hydrate particle velocity increases first and then decreases with the increase of particle diameter due to the comprehensive influence of van der Waals force and drag force. The results also confirmed the maximum of the pressure drop increased when the liquid loading increased. However, the hydrate formation and blockage speed also slow down due to small component of the gas phase in high liquid loading. In addition, comparing with 20 % and 80 % water cut, 50 % water cut has the fastest hydrate formation speed in different experimental conditions. Furthermore, the maximum water conversion rate increased with have a higher water cut. More hydrate will form in the condition, which will lead to the decrease of flow velocity in the pipeline.

Industrial Radiography Testing & Technique Safety for Human Body

The use of Industrial Radiography for examining the quality of Weld joints is very popular worldwide. In India, many welding activities like construction and laying the huge pipelines for gas and water transportation and distribution as well construction of storage tanks are performed. The objects are working under high pressure and therefore, it is important to produce the weld beads with high quality. Industrial radiography uses ionizing radiation to view objects in a way that cannot be seen otherwise. The method has grown out of engineering, and is a major element of non-destructive testing (NDT) to inspect materials for hidden flaws. The radiation caused by these facilities is very dangerous however, with the use of new technologies and proper protection, risks of injury and death associated with radiation can be greatly reduced. Use or radiation sources are associated with a certain amount of radiation hazard. With proper card, this can be minimized. Radiation hazards may be broadly classified as external hazards an internal hazard. External hazards occur when the source of radiation is outside the body and internal hazards arise when the source for radiation gets into the human system. Hazard evaluation is necessary in order to adopt suitable measures to control radiation exposure. The problem of internal hazard does not arise in the use of X-ray equipment. It is considerably easy to estimate the external radiation hazard and there are a number of devices suitable for this purpose.

Physics Constrained High-Precision Data-Driven Modeling for Multi-Path Ultrasonic Flow Meter in Natural Gas Measurement.

Ultrasonic flow meters are crucial measuring instruments in natural gas transportation pipeline scenarios. The collected flow velocity data, along with the operational conditions data, are vital for the analysis of the metering performance of ultrasonic flow meters and analysis of the flow process. In practical applications, high requirements are placed on the modeling accuracy of ultrasonic flow meters. In response, this paper proposes an ultrasonic flow meter modeling method based on a combination of data learning and industrial physics knowledge. This paper builds ultrasonic flow meter flow velocity prediction models under different working conditions, combining pipeline flow field velocity distribution knowledge for data preprocessing and loss function design. By making full use of the characteristics of the physics and data learning, the prediction results are close to the real acoustic path flow velocity distribution; thus, the model has high accuracy and interpretability. Experiments are conducted to prove that the prediction error of the proposed method can be controlled within 1%, which can meet the needs of ultrasonic flow meter modeling and subsequent performance analysis in actual production.

The premixed flame structure and combustion mechanism of clean hydrogen mixed with multi-component natural gas

Hydrogen is widely taken for the most potential clean energy for the moment. Currently, pipeline transport of natural gas mixed with hydrogen is one of the primary approaches of hydrogen transportation. However, compared to pure natural gas (CH4), the explosion and combustion of natural gas mixed with hydrogen may lead to more severe consequences, and its reliability needs to be considered. Existing research of combustion and explosion using methane instead of natural gas have yet to be considered for application to real multi-component natural gas. To address this issue, real multi-component natural gas is configured, and the premixed flame and combustion characterization parameters of natural gas/H2/air are obtained through experiment. The chemical reaction kinetics of natural gas/H2/air mixtures are analyzed using Chemkin Pro software. These results prove that the laminar burning (LB) velocity varies between 0.33 m/s and 2.34 m/s by adding H2. The primitive reactions R1 (H2 + OH → H + H2O) and R3 (H + O2 → O + OH) predominantly contribute to enhancing the LB velocity. The Markstein lengths rang from −0.19 mm to −0.049 mm, most lewis numbers are less than 1, the flame thicknesses and critical destabilization radii are reduced. Additionally, hydrodynamic instability and thermal-diffusion instability are strengthened by adding the hydrogen. As for smaller hydrogen content, the average size of flame cell from about 8 mm program first rises and then falls cyclic fluctuations, fluctuation amplitude gradually reduces, fluctuation frequency accelerates. In larger hydrogen content, this fluctuation amplitude is reduced and the average size of flame cell decreases. In addition, H2 enhances the explosive strength of natural gas. Finally, methane instead of natural gas may exaggerate the velocity of laminar burning and exaggerate or weaken the ignition time delay of natural gas with different hydrogen contents. The current research might provide crucial information for the safe transport of hydrogen mixed with natural gas.

Investigation into flow-induced internal corrosion direct assessment in small-diameter dry gas fluctuating pipeline

Small-diameter undulating natural gas pipelines with low gas transmission capacity do not have internal inspection conditions to grasp the internal corrosion status of the pipeline. This study focuses on a small-diameter undulating dry natural gas gathering and transportation pipeline, the internal corrosion mechanism of the pipeline is studied through corrosion products, and the specific location of the internal corrosion sensitive pipe segment is determined based on multiphase flow simulation and PMDT(pipeline non-contact magnetic anomaly detection); the excavation inspection is ultimately used to evaluate the internal status of the pipeline. The results demonstrate that the internal corrosion mechanism of ZL (ZI Lai) pipeline is O2 and CO2 synergistic corrosion in which O2 plays a dominant role, while the increasing flow rate will aggravate corrosion; The maximum general corrosion rate and critical inclination along the pipeline are 0.0218 mm/a and 18.4°, respectively. Furthermore, twelve corrosion sensitive segments have been identified, including two II-level and six III-level magnetic anomaly segments. The internal corrosion defects are localized at the 3–9o’clock position of the pipeline, with a maximum general corrosion rate not exceeding 0.0228 mm/a. Furthermore, the pipeline failure pressure of 12.27 MPa surpasses the maximum allowable working pressure of 8.84 MPa, ensuring its continued operational safety. The corrosion protection measures of reducing the water content of natural gas, adding vapor corrosion inhibitor and regularly detecting magnetic anomaly pipeline are developed.

Research on Failure Pressure of API 5L X100 Pipeline with Single Defect

Background: With the continuous application of API 5L X100 high-strength grade steel pipeline and the development trend of increasing pipeline diameter and design pressure in China's long natural gas and petroleum pipeline, API 5L X100 high-strength grade steel pipeline steel is bound to become the aorta in long-distance pipeline construction in the future. Studying the failure pressure of API 5L X100 high-strength grade steel pipeline has high economic and social benefits. Objective: Exploring the corrosion mechanism of the two single corroded pipeline models with outer defect and inner defect. Methods: Using ANSYS Workbench 15.0 software to explore the two single corroded pipeline models with outer defect and inner defect and the influence of geometric parameters such as defect depth, defect length, defect width, etc., on the maximum equivalent stress and failure pressure investigated. Based on the finite element analysis database, the failure pressures of two single corroded pipeline models were fitted using Matlab software and the fitting formulas. Results: In the corrosion defect area of the pipeline, stress concentration occurs; Far away from the corrosion defect area, the stress distribution is uniform. For the pipeline model with outer defect and inner defect, as the defect depth and length increases, failure pressure shows a decreasing trend and is almost unaffected by defect width; As the ratio of diameter to thickness increases, failure pressure shows a decreasing trend; By fitting failure pressure formula of the pipeline models with outer defect and inner defect, a multivariate fitting function formula of failure pressure is obtained, with high fitting exactitude. Conclusion: The conclusion obtained have certain guiding values for the normal and stable operation of natural gas and petroleum transportation pipelines.

Innovative acoustic emission method for monitoring the quality and integrity of ferritic steel gas pipelines

Abstract This article presents a comprehensive improvement in the experimental analysis of cracking processes in smooth and sharp V-notched samples taken from gas transport pipelines, utilizing the acoustic emission (AE) method. The research aimed to establish a robust correlation between the failure mechanisms of uni-axially tensile samples and the distinct characteristics of AE signals for enhanced quality management in pipeline integrity. The study encompassed materials from two different straight pipe sections, encompassing both long-term used materials and new, unused materials. Through the application of the k-means grouping method to AE signal analysis, we achieved the identification of AE signal parameters characteristic of various stages of the material destruction process. This advancement introduces a significant improvement in monitoring and managing the operational safety of pipeline networks, offering a methodology that leverages advanced acoustic emission signal analysis. The outcomes present significant implications for the pipeline industry by proposing methods to enhance safety systems and more effectively manage the integrity and quality of gas infrastructure.

Prediction of liquid holdup and pressure drop in gas-liquid two-phase flow based on integrating mechanism analysis and data mining

Gas-liquid two-phase flow widely exists in gas transportation pipelines, and the prediction of liquid holdup and pressure drop is crucial for the safety and efficiency of pipelines. Due to the complexity of multiphase flow, the mechanism model is difficult to accurately and quickly predict the liquid holdup and pressure drop. Machine learning (ML) models have high accuracy, but the lack of physical meaning limits their application. In order to fully leverage the advantages of mechanism models and machine learning models, a new method using physically guided neural networks (PGNN) to predict pressure drop and liquid holdup is proposed. Based on the flow mechanism analysis of different flow patterns, the structure of PGNN is designed according to the calculation process of the mechanism model. Key physical intermediate variables such as shear stress and friction coefficient are added to the model as neurons. Physical constraints in gas-liquid two-phase flow are added to the loss function to give physical significance to neurons. 1390 publicly available experimental data are collected for model training and testing. Due to the uneven distribution of experimental data, the local outlier factor (LOF) algorithm is used to screen outlier of data. By comparing PGNN with other ML models, empirical models, and semi empirical models, it is proved that integrating mechanism into the ML model improves the accuracy and physical consistency. This research presents a fresh outlook on the investigation of the flow dynamics in gas-liquid two-phase systems.

Fast Detection of the Single Point Leakage in Branched Shale Gas Gathering and Transportation Pipeline Network with Condensate Water

The node pressure and flow rate along the shale gas flow process are analyzed according to the characteristics of the shale gas flow pipe network, and the non-leaking and leaking processes of the shale gas flow pipe network are modeled separately. The changes in pressure over time along each pipe segment in the network provide new ideas for identifying leaking pipe sections. This paper uses the logarithmic value of pressure as the basis for judging whether the flow pipe network is leaking or not, according to the process of varying flow parameters resulting in the regularity of leakage. A graph of the change in pressure of the pipe section after the leak compared to the pressure of the non-leaking section of pipe over time can be plotted, accurately identifying the specific section of pipe with the leak. The accuracy of this novel method is verified by the leakage section and statistical data of the shale gas pipeline network in situ used in this paper.

A defect contour imaging method of small diameter pipeline based on self-made three-dimensional magnetic sensor

PurposeThe purpose of this paper is to use the corresponding magnetic sensor and detection method to detect and image the defects of small diameter pipelines. Urban gas pipeline is an energy transportation tool for urban industrial production and social life, which is closely related to urban safety. Preventing the occurrence of urban gas pipeline transportation accidents and carrying out pipeline defect detection are of great significance for the urban economic and social stability. To perform pipeline defect detection, the magnetic flux leakage internal detection method is generally used in the detection of large-diameter long-distance oil and gas pipelines. However, in terms of the internal detection of small-diameter pipelines, due to the heavy weight, large structure of the detection device and small pipe diameter, the detection is more difficult.Design/methodology/approachIn order to solve the above matters, self-made three-dimensional magnetic sensor and three-dimensional magnetic flux leakage imaging direct method are proposed for studying the defect identification. Firstly, for adapting to the diameter range of small-diameter pipelines, and containing the complete information of the defect, a self-made three-dimensional magnetic sensor is made in this paper to improve the accuracy of magnetic flux leakage detection. And on the basis of it, a small diameter pipeline defect detection system is built. Secondly, as detection signal may be affected by background magnetic field interference and the jitter interference, the complete ensemble empirical mode decomposition with adaptive noise method is utilized to screen the detected signal. As a result, the useful signal is reconstructed and the interference signal is removed. Finally, the defect contour inversion imaging of detection is realized based on the direct method of three-dimensional magnetic flux leakage imaging, which includes three-dimensional magnetic flux leakage detection data and data segmentation recognition.FindingsThe three-dimensional magnetic flux leakage imaging experimental results shown that, compared to the actual defects, the typical defects, irregular defects and crack groove defects can be analyzed by the magnetic flux leakage defect contour imaging method in qualitative and quantitative way respectively, which provides a new idea for the research of defect recognition.Originality/valueA three-dimensional magnetic sensor is made to adapt the diameter range of small diameter pipeline, and based on it, a small-diameter pipeline defect detection system is built to collect and display the magnetic flux leakage signal.

Experimental and model research on judging liquid accumulation in pipelines under the action of surfactant

Foam drainage gas extraction is applied in various natural gas extraction scenarios, such as water-bearing gas wells, gas fields with high water content, and wet natural gas pipeline transport, with the goal of enhancing extraction efficiency and lowering production costs. A common issue in foam-carrying liquid gas wells and wet natural gas pipelines is the large errors observed in the prediction model for liquid accumulation onset, derived using ellipsoidal droplets. Additionally, this model is only applicable to a single surfactant type and concentration. To investigate the effects of different types and concentrations of surfactants on the onset of liquid accumulation. This paper re-establishes the critical foam-carrying flow rate model for spherical cap-shaped foam droplets using Newton's laws of motion, through an analysis of their motion state within the air core. Through the critical foam-carrying flow rate test experiments and foam droplet deformation test experiments to obtain critical foam-carrying flow rate model in the surface tension, foam density, Weber number, drag coefficient and other parameters of the change rule and calculation method. The model's validity was further confirmed using field-measured production data from foam-carrying liquid gas wells, demonstrating accurate validation results. Compared to the previous model, this new model treats foam droplets as spherical cap-shape and introduces a dimensionless scaling factor and foaming capacity to quantify the impact of surfactant types and concentrations on foam droplet surface tension and density. This enhances the model's applicability across different types and concentrations of surfactants with greater accuracy. This offers an efficient, precise, and versatile method for predicting liquid accumulation in foam-carrying liquid gas fields, thereby enhancing the efficiency and safety of gas extraction.

Competitiveness of Export-Oriented Systems of Long-Range Energy Supply

The paper examines process chains including production, transport, and conversion of energy resources from Siberia and the Russian Far East to Asian countries. The study aims to find the most effective ways to supply energy to end consumers at various distances. The options considered include pipeline transport of natural gas from eastern regions of Russia to Asian countries; rail transport of coal from Russian export-oriented deposits to Asian countries; natural gas conversion into methanol, with methanol transport through pipelines of various diameters to Asian countries; and coal conversion into methanol, with methanol transport through pipelines of various diameters to Asian countries. Optimization is performed using previously developed mathematical models.