Pipeline Transportation Research Articles

Study of the effect of glycine on the growth and mobility of CO2 hydrate slurries in the loop

The stability of CO2 hydrate slurry mobility is essential for the progression of diverse potential Carbon Capture, Utilization, and Storage (CCUS) applications, while also playing a critical role in maintaining the safety of gas–liquid two-phase flow transportation pipelines. In this study, the effect of glycine on the growth and flowing characteristics of CO2 hydrate slurry was investigated for the first time using a high-pressure recirculating flow loop. A comprehensive analysis of the hydrate growth, morphology, and rheological behavior was performed. The results show that the induction time of CO2 hydrate formation could be effectively prolonged by the presence of glycine in the loop, but it cannot inhibit its rapid formation in the rapid growth period. Meanwhile, agglomeration of the slurry and adsorption on the pipe wall during the flow process were observed with the presence of glycine. The flow pattern of pure CO2 hydrate slurry was gradually transitioned from expansion flow to pseudoplastic flow with the increase of hydrate amount, and shear thinning was observed when the slurry content was not less than 7.6%. The addition of glycine significantly increases the viscosity of the slurry, which makes the slurry behave as an expanding fluid in a wider range. The tendency of shear thickening and the range of shear thickening of the slurry were enlarged. This study raises mobility security concerns for the potential application value of glycine as an LDHI. It also serves as a valuable reference for furthering the advancement of CO2 slurry as a potential application for CCUS.

Investigation of scaling-down experiments for accidental CO2 leakage dispersion risks in constant-pressure transportation pipelines within the CCUS process

Within the framework of strategies to prevent global warming, the safety of CO2 transportation pipelines requires thorough hazard analysis. Accidental leakage during long-distance CO2 transport, influenced by the size of the leakage opening, typically occurs under constant pressure conditions in the CCUS process. This paper introduces an innovative scaled experimental apparatus with an elliptical orifice, designed to simulate leakage due to free rupture in pipelines. The goal is to understand the risk characteristics of constant-pressure leakage in transportation pipelines. The results indicate that during leakage, the pressure drop in the source CO2 pipeline is less than 0.3013 MPa/s, which can be considered constant pressure leakage. The Mach disk size dm has a linear relationship with the elliptical leakage orifice ab. The scaled experiments also show that temperatures can drop to as low as −78°C, indicating significant low-temperature risks. This scaling experiment provides a new approach for predicting and mitigating diffusion risks in long-distance pipeline transportation by examining the relationship between pipeline length and orifice diameter. The research data and results contribute to a deeper understanding of the safety aspects of long-distance transportation of CO2 under constant pressure leakage conditions, providing a basis for risk assessment of leakage accidents and environmental protection measures.

Strategic management of CO2: A scalable model for CCS in decarbonised societies

In future decarbonised energy systems, residual carbon emissions require strategic planning and management. In environmental management, an evaluation of carbon removal considering local geographic frameworks is needed. This paper introduces a scalable and adaptable model for evaluating the economics and geography of future carbon capture and storage (CCS) configurations across geographical scales, covering capture, transport, and storage of carbon. The model is applied to the North Denmark Region, showing that future energy production carbon sources will be concentrated in Thisted and Jammerbugt, while industrial sources remain in Aalborg and Rebild municipalities. Carbon transport configurations, including truck, pipeline, and shipping are assessed, for the carbon to be stored in onshore and offshore geological storages. The regional scale findings suggest that pipelines and onshore storage provide the most economical configuration. However, a sensitivity study using a smaller geographical scope indicates potential for optimising carbon transport by evaluating both carbon volume and distance. The paper discusses how the model's flexibility and scalability enable the integration of alternate cost components, thereby supporting the calculation of the carbon repurposing potentials, including carbon capture, utilisation, and storage (CCUS) configurations.

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.

Research on Predicting the Mechanical Characteristics of Deep-Sea Mining Transportation Pipelines

Deep-sea mining, as a critical direction for the future development of mineral resources, places significant importance on the mechanical characteristics of its transportation pipelines for the safety and efficiency of the entire mining system. This paper establishes a simulation model of the deep-sea mining system based on oceanic environmental loads and the mechanical theory of deep-sea mining transportation pipelines. Through a static analysis, the effective tension along the pipeline length, the maximum values of bending moment, and the minimum values of bending radius are determined as critical points for the dynamic analysis of pipeline mechanical characteristic monitoring. A dynamic simulation analysis of the pipeline’s mechanical characteristics was conducted, and simulation sensor data were obtained as inputs for the prediction model construction. A prediction model of pipeline mechanical characteristics based on the BP neural network was constructed, with the model’s prediction correlation coefficients all exceeding 0.95, enabling an accurate prediction of pipeline state parameters.

Online detection of mixed oil interface in multi-product pipeline using near-infrared spectroscopy

To ensure the quality of refined oil products of sequential transportation, it is necessary to monitor and judge the interfaces between pure oils and mixed oil for guiding accurate mixed oil cutting. In this study, near-infrared spectroscopy (NIRS) was used to investigate the change trend of oil concentration and thus judge the interfaces. The methods of standard deviation of continuous spectra, principal component analysis, difference spectrum, and vector angle θ were used to analyze the online oil NIR spectra to detect the interfaces, respectively. The results show that θ of the spectra pretreated by the combination of airPLS and 1st derivative is the best for reflecting the concentration change trend of mixed oil and judging the interfaces. The interface between the forward pure oil and mixed oil can be judged by a fixed θ threshold, and the interface between the rear pure oil and mixed oil can be judged by a fixed first-order derivative value of the five-parameter logistic fitted curve of θ. This method is not affected by the interference and oil composition change of different batches and does not require oil properties and pipeline parameters, thus it has a good prospect in the oil pipeline transportation field.

Determining onshore or offshore hydrogen storage for large offshore wind parks: The North Sea Wind Power Hub case

The large-scale integration of renewable energy sources leads to daily and seasonal mismatches between supply and demand and the curtailment of wind power. Hydrogen produced from surplus wind power offers an attractive solution to these challenges. In this paper, we consider a large offshore wind park and analyze the need for hydrogen storage at the onshore and offshore sides of a large transportation pipeline that connects the wind park to the mainland. The results show that the pipeline with line pack storage, though important for day-to-day fluctuations, will not offer sufficient storage capacity to bridge seasonal differences. Furthermore, the results show that if the pipeline is sufficiently sized, additional storage is only needed on one side of the pipeline, which would limit the needed investments. Results show that the policy which determines what part of the wind power is fed into the electricity grid and what part is converted into hydrogen has a significant influence on these seasonal storage needs. Therefore, investment decisions for hydrogen systems should be made by considering both the onshore and offshore storage requirements in combination with electricity transport to the mainland.

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.

Research on the application of artificial intelligence tools to predict the operating temperature and pressure of the pipeline transportation system at the Hai Thach - Moc Tinh field

The observation of operating parameters for the single-phase or multi-phase flows of oil and gas pipelines always plays an important role and prerequisite in daily operation. The inlet and outlet parameters of the pipeline such as pressure and temperature will greatly affect the efficiency of the production and transportation process of fields. These parameters are very important. It must be required to observe carefully and strictly. In fact, pressure and temperature signal gauges will always be set up at the inlet and outlet of the pipeline for continuously variable transmission of the signal to the central control room, then the operator can observe regularly. Alarms will be triggered when the signal goes out of the setting operation area. However, the operational parameters transmitted from this gauge are only available after the actual fluid flow passes through the pipeline. This will limit when the operator needs to apply calculation methods to pre-predict the flow regime, and operating parameters of the fluid in the pipeline when fluid flows has not passed through the pipeline. From that approach, the paper presents the result of research on the application of machine learning algorithms (ML) to build models to predict operating conditions of three-phase flows in the pipeline at Hai Thach- Moc Tinh field based on input parameters such as the open of wellhead flow control valve of wells located in wellhead platform WHP-MT1, WHP-HT1, and the commercial gas volume. The results of the research show that the ML calculation method gives the result which is only +/-2 barg/20C difference compared to the field data obtained from pressure (HT1-PT-0911) and temperature (HT1-TI-0911) signals set up at the outlet of the transportation pipeline at the Hai Thach-Moc Tinh field.

Numerical simulation of pressure loss and flow characteristics in combined elbow pipes for solid-liquid two-phase flow.

The transport of solid-liquid two-phase flow is widely used in water conservancy, environmental protection, and municipal engineering. Accurate pressure loss calculation is crucial for hydraulic transport pipelines, particularly in the case of bends, valves, and other deformation parts. These factors directly impact the energy consumption and the investment of the system. This paper employed the Euler-Euler multiphase flow model to investigate the characteristics of solid-liquid two-phase flow in vertically positioned combined elbows. The model was initially validated using data from the literature. Subsequently, based on the validated model, an investigation was conducted to determine the relationship between pressure loss and various factors, including flow velocity, combined angle, particle concentration, and particle size. Finally, the changes in velocity distribution, particle concentration, and turbulent kinetic energy were analyzed. The results indicate that the pressure loss increases with the flow velocity, tends to decrease with the combined angle, and increases with the particle concentration. The relationship between pressure loss and particle size is more complex. The velocity distribution, particle concentration, and turbulent kinetic energy exhibit the variations caused by different factors.

Machine Learning Framework for Real-Time Pipeline Anomaly Detection and Maintenance Needs Forecast Using Random Forest and Prophet Model

This paper introduces an Intelligent Model for Real-Time Pipeline Monitoring and Maintenance Prediction to enhance infrastructure integrity and operational efficiency in Nigeria's oil and gas sector. Given the country's economic dependence on oil and gas revenue, efficient pipeline transportation is crucial. However, pipelines face challenges such as corrosion, mechanical failures, vandalism, and theft, leading to economic losses and environmental risks. Current monitoring systems are mainly reactive, lacking timely anomaly detection and predictive maintenance capabilities. To tackle these challenges, the study utilized sophisticated machine learning methods by combining the Random Forest classifier for real-time anomaly detection with the Prophet model for predictive maintenance forecasting. Datasets from Kaggle were used. The Random Forest classifier demonstrated robust performance with an accuracy of 93.48%, precision of 93.75%, recall of 96.77%, and an F1-score of 95.24%. The Prophet model provided accurate hourly forecasts of operational parameters, aiding proactive maintenance scheduling. Despite some errors encountered (RMSE: 21.48 and MAE: 18.17), the Mean Absolute Percentage Error (MAPE) of 14.87% indicates relatively minor discrepancies compared to actual values. In conclusion, the Intelligent Model shows significant advancements in pipeline monitoring and maintenance prediction by leveraging machine learning for early anomaly detection and timely maintenance interventions. This proactive approach aims to reduce downtime, prevent environmental damage, and optimize operational efficiency in Nigeria's oil and gas infrastructure. Future research could focus on enhancing system scalability across diverse terrains, employing advanced deep learning techniques such as Transformer Networks and Autoencoders for improved prediction accuracy, and exploring cybersecurity measures like blockchain integration to ensure data integrity and protect critical infrastructure from cyber threats.

Study on the suspending mechanism of gangue particle in coal-based solid waste slurry

In China's coal mine backfill mining projects, certain mines demonstrate an extensive filling distance that exceeds 3000 m. However, there are few researches concerning the theoretical underpinnings for slurry long-distance pipeline transportation. Gangue particles suspending in filling slurry is the prerequisite for successful long-distance pipeline transportation. This paper conducts theoretical researches on the heightened sensitivity issue of particle settling within coal-based solid waste filling slurry (CSWFS) for long-distance pipeline transportation, which can easily lead to unstable slurry concentration then pipe blockage or bursting accidents. The mechanical model for particle settling and critical non-settling particle diameter for long-distance pipeline transportation are developed based on the "solid-liquid two-phase carrier suspension fluid", and reveal the intrinsical mechanism of particle settling within CSWFS for long-distance pipeline transportation. Through the calculation of the mechanical model for critical non-settling particle diameter and particle settling, coupled with the particle diameter screening experiment, the value of critical non-settling particle diameter is determined to be 0.0067 m, and the density of solid-liquid two-phase carrier suspension fluid is 1712.37 kg/m3. The CSWFS is classified as a semi-stable slurry, lacking time-dependent suspending state required for long-distance pipeline transportation, which could lead to pipe blockage accidents. Further research into effective methods is urgently required to ensure adequate safety and adaptability for long-distance pipeline transportation of CSWFS.

N-vinylcaprolactam-acrylamide copolymer inhibition performance against 304L stainless steel corrosion in a simulated sweet-sour corrosive environment

Internal corrosion of oilfield pipes in the presence of CO2 and H2S is a significant problem in the oil and gas industry. The financial and material ramifications are immense, given that transportation pipelines are vital to the energy and gas industry. In typical oilfield industries, the prevailing approach to address corrosion issues affecting steel-based structural elements involves the incorporation of corrosion inhibitors into the corrosion system. In this study we evaluated the effectiveness of an N-vinylcaprolactam-acrylamide copolymer (NVAM) in inhibiting the corrosion of stainless steel in a 3.5% NaCl solution saturated with CO2 and containing 100 ppm H2S, which simulates a sweet/sour corrosive environment typical of oilfields Several experimental methods, such as weight loss, electrochemical techniques and surface characterization methodologies (SEM, EDS, & AFM) were used to assess the inhibitor's efficacy. The inhibitor demonstrated remarkable performance, attaining an approximately 90 % inhibition efficiency at a 100 ppm concentration. Adsorption of Poly(NVAM) adhered to the Langmuir adsorption model and functioned primarily as a cathodic inhibitor. The results obtained from the analysis of SEM, EDS, and AFM indicate that poly(NVAM) forms a protective film on the surface of the steel, thereby impeding the access of corrosive species. The protective film efficiently prevented corrosive chemicals from reaching the steel's surface.

Effects of hydrogen and specimen thickness on fracture toughness of ferritic steel welded joint

In this study, fracture behaviors of base metal and weld metal of ferritic steel welded joint in the thick wall pipeline for hydrogen transportation were investigated and the effects of hydrogen and specimen thickness (B) on fracture toughness were comprehensively considered in detail. A series of single edge notched tensile (SENT) tests for base metal and weld metal with B/W (width) ratio of 0.5, 1 and 2 were conducted with and without pre-electrochemical hydrogen charging, and crack tip opening displacement (CTOD) of δm value was obtained by the double clip gauges method. It was found that fracture toughness (δm) of base metal and weld metal decreased with increasing specimen thickness or hydrogenating, and δm of hydrogenating specimen with B/W ratio of 2 was smallest. It was believed that large specimen thickness decreased fracture toughness by constraining plastic deformation at crack tip and restricting dislocations movement, while hydrogen promoted embrittlement by reducing cohesive energy of fracture. In the hydrogenating specimen with larger thickness, there was lower dislocation density near crack tip, leading to a decrease in trapped hydrogen and intensifying the cohesive energy reduction effect, which resulted in reduced δm and the worse fracture toughness, and it means that hydrogen and specimen thickness synergistically affected fracture toughness. In addition, effect of thickness and hydrogen on decreasing fracture toughness was more pronounced for weld metal than base metal, which could be attributed to poorer plastic deformation ability of weld metal and lower dislocation density at crack tip. It is concluded that the hydrogen and thickness effects should be taken into account for the structural integrity evaluation of welded joint in hydrogen transportation pipeline.

Simulation of boost path and phase control method in supercritical CO2 pipeline commissioning process

CO2 pipeline can be applied to Enhanced Oil Recovery (EOR) projects and CO2 geological storage projects, and has high engineering application value. However, pipeline transportation of CO2 is a high-risk link in CO2 storage projects. The phase state commonly used to transport CO2 is a supercritical state with both gaseous and liquid characteristics, and there are also great challenges in the field of pipeline transportation. The existing researches have carried out a lot of exploration and application development in the heat transfer, phase change, transient and special conditions of supercritical CO2 pipeline operation.In this paper, the modeling and exploration of the commissioning process before the formal operation of the supercritical CO2 pipeline are carried out, and the boost path of the supercritical CO2 pipeline in the phase diagram under different working conditions is obtained. The model developed in this paper is based on the sensitivity analysis of the effects of variables such as ground temperature, filling pressure speed, and whether to perform pressure-stabilizing leak detection operations. The step-up path in the phase diagram of the CO2 pipeline commissioning process and the adjustment control method are obtained. And the critical temperature of each working condition that cannot avoid phase transition, thus contributing to the existing knowledge system in this field.

Repurposing natural gas pipelines for hydrogen: Limits and options from a case study in Germany

We investigate the challenges and options for repurposing existing natural gas pipelines for hydrogen transportation. Challenges of re-purposing are mainly related to safety and due to the risk of hydrogen embrittlement of pipeline steels and the smaller molecular size of the gas. From an economic perspective, the lower volumetric energy density of hydrogen compared to natural gas is a challenge. We investigate three pipeline repurposing options in depth: a) no modification to the pipeline but enhanced maintenance, b) use of gaseous inhibitors, and c) the pipe-in-pipe approach. The levelized costs of transportation of these options are compared for the case of the German Norddeutsche Erdgasleitung (NEL) pipeline. We find a similar cost range for all three options. This indicates that other criteria such as the sunk costs, public acceptance, and consumer requirements are likely to shape the decision making for gas pipeline repurposing.

Multidimensional information fusion and broad learning system-based condition recognition for energy pipeline safety

Mechanical activities near energy pipelines pose a significant threat to energy transportation safety and energy system supply. The distributed acoustic sensing (DAS) system, which is an emerging intelligent sensing technology, can help to identify threat activities outside the pipeline. However, existing research has not distinguished fine-grained threat conditions because of insufficient information utilization and real-time requirements in the DAS system dataset, resulting in a large number of false alarms and time-consuming training in practice. To address these issues, this study proposes a pipeline radial threat condition recognition model based on multidimensional information fusion and a broad learning system (MIFBLS). First, the signal is preprocessed to improve the signal-to-noise ratio and generate the original features. Then, the extracted multidimensional temporal features are dimensionally reduced through information entropy, and the time–frequency map is fused and extracted based on a pretrained deep module, thereby achieving information fusion. Finally, the BLS incremental learning strategy is adopted to enhance the updating ability of the model and reduce the burden of data increments on the model training. Comparative experiments on a real-world natural gas pipeline dataset demonstrate the effectiveness and efficiency of the proposed method, indicating the potential for real-time monitoring and intelligent identification in pipeline transportation scenarios.

Significant sliding speed effect on the friction and wear behavior of UHMWPE matrix composites

PurposeWith the rapid development of the pipeline transportation and exploitation of mineral resources, it is urgent requirement for the high-performance polymer matrix composites with low friction and wear to meet the needs of solid material transportation. This paper aims to prepare high-performance ultrahigh molecular weight polyethylene (UHMWPE) matrix composites and investigate the effect of service condition on frictional behavior for composite.Design/methodology/approachIn this study, UHMWPE matrix composites with different content of MoS2 were prepared and the tribological performance of the GCr15/composites friction pair in various sliding speeds (0.025–0.125 m/s) under dry friction conditions were studied by ball-on-disk tribology experiments.FindingsResults show that the frictional behavior was shown to be sensitive to MoS2 concentration and sliding velocity. As the MoS2 content is 2 Wt.%, composites presented the best overall tribological performance. Besides, the friction coefficient fluctuates around 0.21 from 0.025 to 0.125 m/s sliding speed, while the wear rate increases gradually. Scanning electron microscopy images, energy-dispersive spectroscopy and Raman Spectrum analysis present that the main wear mechanisms were abrasive and fatigue wear.Originality/valueThe knowledge obtained herein will facilitate the design of UHMWPE matrix composites with promising self-lubrication performances which used in slag transport engineering field.

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.

ANALYSIS OF METHODS OF ETHANE PIPELINE TRANSPORTATION

The products of hydrocarbon light fractions processing are becoming of great demand. An important component of natural gas is ethane used for high-tech products at gas chemical complexes. Ethane production in situ is a promising direction, with its subsequent transportation to gas and chemical plants. The most economical type of transport is pipeline transportation, providing the construction of a pipeline system including facilities and a linear part. Ethane is a gas that can be transported along isothermal pipelines in both liquid and gaseous states. At the same time, the question of choosing the most rational variant is relevant. The article analyzes possible methods of transporting ethane and ethane fractions along pipelines, consideres variants for pumping gas in a liquid and gaseous states, taking into account the component composition of the product at a specified productivity and initial thermal parameters to summarize recommendations when choosing the most rational method of product transportation. A method is presented for the analytical representation of the dependences of pressure, elasticity, density and viscosity on temperature for the convenient determination of physical properties of multicomponent ethane fractions. The methodological foundations of the thermal and hydraulic analysis of variants for ethane transportation in two phase states – in liquid and gaseous – with the energy efficiency assessment of gas pumping are presented. It is shown that when transporting ethane in a gaseous state, the metal consumption for the pipeline increases twice as compared with the pipeline for transporting the product in a liquid state, while energy consumption also doubles.