Gas Pipeline System Research Articles

DEVELOPMENT FACTORS OF THE REGIONAL TOURIST COMPLEX

The article identifies factors that have a significant impact on the tourism and tourism complex development. It is determined that, the tourist complex is a typical intersectional complex, with a complex system of internal connections, based on the satisfaction of different people’s needs in the realization of tourist activities. It is mentioned that, the work of leading Ukrainian specialists in the geography of tourism points to the multifaceted nature and complexity of a clear and precise division of human activity into recreation and health improvement. This has led to different views on the factors of the development of the regional tourist complex. Traditionally, taking into account the theory of complex formation, they can be grouped into the following groups: economic, social, natural, ecological. The tourism territorial organization is one of the forms of economic processes social organization. It not only allows to indicate the most effective forms of spatial organization of economic processes, but also provides a scientific basis for the concept of sustainable development in understanding the optimization of economic processes and phenomena at the regional and local levels. The environmental impact of tourism is primarily related to such varieties as ecological and rural “green” tourism. They cannot exist only in the conditions of local natural landscapes preservation. The analysis of approaches to the selection of factors for the development of regional tourist complexes allows us to state that this remains a debatable issue in the geography of tourism. It is important to note that studying these factors we can raise the issue of territorial organization of regional tourist complex. For this purpose, it is necessary to define the available specialization of its territorial components and the complexity of the provision of tourism services. For the operation of tourism entities of various types, it is necessary to have a system of transport communications, water pipelines, gas and food pipelines, lines of communication and electricity, that is, a system of production infrastructure, without which no tourist complex is possible.

Optimization and reliability of the power supply systems of a compressor station

As gas pipeline systems become larger and more complex, the importance of optimally operating and planning these facilities has increased. The capital costs and operating expenses of pipeline systems are so large that even small improvements in the use of the system can involve large sums of money. Purpose. This article proposes a method to improve the reliability and optimization of power supply systems for compressor stations. The novelty of the proposed work is the development of a new mathematical model that allows the choice of the most appropriate maintenance policies in the best way to significantly reduce costs as well as to optimize useful key performance indicators – failure rate, average time between breakdowns, the average repair time for equipment in compressor station electrical supply systems. Applying graph theory to represent this mathematical model from the schematic diagram of the different energy sources with respect to the five compressor stations is adequate. Methods. The problem that arises for the future operator or operator is, among others, how to balance two main aspects: a technical aspect and an economic aspect. The proposed methodology introduces a research algorithm to calculate the optimal values of the operating parameters of the power supply systems of compressor stations by combining technical and economic aspects in order to reduce costs and increase performance indicators. The proposed algorithm can be implemented in FORTRAN code. Results. The algorithm developed is an efficient tool for calculating maintenance costs and allows by means of programming to define the most appropriate maintenance policy. On the other hand, this technique could be used as an essential economic evaluation indicator for other equipment in order to choose among all the technically possible solutions the one which allow obtaining the best economic result. Practical value. The proposed algorithm has been examined in this third variant of the supply system with two turbogenerators. The result of the optimization shows a clear preference for selecting station C for the pipeline as this presents the minimum cost which is the definition of the algorithm optimizer. Then, it is important to adopt the most recommended maintenance policies and practices in order to ensure the availability of the power supply systems and to avoid unplanned outages with the resulting loss of production.

Toward Detection and Attribution of Cyber-Attacks in IoT-Enabled Cyber–Physical Systems

Securing Internet-of-Things (IoT)-enabled cyber-physical systems (CPS) can be challenging, as security solutions developed for general information/operational technology (IT/OT) systems may not be as effective in a CPS setting. Thus, this article presents a two-level ensemble attack detection and attribution framework designed for CPS, and more specifically in an industrial control system (ICS). At the first level, a decision tree combined with a novel ensemble deep representation-learning model is developed for detecting attacks imbalanced ICS environments. At the second level, an ensemble deep neural network is designed to facilitate attack attribution. The proposed model is evaluated using real-world data sets in gas pipeline and water treatment system. Findings demonstrate that the proposed model outperforms other competing approaches with similar computational complexity.

Modeling New Constructions of T-joint Connection of the Pipeline to Increase Efficiency

The oil and gas pipeline system is currently the most common way to transport oil and gas. One of the main hazardous areas of this system is the T-joint connection. The object of my research will be a T-joint connection. Branch nodes and taps are the most dangerous sections of the pipeline system. The tee assembly, which includes the main pipe and pipe, experiences a stress-strain state caused by a number of reasons, which relates it to tasks requiring increased control and attention. Such reasons include the operating conditions of the pipeline system, constant loads, the environment in the pipes and the presence of defective areas. One of the ways to strengthen the T-joint connection is the use of special reinforcing elements, which have their own manufacturing and assembly technology with the pipeline.

Geotechnical Monitoring of Pipeline Systems Operating Under Conditions of Permafrost (Yakutia)

Life safety on the territory of the Republic of Sakha (Yakutia) is directly related to the uninterrupted supply of energy and heat, which is caused by low climatic temperatures. Even in Central Yakutia, the average period of temperatures below 0° C is about 210 days, below −20 ° C - 138 days. The minimum temperature is distributed in the range from −47.8 ° C to −60.3 ° C. Under such natural conditions, the release of any object in gas and heat supply chain leads to disastrous consequences. In the year at gas and heat supply facilities, several dozen emergencies of varying severity are recorded, mainly in winter period. The system of oil and gas pipelines laid on the territory of the Republic of Sakha (Yakutia), mostly located in the permafrost zone, is affected by dangerous geological processes, which significantly affects its reliability and safety. For stable operation of oil and gas complex (OGC) of the Republic, an assessment of pipeline state system, based on geotechnical monitoring, is necessary. The monitoring system provides heterogeneous data, the analysis of which helps to clarify the interaction between pipeline and permafrost in various geological conditions, and allows you to evaluate and predict the condition of objects and environment.

Experimental Design of Acoustic Emission Detection for Micro Leakage in Marine Compressed Gas System

In order to detect the micro leakage of marine compressed gas pipeline system, an experimental platform for detecting the micro leakage of compressed gas is designed by using acoustic emission technology. The results show that the experimental platform can effectively simulate the two typical marine compressed gas pipeline leakage problems: pipe wall damage and valve internal leakage. At the same time, these leakage problems can be effectively detected by using acoustic emission signal acquisition and processing system.

A three-tiered intrusion detection system for industrial control systems

Abstract This article presents three-tiered intrusion detection systems, which uses a supervised approach to detect cyber-attacks in industrial control systems networks. The proposed approach does not only aim to identify malicious packets on the network but also attempts to identify the general and finer grain attack type occurring on the network. This is key in the industrial control systems environment as the ability to identify exact attack types will lead to an increased response rate to the incident and the defence of the infrastructure. More specifically, the proposed system consists of three stages that aim to classify: (i) whether packets are malicious; (ii) the general attack type of malicious packets (e.g. Denial of Service); and (iii) finer-grained cyber-attacks (e.g. bad cyclic redundancy check, attack). The effectiveness of the proposed intrusion detection systems is evaluated on network data collected from a real industrial gas pipeline system. In addition, an insight is provided as to which features are most relevant in detecting such malicious behaviour. The performance of the system results in an F-measure of: (i) 87.4%, (ii) 74.5% and (iii) 41.2%, for each of the layers, respectively. This demonstrates that the proposed architecture can successfully distinguish whether network activity is malicious and detect which general attack was deployed.

Multi-objective transient peak shaving optimization of a gas pipeline system under demand uncertainty

It is the primary responsibility of a gas pipeline company to satisfy the gas demand of customers and ensure the economical operation of its pipelines. This paper presents a stochastic multi-objective transient peak shaving optimization model that considers uncertainty in gas demand while optimizing operational schemes of compressors and peak shaving measures of underground gas storages. The model is a rigorous multi-objective non-linear program (NLP) constrained by governing gas flow equations, operating envelopes of centrifugal compressors, and thermodynamic equations that model natural gas properties. The proposed multi-objective model aims to minimize the operational costs (the sum of the electricity cost of compressor stations and the gas withdrawal cost of underground gas storage) and maximize the line pack at the end of the time horizon subject to multiple legal and physical constraints. The model was tested on a real gas pipeline system, and a set of Pareto optimal solutions are obtained. The optimal operational schemes and peak shaving measures under three typical Pareto optimal solutions are analyzed in detail, and numerical results are presented following stochastic and robust optimization approaches.

Gas Supply Reliability Analysis of a Natural Gas Pipeline System Considering the Effects of Demand Side Management

Abstract At present, China has a developing natural gas market, and ensuring the security of gas supply is an issue of high concern. Gas supply reliability, the natural gas pipeline system's ability to satisfy the market demand, is determined by both supply side and demand side and is usually adopted by the researches to measure the security of gas supply. In the previous study, the demand side is usually simplified by using load duration curve (LDC) to describe the demand, which neglects the effect of demand side management. The simplification leads to the inaccurate and unreasonable assessment of the gas supply reliability, especially in high-demand situation. To overcome this deficiency and achieve a more reasonable result of gas supply reliability, this paper extends the previous study on demand side by proposing a novel method of management on natural gas demand side, and the effects of demand side management on gas supply reliability is analyzed. The management includes natural gas prediction models for different types of users, the user classification rule, and the demand adjustment model based on user classification. First, an autoregressive integrated moving average (ARIMA) model and a support vector machine (SVM) model are applied to predict the natural gas demand for different types of users, such as urban gas distributor (including residential customer, commercial customer, small industrial customer), power plant, large industrial customer, and compressed natural gas (CNG) station. Then, the user classification rule is built based on users' attribute and impact of supplied gas's interruption or reduction. Natural gas users are classified into four levels. (1) demand fully satisfied, (2) demand slightly reduced, (3) demand reduced, and (4) demand interrupted. The user classification rule also provides the demand reduction range of different users. Moreover, the optimization model of demand adjustment is built, and the objective of the model is to maximize the amount of gas supplied to each user based on the classification rule. The constraints of the model are determined by the classification rule, including the demand reduction range of different users. Finally, the improved method of gas supply reliability assessment is developed and is applied to the case study of our previous study derived from a realistic natural gas pipeline system operated by PetroChina to analyze the effects of demand side management on natural gas pipeline system's gas supply reliability.

Evolutionary Deep Belief Network for Cyber-Attack Detection in Industrial Automation and Control System

Industrial automation and control systems (IACS) are tremendously employing supervisory control and data acquisition (SCADA) network. However, their integration into IACS is vulnerable to various cyber-attacks. In this article, we first present population extremal optimization (PEO)-based deep belief network detection method (PEO-DBN) to detect the cyber-attacks of SCADA-based IACS. In PEO-DBN method, PEO algorithm is employed to determine the DBN's parameters, including number of hidden units and the size of mini-batch and learning rate, as there is no clear knowledge to set these parameters. Then, to enhance the performance of single method for cyber-attacks detection, the ensemble learning scheme is introduced for aggregation of the proposed PEO-DBN method, called EnPEO-DBN. The proposed detection methods are evaluated on gas pipeline system dataset and water storage tank system dataset from SCADA network traffic by comparing with some existing methods. Through performance analysis, simulation results show the superiority of PEO-DBN and EnPEO-DBN.

Substantiation of methods of improving safety of pipeline gas transportation

Ensuring the operational efficiency of hazardous production facilities throughout their entire service life becomes a formidable challenge associated with coordinating thorough monitoring of such facilities, assessing their exposure, mitigation and sustainability, and taking measures to minimize and prevent negative outcomes that can lead to negative consequences, including human fatalities, injuries and economic losses. At the same time, the optimal choice of the ratio between levels of risk and costs of identification, regulation and increase in the resource will ensure both a reduction to a minimum of the risk of failures in gas pipeline systems and increase the efficiency of resource use to maximize technogenic safety. The paper proposes a methodology for the calculation of risk indicators and the probability of emergencies on gas networks and gas distribution facilities during their operation in normal and emergency situations.

Analysis of COVID-19 Impact on Natural Gas Supply Reliability

In this study, we have analyzed the impact of COVID-19 on natural gas supply reliability. Natural gas supply reliability is defined as the ability to satisfy the market demand and is determined by both supply-side and demand-side policy. To evaluate the gas supply reliability of the natural gas pipeline system, we have applied the method of gas supply capacity calculation based on the results of the previous gas supply reliability studies. The method combines the unsteady flow hydraulic analysis, simulation of the state transition process, and the forecasting analysis of the demand and consumption. The analysis presents a case study based on the gas pipeline system in China. The analysis results indicate that the COVID-19 consequences will cause a decrease in gas supply reliability.

Design of Constructive Controller of Nonlinear System Based on Polynomial Function Growth Condition and Its Application in Deep Subsea Energy Mining and Production Control System

This paper mainly studies the output feedback control problem of the stochastic nonlinear system based on loose growth conditions and applies the research results to the valve control system of underwater oil and gas pipelines, which can improve the speed and stability of the equipment system. First, the concept of randomness is introduced to study the actual tracking control problem of output feedback of stochastic nonlinear systems, remove the original harsher growth conditions, make it meet the more general polynomial function growth conditions, and propose a combination of static and dynamic output feedback practices. The design of the tracking controller makes all the states of the system meet boundedness and ensures that the tracking error of the system converges to a small neighborhood of zero. Second, the system is extended to the parameter‐uncertain system, and the output feedback tracking controller with complete dynamic gain is constructed by proving the boundedness of the system state and gain. Further, the time‐delay factor is introduced, and the nonlinear term of the system satisfies the more relaxed power growth condition, combined with the inverse method to cleverly construct a set of Lyapunov functions and obtain the output controller to ensure that the system is asymptotically probabilistic in the global scope. Stability. Finally, through the ocean library in the Simulation X simulation software, the controller design results are imported into the underwater electro‐hydraulic actuator model to verify the effectiveness of the controller design.

Elimination of Undetectable Attacks on Natural Gas Networks

Natural gas pipeline system operations rely heavily on Supervisory Control and Data Acquisition (SCADA) systems. While the SCADA systems introduce many advantages, they also introduce more vulnerabilities by providing opportunities for malicious cyber-attackers. If the cyber-attacks properly modify pressures, flows, and the topology the operator believes is present simultaneously, the cyber-attacks can be undetectable. While this topic has received attention for electrical grids, other cyber-physical systems have seen much less study on this topic. Natural gas networks are employed extensively to power generators in the electrical grid, so attacks on natural gas networks are very important. We have not seen any research on this topic for natural gas networks yet. The particular nonlinear equations which model natural gas networks make the analysis much more difficult. In this paper, we study undetectable attacks on natural gas networks in a signal processing perspective by describing the steady-state mathematical model and sensor measurements. We propose a countermeasure to eliminate undetectable attacks by protecting sensors in specific locations. We present an example that describes how an operator can be misled if the proposed countermeasure is not applied. In such cases, the operator could apply inappropriate control which could damage the system or cause a loss of critical gas supply to customers.

Analysis and Research on Pipeline Vibration of a Natural Gas Compressor Station and Vibration Reduction Measures

The abnormal vibration of natural gas station pipelines seriously threatens the safety of pipeline transportation, and improper handling will cause huge economic losses. For the abnormal vibration of the pipeline, reasonable treatment must be carried out. The Yongchang gas station belongs to the west–east gas pipeline system in China. Since its production, abnormal vibration has often occurred in the west-third outbound pipeline of the Yongchang gas station, and the vibration changes according to the different gas transport volumes. In this paper, the outbound pipeline of the Yongchang pressure station is taken as the research object, and the vibration analysis of the station yard pipeline is carried out. The numerical model of the station yard pipeline is established, and the correctness of the model is verified by the field vibration test. The fluid–solid coupling method is used to analyze pipeline vibration under different working conditions. Then, three kinds of vibration reduction schemes are proposed and verified by simulation. The main conclusions are as follows: (1) The fluid pressure fluctuation in the pipeline is the root cause of abnormal vibration in the station. (2) When the gas transmission volume is large, the vibration of the pipeline system will become more severe. (3) The scheme of increasing pipe diameter and adding appropriate constraints has the best vibration reduction effect.

A model-based health indicator for leak detection in gas pipeline systems

Leakage in gas pipelines is becoming a significant issue and has attracted much attention in recent years. This paper is concerned with the development of a robust health indicator for identifying the leakage in gas pipeline systems. A spectral exponent indicator is proposed based on a theoretical leak noise spectrum model. Measurements of the leak acoustic signals are also presented from a pipe rig with air under pressure. Then, a feature selection technique is employed to select properly desired features. Three data-driven approaches, artificial neural networks (ANNs), support vector machine (SVM), and random forest (RF) are trained with the most discriminative features. The proposed methodology showed to achieve 99.4%, 99.6% and 99.4% accuracies for ANN, SVM and RF respectively. Furthermore, the proposed indicator showed to be robust under different conditions illustrating its ability for applications in the field.

Design and analysis of the cathodic protection system of oil and gas pipelines, using distributed equivalent circuit model

Cathodic protection (CP) method is widely used in the oil and gas industry in order to prevent (or reduce) rust and corrosion of structures and metal pipelines or their associated cost. To guarantee a more effective CP system, an applicable design for the under protected structures is required. The conventional models recommended by the designers are based on the equivalent circuit of the overall CP system, which are lumped model and may be useful for the compact systems like integrated industrial plants, where oil and gas pipelines are installed in kilometers. Since such a lumped model leads to inaccurate results, this study aims at proposing a new distributed model to design a cathodic protection system for oil and gas transmission pipelines, which is extendable and can be useable in other structures. The main difference between the proposed model and the conventional approach is the use of actual measured soil resistance throughout the structure instead of using a fixed mean value. The effectiveness of the proposed model has been demonstrated by analytical analysis and computer-based simulations. The proposed method shows a significant superiority over the conventional lumped models when variation of the soil resistance through the structure is high. Hence, the application of the devised method in design of a CP system of the pipelines improves the quality of the protection. The distributed equivalent circuit model with its distributed parameters is utilized to design and analyze the performance of a real case i.e., the CP protection system of a 20-km transmission pipeline with soil-measured data. To calculate the performance of the designed CP system, the results are compared with those of the conventional model.

Increasing efficiency of use of dryers at the gas-processing enterprises

Gas is the most environmentally friendly type of fuel and its role only increases over time. According to experts ’ forecasts by 2050 its role in the world’s energy balance will be 28-30 %. The main technological process used in gas production and transportation is the drying process. Annually, about 20-25 billion cubic meters of associated petroleum gases are processed at gas processing plants. In Russia, the production of liquefied natural gas is becoming more popular. The quality of associated petroleum gas intended for processing is subject to high demands, such as purification of methanol, mercury and gas dehydration. Mostly dehydration is carried out using zeolites. The paper presents the result. On the territory of Russia, a significant proportion of gas fields contain hydrogen sulfide and organosulfuric compounds, without purification from which gas can not be sold to the main gas pipeline system and consumers. The organization of gas production at the Orenburg and then Astrakhan fields required the use of technologies for gas purification from hydrogen sulfide, production of gas sulfur and post-treatment of tail gases of sulfur production, as well as gas purification from organosulfur compounds.

Fracture assessment of pipeline girth weld at low temperature

The results of long-distance oil and gas pipeline failure analysis are important to the industry in order to maintain the reliability and safety of them. Seam welding in these pipes is done with good accuracy at place of work, while girth welding is carried out in the installation site and usually causes the main failure problem. Therefore, the most vulnerable and crucial part of these pipes is the girth welding. Investigating the fracture behavior of girth weld in high-pressure gas pipeline systems at low temperatures is important because these products are hazardous and may lead to explosion, leading to economic losses and environmental pollution. In the present study, the fracture behavior of girth-welded API 5L X65 natural gas transportation pipes was experimentally investigated at low temperatures. The fracture parameters were obtained using Arcan fixture in which all of the in-plane modes including pure tensile mode to pure shear mode can be created by altering the loading angle from 0° to 90°. Finite element analysis was also conducted by ABAQUS finite element software in order to determine geometrical coefficients which are required in calculating the fracture toughness. Results revealed that by decreasing the temperature and increasing the mode II loading contribution, the fracture toughness values were also decreased.

System-level prognosis and health monitoring modeling framework and software implementation for gas pipeline system integrity management

Over the past few decades, recurrent pipeline failures have caused a major impact on human lives and property damage. Studies have shown the lack of a comprehensive, integrated, and accessible set of risk-informed integrity management models and tools for pipeline operators are the main reason behind those damages. To address this gap, this paper presents a system-level Prognosis and Health Monitoring (PHM) modeling framework for gas pipeline system integrity management to prevent or reduce the likelihood of failures. PHM modeling is a comprehensive approach that takes into consideration all possible failure modes of the pipeline under study. It leverages the advancement of sensor technology to stream field data in real-time to perform a dynamic system-level failure analysis based on Hybrid Causal Logic (HCL) and Dynamic Bayesian Networks (DBNs) predictive models to provide cost-effective and optimal mitigation actions such as sensor placement and maintenance schedule optimizations. The developed models are implemented into a software platform where the pipeline operators can observe the real-time and projected health state of the pipeline and the set of suggested actions to enhance the structural integrity of the pipeline system. The platform includes three main modules: Real-Time Monitoring, System-Level Reliability, and Optimal Mitigation Actions. From a safety perspective, the proposed comprehensive and dynamic pipeline health assessment framework either prevents the pipeline failures or reduces their likelihood by supporting pipeline operators in optimal decision-making and planning activities. To verify the performance of the proposed framework and its software implementation, it is applied to a case study of a corroded gas transmission pipeline and the results are discussed.