Transmission Pipelines Research Articles

Internal leakage rate prediction and unilateral and bilateral internal leakage identification of ball valves in the gas pipeline based on pressure detection

In the petrochemical industry, the ball valve internal leakage has been identified as a significant cause of production safety accidents, leading to mass casualties and economic losses. Depending on the flowing direction of the fluid, the form of ball valve internal leakage can be separated into unilateral and bilateral internal leakage. If a ball valve has a unilateral internal leakage, it is capable to play a sealing role, which can reduce gas venting and economic losses during natural gas fire operations. Therefore, this study aimed to develop a method for predicting the internal leakage rate and recognizing the unilateral and bilateral internal leakage used in gas transmission pipelines. For predicting the ball valve internal leakage rate, an Adaboost Integrated Circular Search Algorithm Optimised Support Vector Regression (CSA-SVR-Adaboost) model was employed and compared with other models. The CSA-SVR-Adaboost model demonstrated superior performance, displaying the lowest errors and highest correlation coefficients compared to the other models considered. Furthermore, this study aimed to identify unilateral and bilateral internal leakage of ball valves. To achieve this, a Dung Beetle Optimization Algorithm for Optimizing Kernel Extreme Learning Machine (DBO-KELM) model was adopted and evaluated based on its recognition performance. The recognition accuracy of DBO-KELM was 85.19%, surpassing the recognition accuracy of the Extreme Learning Machine (ELM) and Kernel Extreme Learning Machine (KELM) algorithms by 9.5% and 14.9%, respectively.

Performance Analysis of Deep Learning Implementation in Operational Condition Forecasting of a Gas Transmission Pipeline Network

Monitoring natural gas transmission in a pipeline network is important to maintain the supply and demand balance in natural gas transactions and distribution. Gas pressure, temperature, flowrate, and gas properties must be monitored during the transmission process. These variables, also known as operational conditions, need to be simulated carefully to understand the dynamics and behavior over time. Commonly used physical equations, such as thermodynamic or hydraulic equations, have limitations in simulating future trends because they need some known boundary conditions to be solved. In that case, data-driven method is needed, especially nowadays when data management is widely implemented. This paper implements a deep Recurrent Neural Network (RNN) to forecast the future behavior of gas pressure as an operational condition in a gas pipeline network receiving platform. Different types of recurrent cells are used, i.e., Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). The model is trained in 8 years of a gas pipeline network operational data. Historical flowrate data in the end-nodes become the forecast input in addition to the past pressure data. The sensitivity of the model and learning parameters is experimented with and analyzed to understand the capacity of the RNN in the given task. Mean absolute error is set as the satisficing metric, whereas the training time is set as optimizing metrics. The obtained best model successfully forecasts the future pressure of one day ahead with only around 2% relative error.

Greenhouse gas emissions from U.S. crude oil pipeline accidents: 1968 to 2020

Crude oil pipelines are considered as the lifelines of energy industry. However, accidents of the pipelines can lead to severe public health and environmental concerns, in which greenhouse gas (GHG) emissions, primarily methane, are frequently overlooked. While previous studies examined fugitive emissions in normal operation of crude oil pipelines, emissions resulting from accidents were typically managed separately and were therefore not included in the emission account of oil systems. To bridge this knowledge gap, we employed a bottom-up approach to conducted the first-ever inventory of GHG emissions resulting from crude oil pipeline accidents in the United States at the state level from 1968 to 2020, and leveraged Monte Carlo simulation to estimate the associated uncertainties. Our results reveal that GHG emissions from accidents in gathering pipelines (~720,000 tCO2e) exceed those from transmission pipelines (~290,000 tCO2e), although significantly more accidents have occurred in transmission pipelines (6883 cases) than gathering pipelines (773 cases). Texas accounted for over 40% of total accident-related GHG emissions nationwide. Our study contributes to enhanced accuracy of the GHG account associated with crude oil transport and implementing the data-driven climate mitigation strategies.

Optimization for Pipeline Corrosion Sensor Placement in Oil-Water Two-Phase Flow Using CFD Simulations and Genetic Algorithm.

Internal corrosion is a major concern in ensuring the safety of transmission and gathering pipelines in Structural Health Monitoring (SHM). It usually requires numerous sensors deployed inside the piping system to comprehensively cover the locations with high corrosion rates. This study presents a hybrid modeling strategy using Computational Fluid Dynamics (CFD) and Genetic Algorithm (GA) to improve the sensor placement scheme for corrosion detection and monitoring. The essence of the proposed strategy harnesses the well-validated physical modeling capability of the CFD to simulate the oil-water two-phase flow and the stochastic searching ability of the GA to explore better solutions on a global level. The CFD-based corrosion rate prediction was validated through experimental results and further used to form the initial population for GA optimization. Importantly, fitness was defined by considering both sensing effectiveness and cost of sensor coverage. The hybrid modeling strategy was implemented through case studies, where three typical pipe fittings were used to demonstrate the applicability of the sensor layout design for corrosion detection in pipelines. The GA optimization results show high accuracy for sensor placement inside the pipelines. The best fitness of the U-shaped, upward-inclined, and downward-inclined pipes were 0.9415, 0.9064, and 0.9183, respectively. Upon this, the hybrid modeling strategy can provide a promising tool for the pipeline industry to design the practical placement.

Investigation of a carbon monoxide poisoning accident with a hidden source

In June 2022, a carbon monoxide poisoning accident with hidden source occurred in a bonded gold/silver wire manufacturing enterprise in Guangzhou, causing 10 people to be poisoned, of which 1 was caused by carbon monoxide poisoning and 9 by carbon monoxide contact reaction. The symptoms were dizziness, fatigue and vomiting. After 5 to 7 h, the saturation of carboxyhemoglobin in finger pulse was 4% to 10%, and the saturation of carboxyhemoglobin in blood gas biochemical analysis was 1.9% to 5.8%. The concentration of carbon monoxide detected in the carbon borne purification plant of the enterprise was 34.46-37.26 mg/m(3). It was judged that the accident was carbon monoxide poisoning caused by carbon monoxide gas being transported to the work post along the gas transmission pipeline due to abnormal operation of the carbon borne purification plant. By investigating the source and cause of poison, this paper provides a warning for the similar process to prevent similar events, and provides a new idea for the identification of chemical poisoning risk. At the same time, it is warned that similar enterprises should fully consider the risk of poisoning under specific circumstances, strengthen equipment maintenance and repair, and prevent the occurrence of similar incidents.

A Methodology to Combine Shaking and Ground Failure Models for Forecasting Seismic Damage to Buried Pipeline Networks

ABSTRACT How does an earthquake affect buried pipeline networks? It is well known that the seismic performance of buried pipelines depends on ground failures (GFs) as well as strong ground shaking (SGS), but it is unclear how the various types of earthquake hazards should be collectively combined, as existing methodologies tend to examine each of the earthquake hazards separately. In this article, we develop a probability-based methodology to consistently combine SGS with three types of GF (surface faulting, liquefaction, and landslide) for forecasting seismic damage in buried pipeline networks from a given earthquake rupture scenario. Using a gas transmission pipeline example, we illustrate how the proposed methodology enables others (e.g., researchers, pipeline operators who manage distribution lines, and consultants) to modularly combine various models such as those for estimating probability of GF, permanent ground displacements, and pipeline fragility. Finally, we compare the proposed methodology against the Hazus methodology to explore implications from considering each hazard one at a time.

The optimum use of high-strength steel in the construction of gas transmission pipeline

PurposeThe aim of this study is to assess the opportunity for the development of hydrocarbon transportation using high-strength steel (HSS) in pipeline construction in terms of cost savings and reliability.Design/methodology/approachSeveral optimizations of pipeline design and operations were performed to estimate the total life-cycle cost variation associated with different grades of high-strength steel. The generalized reduced gradient (GRG) method was used in an Excel table to determine optimal total life cycle each pipeline. Variables used in this optimization with respect to each steel grade were as follows: pipeline external diameter, wall thickness, number of compression stations and installed power in each compression station. The reliability of a pipeline with optimal cost was assessed to highlight the impact of steel grade on pipeline reliability.FindingsThe study showed that the cost reduction is strongly dependent on the adopted gas pipeline configuration. The number of compression stations and external diameter are the main factors influencing the pipeline total life cycle cost, while the steel price seems to have a minor effect, the reduction of the gas pipeline total life cycle does not exceed 5% even with a 50% difference in pipe steel prices between X70 and X100 steels. On the other side, for the same external diameter, X100 steel presents better pipeline reliability against carbonic corrosion compared to X70 steel.Practical implicationsThe main contribution of this study is to provide a decision-support tool to help pipeline constructors enhance the profitability of natural gas transmission pipelines. The optimization method used is simple to use for design engineers during a feasibility study.Originality/valueThe present study presents one step to fill the gap concerning the question of balancing the trade-off between cost savings and structural reliability in high-strength steel pipelines during the early stages of feasibility studies. The optimal design and operations parameters ensuring cost savings on total life cycle costs are identified via an optimization method. The impact of selected optimal parameters on the long-term pipeline service life was estimated via a structural reliability analysis.

Experimental Evaluation of Kinetic Behavior of Asphaltene Particles: Effect of Temperature, Shear Stress, and Inhibitors

Summary Asphaltene deposits under a variety of temperatures and shear stresses in reservoirs, wells, and crude oil transmission pipelines, and it is currently one of the most serious problems in the oil industry. The size of asphaltene particles strongly affects the deposition rate. The particle size is mainly determined by aggregation rate that depends on shear rate and temperature. Therefore, different shear rates of 127 s–1 and 254 s−1 were applied within Couette flow at 25°C, 45°C, and 65°C, and the particle size was analyzed by using an optical microscope. Crude oil viscosity and asphaltene solubility were determined using a capillary tube viscometer and IP143 procedure, respectively. In this work, the effects of four additives, namely, dodecyl benzene sulfonic acid (DBSA), nonyl phenol (NP), salicylic acid (SA), and benzoic acid (BA), were studied on the aggregation of asphaltene particles in a light crude oil. The additives were chosen based on their functional groups. Moreover, asphaltene functional groups were determined using a Fourier transform infrared (FTIR) analyzer to better understand the behavior of inhibitors in preventing the aggregation of asphaltene particles at different conditions. DBSA, BA, and SA were inhibitors, and NP behaved as a promoter. According to the results, the presence of acidic groups, SO3H in DBSA and COOH in SA and BA, increases the interaction of inhibitor with asphaltene and so reduces the aggregation of asphaltene particles. The stronger acidic group of DBSA improved its performance compared to other inhibitors. Both increasing temperature and increasing shear stress resulted in higher collisions of asphaltene particles and thus lowered the efficiency of inhibitors at a constant concentration.

Flow Improvers and Pipeline Internal Coating Benefits and Limitations with Respect to Pipeline Capacity Enhancement

This article illustrates the outcome of a theoretical examination of applying internal coating and flow improver to gas and liquid pipeline systems. A test case of a 12-inches, 18-inches, 24-inches, 30-inches, 36-inches, and 42-inches diameter gas and liquid transmission pipelines evaluates hypothetically, synergistic use of pipeline internal coating with flow improver to enhance flow rate of a pipeline and minimize internal friction. The improvements in pipeline hydraulics are recognized and the enhancement of pipeline capacity calculated over a broad range of parameters. The hydraulic benefits are presented as percentage increase in pipeline capacity using flow equations. Analysis shows that internal coating of pipelines plus injection of flow improver is hydraulically and economically viable for both gas and liquid pipelines with a typical capacity increase greater than 116%. Corrosion protection and safety is improved with low operating cost.

The development of complex engineering models using artificial neural network-based proxy models for life cycle assessments of energy systems

The energy industry has been using life cycle assessment (LCA) to determine the environmental impact of projects. Obtaining accurate data of certain industrial activities requires complex engineering models that have long computing times, are difficult for non-experts to use, and may contain confidential data. This work examines using proxy models based on quadratic and artificial neural network (ANN) regression to create an accurate, easy-to-use, black-box model that can be easily shared. Generating target values from the engineering software needed for training can be time-consuming, hence, adaptive sampling methods are examined (random, spread, high error, and the combo method [50/50 random/high error]). Two case studies were examined: a transportation fuel LCA of Maya, Bow River, and mined bitumen crude oils; and an LCA of a natural gas transmission pipeline (NGTL). This work found that ANN proxy models are more accurate than quadratic regression, and the high error sampling method reduced the maximum error but increased the average error. The combo and high error methods using 3000 to 4000 samples achieved similar maximum errors to the random method using 10,000 samples. Because of uncertainty in LCA input values, reducing average error is less valuable than reducing extreme errors. For the NGTL case study, the ANN model was able to reduce the average and max error by 67% and 68%, respectively, while using 35% fewer coefficients; ANN models are more appropriate for complex nonlinear models.

Understanding the factors and consequences of pipeline incidents: An analysis of gas transmission pipelines in the US

The contemporary world is confronted with a significant and pressing challenge in the form of the energy crisis. Natural gas represents a potential solution to the crisis, and its transportation relies heavily on transmission and distribution pipelines. Regrettably, these pipelines have witnessed a significant number of severe incidents in recent years due to various reasons. This study aims to investigate the influence of different background factors on pipeline incidents triggered by distinct causal factors, using incident records from the PHMSA in the United States. This study reveals that outside force damage is the most frequent causal factor, responsible for 41.21% of total incidents. The failure rate of gas transmission pipelines is notably affected by the operational pressure ratio and the laying location class. Moreover, this study explores the relationship between various factors and each causal factor leading to the incident, assessing the incident's consequences in terms of type, injury, fatality, and total cost. Generally, incidents involving larger-diameter pipelines with higher operational pressure ratios and deployed in higher location classes have more severe consequences, with the highest injury rate, fatality rate, and cost rate being 1.728 × 10−4, 1.043 × 10−4, and 1953.36 $ per incident per kilometer, respectively. These findings contribute to a better understanding of pipeline failures and can aid in the development of accurate and effective predictive models for gas pipelines.

Parametric Analysis of Conductive Coupling of Transmission Line Tower Grounding and Pipeline in Multilayer Soil

Parametric Analysis of Conductive Coupling of Transmission Line Tower Grounding and Pipeline in Multilayer Soil

Experimental Investigation of Gas Transmission Pipeline Blockage Detection Based on Dynamic Pressure Method

The blockage of natural gas pipelines caused by solid deposits such as hydrates is one of the major safety risks to transmission pipeline systems. The key to effective blockage relief or removal is to determine the location and severity of the blockage. In recent years, the pressure pulse wave method has been considered as a practical detection method due to its fast response time, simplicity of operation, and extended detection distance. Nevertheless, the current implementation of this method in pipelines indicates that the accuracy in detecting blockages is very low. To improve the accuracy of the pressure wave blockage detection technique in our experiments, a series of experiments were carried out to detect and locate hydrate blockages in natural gas pipelines based on the pressure wave method using a separate pipeline system of 22 mm diameter and 106 m length. The experimental results show that the accuracy of the blockage location prediction based on the pressure pulse wave method is within 5%. Still, the blockage’s cross-sectional shape can significantly affect the intensity of the reflected wave, with a maximum prediction error of 35%.

Limit load prediction analysis of X80 pipeline containing corrosion in mountainous landslide section

Currently in China X80 pipeline laying mostly concentrated in mountainous areas, oil and gas pipeline transmission distance, through the complex and diverse terrain, the pipeline by the buried environment will not only appear corrosion defects, but also by the impact of soil slippage to reduce the pressure-bearing capacity of the pipeline, resulting in pipeline perforation, broken, leading to oil and gas leakage accidents, further leading to fire, explosion and environmental pollution and other major safety accidents. In view of the important strategic position of oil and gas pipelines and the severity of accident hazards, it is important to study the ultimate bearing capacity of buried corroded pipelines. With this purpose, this paper analyzes the existing pipe-soil coupling theories based on the large-scale test in the field, optimizes the nonlinear contact model, and establishes a nonlinear corroded pipe-soil interaction model and verifies its accuracy. By using the existing soil load application function and coupling the actual soil slip data, the inhomogeneous movement of soil slip is realized. Based on the existing corrosion size characterization methods, the effect of corrosion size on the ultimate load carrying capacity of intact pipes was further verified by means of a combination of FEA and experiments. Specifically, the effects of soil slip under no load and internal pressure coupled conditions on the mechanical behavior of corroded pipelines are compared and analyzed; the necessity of considering soil slip is clarified; the influencing factors such as pipe corrosion size, operating internal pressure, and corrosion position are analyzed to reveal the failure mechanism of buried corroded pipelines in mountainous areas. By using the pipe displacement at the strain failure as the evaluation index, and using the dimensional analysis method to reveal the relationship between each influencing factor and the ultimate load, the ultimate load prediction formula for corroded pipelines under soil slip actions is derived. The research results can help evaluate the safety condition of existing operating pipelines, release early warning for the structure safety of pipelines, and provide guidance for the safety protection of pipelines in mountainous areas.

Computational fluid dynamic modeling of methane-hydrogen mixture transportation in pipelines: Understanding the effects of pipe roughness, pipe diameter and pipe bends

A computational fluid dynamic modeling framework is developed to quantify frictional losses, assess the energy efficiency of transport, and characterize the mixing behavior of methane-hydrogen blends across representative regions of a large gas network such as transmission, distribution, and household pipeline sections. The principal conclusions from the present study are: (i) The increase in the energy required for transporting hydrogen as methane-hydrogen blends depends on the volume fraction of hydrogen, the nature of the flow conditions, pipe diameter, pipe roughness and pipe bends. (ii) Pipelines that have larger surface roughness or smaller diameters or those with bend sections require greater energy for transporting gas blends. (iii) The methane-hydrogen gas blends develop a core-annular flow pattern under steady state conditions with the denser and more viscous methane flowing near the pipe wall as the annulus while the less dense and less viscous hydrogen concentrated more towards the mid-sections of the pipelines.

Molecular dynamics study of hydrogen-induced cracking behavior of ferrite–pearlite gas transmission pipeline steel

Molecular dynamics study of hydrogen-induced cracking behavior of ferrite–pearlite gas transmission pipeline steel

Water Distribution Challenges in Northeast Trinidad and Tobago

Provision of a reliable supply of water with adequate pressures is a paramount challenge for the water distribution network in Northeast Trinidad and Tobago. Customers in this region, served by the Water and Sewerage Authority of Trinidad and Tobago experience difficulties in obtaining a pipe borne supply of water as they reside on areas of high elevation or are at the farthest end of the distribution system. Areas where water supply challenges are a problem are Oropoune Gardens Piarco, Upper Five Rivers Arouca, Windy Hill Arouca, Edna Hill Arouca, Lillian Heights Arouca, The Foothills Arouca, Pineridge Heights Housing Development and Ridgeview Heights Housing Development Bon Air North. Sources of supply to these impacted areas are the North Oropouche Water Treatment Plant, the Hollis Water Treatment Plant, the Tacarigua High Lift Station and Arouca wells. Challenges in the water supply are a consequence of obsolete pipelines, numerous leaks, failure of mechanical equipment and a shortened duration of supply. This paper identifies the inefficiencies and challenges of the water distribution system in this region by simulating flow through crucial transmission and distribution pipelines using ANSYS Fluent simulation. The Hazen-Williams equation was used to calculate frictional pressure loss in the respective crucial pipelines. Using the results from both analyses, prospective solutions to alleviate and eliminate the inadequate water supply experiences faced by customers in these areas were advocated.

Mechanical Excitation of Large-scale Sprinkler Based on PWM Technology

In order to improve the life of a variable displacement sprinkler irrigation machine, this paper establishes a finite element analysis model to analyze its mechanical excitation law. First of all, in the process of model selection, this paper selects the first span of variable sprinkler as the mechanical excitation analysis model based on the actual operation. Then, in the analysis and setting, the terrain difference is ignored, and the pressure values on the main water transmission pipeline of the first span are equal. Finally, the simulation experiment shows that the amplitude of mechanical excitation is positively correlated with the frequency and amplitude of pressure pulsation, and it is mainly when the valve is closed that caused by the pressure pulsation. It provides research support and direction reference for further weakening mechanical excitation.

The impact of corrosion on the adsorption of gaseous Hg0 onto the surface of steels: Implications for decommissioning in the oil and gas industry

The rate of decommissioning of global oil and gas production facilities will accelerate over coming decades, as mature developments reach the end of use, and consumers transition towards renewable energy. Decommissioning strategies should include thorough environmental risk assessments which consider contaminants which are known to be present in oil and gas systems. Mercury (Hg) is a global pollutant that occurs naturally in oil and gas reservoirs. However, knowledge of Hg contamination in transmission pipelines and process equipment is limited. We investigated the potential for accumulation of Hg0 within production facilities, particularly those transporting gases, by considering the deposition of Hg onto steel surfaces from the gas phase. Following incubation experiments in a Hg saturated atmosphere; fresh API 5L‐X65 and L80–13Cr steels were found to adsorb 1.4 × 10−5 ± 0.04 × 10−5 and 1.1 × 10−5 ± 0.04 × 10−5 g m−2, respectively, while corroded samples of the same steels adsorbed 0.12 ± 0.01 and 0.83 ± 0.02 g m−2; an increase in adsorbed mercury by four orders of magnitude. The association between surface corrosion and Hg was demonstrated by laser ablation ICPMS. The levels of Hg measured on the corroded steel surfaces indicates a potential environmental risk; therefore, mercury speciation (including the presence of ß-HgS, not considered in this study), concentrations and cleaning methods should be considered when developing oil and gas decommissioning strategies.

Study on numerical simulation of leakage and diffusion law of parallel buried gas pipelines in tunnels

Parallel buried gas pipelines in tunnels are located in a confined space environment, where natural gas is vulnerable to accumulating to the minimum explosion limit concentration after a leakage accident. Therefore, to reduce the time for locating the leakage source after an accident and compensate for the loss of emergency response, an experimental model for scaling parallel gas transmission pipelines in tunnels was established and the dispersion characteristics and influencing factors of continuous leakage of natural gas within buried soil and in tunnel space were investigated numerically, and the correlation between the volume of the explosion range of natural gas within the tunnel space and each influencing factor was explored using gray correlation analysis. The research shows that the leakage dispersion process of parallel buried gas pipelines in tunnels includes seepage leakage in the soil region and diffusion transport in the tunnel air region. In the soil region, natural gas from the pipeline leak forms a circular shape and tends to percolate upward due to the combined effect of pressure and concentration gradients.In the tunnel air region, the spatial dispersion of natural gas concentration obeys a multivariate Gaussian distribution, and the temporal dimension is divided into three phases: the initial phase of leakage, the spreading phase and the stable phase of leakage. The diffusion speed of natural gas is positively correlated with the operating pressure of pipeline. The concentration peak value (ymax) at the leakage orifice position and the leakage aperture (dx) approximately meet the linear relationship: ymax= 7.62dx. The diffusion path of natural gas is greatly influenced by the orientation of the pipeline perforations, and the tunnel walls have a directional effect on the diffusion of natural gas. The main factors affecting the volume of the explosion range of natural gas within the tunnel space are parallel pipeline leakage pressure, pipeline leakage aperture, parallel pipeline leakage position, pipeline operating pressure, and pipeline leakage direction, with grey correlation coefficients of 0.76, 0.675, 0.662, 0.553, and 0.55. The proposed model was demonstrated be able to simulate and predict the diffusion of natural gas under the accidental leakage of buried gas pipelines in tunnels. And the results of this study can guide the installation of buried gas pipelines crossing mountain tunnels to prevent accidents.