Oil and Gas Pipeline Network for Industrial Applications

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Sciences applsci	2.5	5.3	2011	18.4 Days	CHF 2400	Submit
Energies energies	3.0	6.2	2008	16.8 Days	CHF 2600	Submit
Fluids fluids	1.8	3.4	2016	21.1 Days	CHF 1800	Submit
Modelling modelling	1.3	2.7	2020	18.9 Days	CHF 1000	Submit
Processes processes	2.8	5.1	2013	14.9 Days	CHF 2400	Submit

17 pages, 5399 KiB

Open AccessArticle

Experimental Research of the Possibility of Applying the Hartmann–Sprenger Effect to Regulate the Pressure of Natural Gas in Non-Stationary Conditions

by Artem Belousov, Vladimir Lushpeev, Anton Sokolov, Radel Sultanbekov, Yan Tyan, Egor Ovchinnikov, Aleksei Shvets, Vitaliy Bushuev and Shamil Islamov

Processes 2025, 13(4), 1189; https://doi.org/10.3390/pr13041189 - 14 Apr 2025

Viewed by 432

Abstract

This research focuses on the development of a quasi-isothermal pressure regulator based on the principle of flow mixing after energy separation. Currently, no established methods exist for designing pressure reduction devices that utilize energy separation effects, and this study aims to fill this [...] Read more.

This research focuses on the development of a quasi-isothermal pressure regulator based on the principle of flow mixing after energy separation. Currently, no established methods exist for designing pressure reduction devices that utilize energy separation effects, and this study aims to fill this gap. The paper presents experimental results on the performance of a pressure reduction device operating based on the Hartmann–Sprenger effect. This study investigated the hypothesis that by selecting the size of resonators, relative distances, and their mutual location, it would be possible to realize pressure regulation, simultaneously providing both the maintenance of a significant effect and the full provision of the functions of pressure regulators operating in non-stationary conditions. The experiments involved three resonators (45.5 mm, 70.5 mm, and 97.5 mm) in regurgitant mode. The findings revealed that the smallest resonator demonstrated the highest rate of temperature increase, with an average value of 2.36 K/s. The medium resonator exhibited the highest reliability under non-stationary conditions, while the largest resonator provided the highest temperature, with a maximum excess of 102 K over the temperature in front of the nozzle. The primary goal of this study was to develop technology suitable for installation at a pressure reduction station, considering mass and dimensional constraints. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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22 pages, 6378 KiB

Open AccessArticle

Explainable Ensemble Learning Model for Residual Strength Forecasting of Defective Pipelines

by Hongbo Liu and Xiangzhao Meng

Appl. Sci. 2025, 15(7), 4031; https://doi.org/10.3390/app15074031 - 6 Apr 2025

Viewed by 376

Abstract

The accurate prediction of the residual strength of defective pipelines is a critical prerequisite for ensuring the safe operation of oil and gas pipelines, and it holds significant implications for the pipeline’s remaining service life and preventive maintenance. Traditional machine learning algorithms often [...] Read more.

The accurate prediction of the residual strength of defective pipelines is a critical prerequisite for ensuring the safe operation of oil and gas pipelines, and it holds significant implications for the pipeline’s remaining service life and preventive maintenance. Traditional machine learning algorithms often fail to comprehensively account for the correlative factors influencing the residual strength of defective pipelines, exhibit limited capability in extracting nonlinear features from data, and suffer from insufficient predictive accuracy. Furthermore, the predictive models typically lack interpretability. To address these issues, this study proposes a hybrid prediction model for the residual strength of defective pipelines based on Bayesian optimization (BO) and eXtreme Gradient Boosting (XGBoost). This approach resolves the issues of excessive iterations and high computational costs associated with conventional hyperparameter optimization methods, significantly enhancing the model’s predictive performance. The model’s prediction performance is evaluated using mainstream metrics such as the Mean Absolute Percentage Error (MAPE), Coefficient of Determination (R²), Root Mean Square Error (RMSE), robustness analysis, overfitting analysis, and grey relational analysis. To enhance the interpretability of the model’s predictions, reveal the significance of features, and confirm prior domain knowledge, Shapley additive explanations (SHAP) are employed to conduct the relevant research. The results indicate that, compared with Random Forest, LightGBM, Support Vector Machine, gradient boosting regression tree, and Multi-Layer Perceptron, the BO-XGBoost model exhibits the best prediction performance, with MAPE, R², and RMSE values of 5.5%, 0.971, and 1.263, respectively. Meanwhile, the proposed model demonstrates the highest robustness, the least tendency for overfitting, and the most significant grey relation degree value. SHAP analysis reveals that the factors influencing the residual strength of defective pipelines, ranked in descending order of importance, are defect depth (d), wall thickness (t), yield strength (σ_y), external diameter (D), defect length (L), tensile strength (σ_u), and defect width (w). The development of this model contributes to improving the integrity management of oil and gas pipelines and provides decision support for the intelligent management of defective pipelines in oil and gas fields. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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15 pages, 6196 KiB

Open AccessArticle

Analysis and Control of Abnormal Wear of Reciprocating Compressors in Natural Gas Underground Storage Caverns

by Sijia Zheng, Zhixiang Dai, Fei Wang, Feng Wang, Yongbo Wang, Qin Bie, Wei Jiang, Jingdong Chen, Zicheng Peng and Jie Sun

Processes 2025, 13(4), 996; https://doi.org/10.3390/pr13040996 - 26 Mar 2025

Viewed by 267

Abstract

Throughout China’s 14th five-year plan, the national natural gas pipeline network has been interconnected, and the gas quality became increasingly complex. A certain amount of dust particles widely spread in the natural gas pipeline and lead to abnormal wear of the reciprocating compressor’s [...] Read more.

Throughout China’s 14th five-year plan, the national natural gas pipeline network has been interconnected, and the gas quality became increasingly complex. A certain amount of dust particles widely spread in the natural gas pipeline and lead to abnormal wear of the reciprocating compressor’s compression cylinder within the underground storage cavern. The wear characteristics of the compression cylinder are effectively demonstrated based on the tangential impact energy model, and combined with field measurement and the moving-grid method of computational fluid dynamics. The results reveal that the lubricating oil forms “grinding paste” when mixed with dust particles. With an increase in the dust mass concentration from 0.01% to 3.00%, the viscosity of the “grinding paste” increases from 450,800 mPa·s to 1,274,000 mPa·s, and the density increases from 890 kg/m³ to 980 kg/m³. The abnormal wear frequently occurs at the 12 o’clock and 6 o’clock directions of the compression cylinder. When the piston is in the midpoint of the stroke, the wall shear rate and the wear rate are the highest. When the piston is at both endpoints of the stroke, the wall shear rate and the wear rate are the lowest. For every 1000 h of operation without repairing the cylinder, the dust concentration should be controlled below 0.60%. For every 5000 h and 10,000 h of operation without replacing the cylinder, the dust concentration should be controlled below 1.3% and 0.4%. When the dust mass concentration is 0.01%, the wear rate decreases with decreasing lubricating oil viscosity. When the dust mass concentration is 0.51% and 1.0%, and the lubricating oil viscosities are 259,700 mPa·s, 220,500 mPa·s, and 196,980 mPa·s, the wear rate increases dramatically with decreasing lubricating oil viscosity. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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24 pages, 8527 KiB

Open AccessArticle

Real-Time Elbow and T-Junction Detection and Estimation Framework for In-Line Inspection in Natural Gas Pipelines Using 3D Point Cloud

by Hoa-Hung Nguyen, Jae-Hyun Park, Jae-Jun Kim, Kwanghyun Yoo, Dong-Kyu Kim and Han-You Jeong

Appl. Sci. 2025, 15(6), 3397; https://doi.org/10.3390/app15063397 - 20 Mar 2025

Viewed by 252

Abstract

In-line inspection (ILI) is essential for maintaining the integrity of natural gas pipelines. In ILI, pipeline inspection gauges (PIGs) autonomously navigate through pipelines under real-time and resource-constrained conditions to measure pipeline irregularities. Elbow and T-junction detection and estimation (ETDE) play a critical role [...] Read more.

In-line inspection (ILI) is essential for maintaining the integrity of natural gas pipelines. In ILI, pipeline inspection gauges (PIGs) autonomously navigate through pipelines under real-time and resource-constrained conditions to measure pipeline irregularities. Elbow and T-junction detection and estimation (ETDE) play a critical role in enabling PIG navigation to avoid speed excursions which prevent effective data collection or even damage the PIG and pipelines. Existing approaches are often computationally intensive, incomplete, or late estimations, making them unsuitable for real-time operation in such environments. This paper proposes a real-time elbow and T-junction detection and estimation (RT-ETDE) framework that efficiently detects elbows and T-junctions and estimates their critical parameters for PIG navigation using 3D point clouds. Our framework relies on intelligent point cloud partition and feature extraction together with simple geometric solutions which greatly reduce computational complexity. Furthermore, several real-time adaptation techniques are introduced to ensure real-time operation. Experimental results on a prototype pipeline demonstrate that the RT-ETDE framework consistently detects elbows and T-junctions while achieving a 10 Hz frame rate on a real PIG processing unit, validating its suitability for next-generation pipeline inspection systems. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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21 pages, 15426 KiB

Open AccessArticle

Numerical Simulation on Aerodynamic Noise of (K)TS Control Valves in Natural Gas Transmission and Distribution Stations in Southwest China

by Xiaobo Feng, Lu Yu, Hui Cao, Ling Zhang, Yizhi Pei, Jingchen Wu, Wenhao Yang and Junmin Gao

Energies 2025, 18(4), 968; https://doi.org/10.3390/en18040968 - 17 Feb 2025

Viewed by 429

Abstract

Fluid dynamic noise produced by eddy disturbances and friction along pipe walls poses a significant challenge in natural gas transmission and distribution stations. (K)TS control valves are widely used in natural gas transmission and distribution stations across Southwest China and are among the [...] Read more.

Fluid dynamic noise produced by eddy disturbances and friction along pipe walls poses a significant challenge in natural gas transmission and distribution stations. (K)TS control valves are widely used in natural gas transmission and distribution stations across Southwest China and are among the primary sources of noise in these facilities. In this study, a 3D geometric model of the (K)TS valve was developed, and the gas flow characteristics were simulated to analyze the gas flow field and sound field within the valve under varying pipeline flow velocities, outlet pressures, and valve openings. The results demonstrate that accurate calculations of the 3D valve model can be achieved with a grid cell size of 3.6 mm and a boundary layer set to 3. The noise-generating regions of the valve are concentrated around the throttle port, valve chamber, and valve inlet. The primary factors contributing to the aerodynamic noise include high gas flow velocity gradients, intense turbulence, rapid turbulent energy dissipation, and vortex formation and shedding within the valve. An increase in inlet flow velocity intensifies turbulence and energy dissipation inside the valve, while valve opening primarily influences the size of vortex rings in the valve chamber and throttle outlet. In contrast, outlet pressure exerts a relatively weak effect on the flow field characteristics within the valve. Under varying operating conditions, the noise directivity distribution remains consistent, exhibiting symmetrical patterns along the central axis of the flow channel and forming six-leaf or four-leaf flower shapes. As the distance from the monitoring point to the valve increases, noise propagation becomes more concentrated in the vertical direction of the valve. These findings provide a theoretical basis for understanding the mechanisms of aerodynamic noise generation within (K)TS control valves during natural gas transmission, and can also offer guidance for designing noise reduction solutions for valves. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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18 pages, 9478 KiB

Open AccessArticle

Robust and Unbiased Estimation of Robot Pose and Pipe Diameter for Natural Gas Pipeline Inspection Using 3D Time-of-Flight (ToF) Sensors

by Hoa-Hung Nguyen, Jae-Hyun Park, Jae-Jun Kim, Kwanghyun Yoo, Dong-Kyu Kim and Han-You Jeong

Appl. Sci. 2025, 15(4), 2105; https://doi.org/10.3390/app15042105 - 17 Feb 2025

Cited by 1 | Viewed by 565

Abstract

The estimation of robot pose and pipe diameter is an essential task for reliable in-line inspection (ILI) operations and the accurate assessment of pipeline attributes. This paper addresses the problem of robot pose and pipe diameter estimation for natural gas pipelines based on [...] Read more.

The estimation of robot pose and pipe diameter is an essential task for reliable in-line inspection (ILI) operations and the accurate assessment of pipeline attributes. This paper addresses the problem of robot pose and pipe diameter estimation for natural gas pipelines based on 3D time-of-flight (ToF) sensors. To tackle this challenge, we model the problem as a non-linear least-squares optimization that fits 3D ToF sensor measurements in its local coordinates to an elliptic cylindrical model of the pipe inner surface. We identify and prove that the canonical ellipse-based estimation method (C-EPD), which uses a canonical residual function, suffers from bias in diameter estimation due to its asymmetry to depth errors. To overcome this limitation, we propose the robust and unbiased estimation of pose and diameter (RU-EPD) approach, which employs a novel error-based residual function. The proposed function is symmetric to depth errors, effectively reducing estimation bias. Extensive numerical simulations and prototype pipeline experiments demonstrate that RU-EPD outperforms C-EPD, achieving an at least six times lower estimation bias and a 2.5 times smaller estimation error range in pipe diameter and about a 2 times smaller estimation error range in pose estimation. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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21 pages, 2911 KiB

Open AccessArticle

Fast and Accurate Prediction of Corrosion Rate of Natural Gas Pipeline Using a Hybrid Machine Learning Approach

by Hongbo Liu, Xinlei Cai and Xiangzhao Meng

Appl. Sci. 2025, 15(4), 2023; https://doi.org/10.3390/app15042023 - 14 Feb 2025

Viewed by 876

Abstract

The precise prediction of natural gas pipeline corrosion rates holds great significance for pipeline maintenance and corrosion control. Existing prediction methods, especially traditional models, often fail to adequately consider noise interference and the strong nonlinear characteristics of corrosion data, resulting in insufficient prediction [...] Read more.

The precise prediction of natural gas pipeline corrosion rates holds great significance for pipeline maintenance and corrosion control. Existing prediction methods, especially traditional models, often fail to adequately consider noise interference and the strong nonlinear characteristics of corrosion data, resulting in insufficient prediction accuracy. To enhance predictive performance, a hybrid prediction model based on machine learning is been proposed. This model consists of three main components: data processing, model optimization, and prediction performance evaluation. In this model, data decomposition algorithms and principal component analysis are employed to eliminate redundant noise from the original data and capture their primary features. A stratified sampling method is utilized to divide the data into a training set and test set, avoiding biases caused by random sampling. A modified particle swarm optimization algorithm is applied to optimize the parameters of a back propagation neural network. The model’s predictive performance is assessed using various indicators, including R², MAPE, RMSE, MAE, U1, U2, RE, forecasting effectiveness, comparing the results with existing literature, Grey Relational Analysis, and interpretability research. The proposed prediction model is compared with eight advanced prediction models using data from a natural gas pipeline in western China. This study reveals that the developed model outperforms the others, demonstrating excellent prediction accuracy and effectively guiding the formulation of corrosion control measures. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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20 pages, 4825 KiB

Open AccessArticle

Risk Diagnosis Analysis of Ethane Storage Tank Leakage Based on Fault Tree and Fuzzy Bayesian Network

by Min Pang, Zheyuan Zhang, Zhaoming Zhou and Qing Li

Appl. Sci. 2025, 15(4), 1754; https://doi.org/10.3390/app15041754 - 9 Feb 2025

Cited by 1 | Viewed by 646

Abstract

This study proposes a risk assessment method for ethane tank leakage based on Fault Tree Analysis (FTA) and the Fuzzy Bayesian Network (FBN). It aims to diagnose and probabilistically evaluate system risks in scenarios where leakage data are imprecise and insufficient. Initially, a [...] Read more.

This study proposes a risk assessment method for ethane tank leakage based on Fault Tree Analysis (FTA) and the Fuzzy Bayesian Network (FBN). It aims to diagnose and probabilistically evaluate system risks in scenarios where leakage data are imprecise and insufficient. Initially, a fault tree for ethane tank leakage risk is constructed using the connectivity of logical gates. Then, through the analysis of minimal cut sets, the fundamental causes of ethane tank leakage risk are identified, including cracking, instability, and corrosion perforation. Subsequently, the fault tree is mapped into a Bayesian network, which is then integrated to transform it into an FTA–FBN risk diagnostic probability model. Prior probabilities of parent nodes and conditional probability tables are obtained through fuzzy mathematics principles and expert guidance. These are combined with Bayesian inference to derive posterior probabilities, thereby determining the contribution of each basic event to the ethane tank leakage risk. By leveraging the advantages of the fuzzy Bayesian network in handling uncertain problems, the model and analysis effectively address the ambiguities encountered in real-world scenarios. In order to better cope with the uncertainty of leakage, the weakest t-norm algorithm and the similarity aggregation method are introduced for the parameter learning of the fuzzy Bayesian network to achieve an accurate solution of the model. Finally, this integrated model is used in a real case to study the causes of ethane storage tank leakage. The research results are of great scientific significance for revealing the evolution mechanism of ethane storage tank leakage accidents and ensuring system safety throughout the life cycle. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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22 pages, 2326 KiB

Open AccessReview

Basic Theory and Applications of Oil and Gas Pipeline Non-Destructive Testing Methods

by Yuqin Wang, Fei Song, Qingshan Feng, Weibiao Qiao, Shaohua Dong, Yangyang Jiang and Qianli Ma

Energies 2024, 17(24), 6366; https://doi.org/10.3390/en17246366 - 18 Dec 2024

Cited by 1 | Viewed by 1359

Abstract

In recent years, with the increasing construction mileage of oil and gas pipelines (OGPs), the aging problem of OGPs has become increasingly prominent, so, ensuring the safety of OGPs is of great significance. In addition, the safety of OGP transportation is also an [...] Read more.

In recent years, with the increasing construction mileage of oil and gas pipelines (OGPs), the aging problem of OGPs has become increasingly prominent, so, ensuring the safety of OGPs is of great significance. In addition, the safety of OGP transportation is also an important component of pipeline integrity. Therefore, to ensure the safety of OGP transportation, regular OGP inspections should be carried out. During this process, defects in the OGP and measured wall thickness information should be recorded to provide a basis for subsequent pipeline repair or replacement. This study analyzes the literature on pipeline testing and reviews approximately eighty articles. Based on these articles, we summarize the types of common OGP defects and review the basic principles of various non-destructive testing methods for pipelines, including electromagnetic acoustic transducer inspection, magnetic flux leakage testing, ultrasonic testing, and eddy current testing. We also provide a detailed introduction to the applications and innovative testing methods based on the above OGP inspection methods. Finally, an analysis and outlook on the future research focus of OGP inspection technology are presented. This research suggests that different detection methods should be used for different types of defects, such as using the magnetic leakage method for the internal detection of natural gas pipelines. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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16 pages, 6596 KiB

Open AccessArticle

Study on Explosion Venting Characteristics of L-Type Venting Duct

by Fan Wu, Xing Zhou, Yongmei Hao and Sunqi Zhuang

Processes 2024, 12(12), 2726; https://doi.org/10.3390/pr12122726 - 2 Dec 2024

Viewed by 741

Abstract

The failure state of the natural gas pipelines in underground space may cause explosions, and an explosion flow field is affected by the structure of the venting duct. Based on FLACS software v9.0, the influence of the explosion vent and venting duct on [...] Read more.

The failure state of the natural gas pipelines in underground space may cause explosions, and an explosion flow field is affected by the structure of the venting duct. Based on FLACS software v9.0, the influence of the explosion vent and venting duct on temperature and pressure fields is studied. The results show that when the area of the explosion vent increases from 0 to 100 cm², the peak overpressure decreases by half, and the overpressure drops to zero within 0.3 s. For different L-type venting ducts, when the structural coefficient is less than 5, the peak overpressures and pressure variations are similar. When the structural coefficient is equal to 5, the peak overpressure significantly decreases, and the time to reach the peak value is extended by 50%. From the perspective of achieving a safe and efficient venting effect, the optimal structural coefficient is 5 for the L-type venting duct. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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13 pages, 5482 KiB

Open AccessArticle

Simulation Analysis of the Annular Liquid Disturbance Induced by Gas Leakage from String Seals During Annular Pressure Relief

by Qiang Du, Ruikang Ke, Xiangwei Bai, Cheng Du, Zhaoqian Luo, Yao Huang, Lang Du, Senqi Pei and Dezhi Zeng

Modelling 2024, 5(4), 1674-1686; https://doi.org/10.3390/modelling5040087 - 8 Nov 2024

Viewed by 752

Abstract

Due to the failure of string seals, gas can leak and result in the abnormal annulus pressure in gas wells, so it is necessary to relieve the pressure in gas wells. In the process of pressure relief, the leaked gas enters the annulus, [...] Read more.

Due to the failure of string seals, gas can leak and result in the abnormal annulus pressure in gas wells, so it is necessary to relieve the pressure in gas wells. In the process of pressure relief, the leaked gas enters the annulus, causes a the great disturbance to the annulus flow field, and thus reduces the protection performance of the annular protection fluid in the string. In order to investigate the influence of gas leakage on the annular flow field, a VOF finite element model of the gas-liquid two-phase flow disturbed by gas leakage in a casing was established to simulate the transient flow field in the annular flow disturbed by gas leakage, and the influences of leakage pressure differences, leakage direction, and leakage time on annular flow field disturbance and wall shear force were analyzed. The analysis results showed that the larger leakage pressure difference corresponded to the faster diffusion rate of the leaked gas in the annulus, the faster the flushing rate of the leaked gas against the casing wall, and a larger shear force on the tubing wall was detrimental to the formation of the corrosion inhibitor film on the tubing wall and casing wall. Under the same conditions, the shear action on the outer wall of tubing in the leakage direction of 90° was stronger than that in the leakage directions of 135° and 45° and the diffusion range was also larger. With the increase in leakage time, leaked gas further moved upward in the annulus and the shear effect on the outer wall of tubing was gradually strengthened. The leaked acid gas flushed the outer wall of casing, thus increasing the peeling-off risk of the corrosion inhibitor film. The study results show that the disturbance law of gas leakage to annular protection fluid is clear, and it was suggested to reduce unnecessary pressure relief time in the annulus to ensure the safety and integrity of gas wells. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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21 pages, 7042 KiB

Open AccessArticle

Development of Machine Learning-Based Production Forecasting for Offshore Gas Fields Using a Dynamic Material Balance Equation

by Junhyeok Hyoung, Youngsoo Lee and Sunlee Han

Energies 2024, 17(21), 5268; https://doi.org/10.3390/en17215268 - 23 Oct 2024

Cited by 1 | Viewed by 1309

Abstract

Offshore oil and gas fields pose significant challenges due to their lower accessibility compared to onshore fields. To enhance operational efficiency in these deep-sea environments, it is essential to design optimal fluid production conditions that ensure equipment durability and flow safety. This study [...] Read more.

Offshore oil and gas fields pose significant challenges due to their lower accessibility compared to onshore fields. To enhance operational efficiency in these deep-sea environments, it is essential to design optimal fluid production conditions that ensure equipment durability and flow safety. This study aims to develop a smart operational solution that integrates data from three offshore gas fields with a dynamic material balance equation (DMBE) method. By combining the material balance equation and inflow performance relation (IPR), we establish a reservoir flow analysis model linked to an AI-trained production pipe and subsea pipeline flow analysis model. We simulate time-dependent changes in reservoir production capacity using DMBE and IPR. Additionally, we utilize SLB’s PIPESIM software to create a vertical flow performance (VFP) table under various conditions. Machine learning techniques train this VFP table to analyze pipeline flow characteristics and parameter correlations, ultimately developing a model to predict bottomhole pressure (BHP) for specific production conditions. Our research employs three methods to select the deep learning model, ultimately opting for a multilayer perceptron (MLP) combined with regression. The trained model’s predictions show an average error rate of within 1.5% when compared with existing commercial simulators, demonstrating high accuracy. This research is expected to enable efficient production management and risk forecasting for each well, thus increasing revenue, minimizing operational costs, and contributing to stable plant operations and predictive maintenance of equipment. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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21 pages, 8403 KiB

Open AccessArticle

Research on the Dynamic Leaking and Diffusion Law of Hydrogen-Blended Natural Gas under the Soil–Atmosphere Coupled Model

by Shuai Ren, Jingyi Huang, Jiuqing Ban, Jiyong Long, Xin Wang and Gang Liu

Energies 2024, 17(20), 5035; https://doi.org/10.3390/en17205035 - 10 Oct 2024

Cited by 1 | Viewed by 989

Abstract

With the breakthrough in mixing hydrogen into natural gas pipelines for urban use, the widespread application of hydrogen-blended natural gas (HBNG) in energy delivery is imminent. However, this development also introduces significant safety concerns due to notable disparities in the physical and chemical [...] Read more.

With the breakthrough in mixing hydrogen into natural gas pipelines for urban use, the widespread application of hydrogen-blended natural gas (HBNG) in energy delivery is imminent. However, this development also introduces significant safety concerns due to notable disparities in the physical and chemical properties between methane and hydrogen, heightening the risks associated with gas leaks. Current models that simulate the diffusion of leaked HBNG from buried pipelines into the atmosphere often employ fixed average leakage rates, which do not accurately represent the dynamic nature of gas leakage and diffusion. This study uses computational fluid dynamics (CFD) 2024R1 software to build a three-dimensional simulation model under a soil–atmosphere coupling model for HBNG leakage and diffusion. The findings reveal that, in the soil–atmosphere coupling model, the gas diffusion range under a fixed leakage rate is smaller than that under a dynamic leakage rate. Under the same influencing factors in calm wind conditions, the gas primarily diffuses in the vertical direction, whereas under the same influencing factors in windy conditions, the gas mainly diffuses in the horizontal direction. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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26 pages, 10499 KiB

Open AccessArticle

Novel Adaptive Hidden Markov Model Utilizing Expectation–Maximization Algorithm for Advanced Pipeline Leak Detection

by Omid Zadehbagheri, Mohammad Reza Salehizadeh, Seyed Vahid Naghavi, Mazda Moattari and Behzad Moshiri

Modelling 2024, 5(4), 1339-1364; https://doi.org/10.3390/modelling5040069 - 24 Sep 2024

Viewed by 1013

Abstract

In the oil industry, the leakage of pipelines containing hydrocarbon fluids causes significant environmental and economic damage. Recently, there has been a growing trend in employing data mining techniques for detecting leaks. Among these methods is the Hidden Markov Model, which, despite good [...] Read more.

In the oil industry, the leakage of pipelines containing hydrocarbon fluids causes significant environmental and economic damage. Recently, there has been a growing trend in employing data mining techniques for detecting leaks. Among these methods is the Hidden Markov Model, which, despite good results with stationary data, becomes inefficient when a leak causes a drop in the pressure or flow, reducing its accuracy. This paper presents an adaptive Hidden Markov method. Previous methods had low accuracy due to insufficient information for accurate leak detection. They often classified the size and location of leaks broadly. In contrast, the proposed model extracts hidden features to accurately identify the location and size of leaks, even in noisy conditions. Simulating a leak in a section of an oil pipeline in the Iranian Oil Export Corridor demonstrates the proposed method’s superiority over common methods like K-NN, SVM, Naive Bayes, and logistic regression. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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17 pages, 10336 KiB

Open AccessArticle

Numerical Analysis of Leakage and Diffusion Characteristics of In-Situ Coal Gas with Complex Components

by Enbin Liu, Lianle Zhou, Ping Tang, Bo Kou, Xi Li and Xudong Lu

Energies 2024, 17(18), 4694; https://doi.org/10.3390/en17184694 - 20 Sep 2024

Cited by 1 | Viewed by 928

Abstract

To alleviate the shortage of natural gas supply, the in-situ conversion of coal to natural gas is more beneficial for advancing the clean and efficient use of energy. Since in-situ coal gas contains complex components, such as H₂, CH₄, [...] Read more.

To alleviate the shortage of natural gas supply, the in-situ conversion of coal to natural gas is more beneficial for advancing the clean and efficient use of energy. Since in-situ coal gas contains complex components, such as H₂, CH₄, and CO, their leakage poses a serious risk to human life and property. Currently, the area of consequence of the harm caused by a leak in a gathering pipeline transporting in-situ coal gas has not been clarified. Therefore, this paper adopted the method of numerical simulation to pre-study the concentration distribution of each component and determined that the main components of concern are CO and H₂ components. Afterward, the diffusion law of in-situ coal gas is analyzed and studied under different working conditions, such as wind speed, temperature, pipe diameter, leakage direction, and leakage aperture ratio. The results indicate that when a pipeline leak occurs, the CO component has the largest influence range. With increasing wind speed, the warning boundary of CO rapidly expands downwind, then gradually diminishes, reaching a peak value of 231.62 m at 7 m/s. The range of influence of the leaked gas is inversely proportional to temperature and directly proportional to pipe diameter and leakage aperture ratio. When the gas leaks laterally, the diffusion early warning boundary value of each component is maximal. Among them, the leakage aperture ratio has a significant impact on the concentration distribution of in-situ coal gas, whereas the effect of temperature is relatively minor. This study contributes to an understanding of the leakage and diffusion characteristics of in-situ coal gas-gathering pipelines. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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23 pages, 3710 KiB

Open AccessArticle

A Novel Hybrid Internal Pipeline Leak Detection and Location System Based on Modified Real-Time Transient Modelling

by Seyed Ali Mohammad Tajalli, Mazda Moattari, Seyed Vahid Naghavi and Mohammad Reza Salehizadeh

Modelling 2024, 5(3), 1135-1157; https://doi.org/10.3390/modelling5030059 - 2 Sep 2024

Cited by 2 | Viewed by 1776

Abstract

A This paper proposes a modified real-time transient modelling (MRTTM) framework to address the critical challenge of leak detection and localization in pipeline transmission systems. Pipelines are essential infrastructure for transporting liquids and gases, but they are susceptible to leaks, with severe environmental [...] Read more.

A This paper proposes a modified real-time transient modelling (MRTTM) framework to address the critical challenge of leak detection and localization in pipeline transmission systems. Pipelines are essential infrastructure for transporting liquids and gases, but they are susceptible to leaks, with severe environmental and economic impacts. MRTTM tackles this challenge with a three-stage operational process. First, “Data Collection” gathers sensor data from designated observation points. Second, the “Detection” stage identifies leaks. Finally, “Decision-Making” utilizes MRTTM to pinpoint the exact leak magnitude and location. This paper introduces an innovative method designed to significantly enhance pipeline leak detection and localization through the application of artificial intelligence and advanced signal processing techniques. The improved MRTTM framework integrates AI for pattern recognition, state space modelling for leak segment identification, and an extended Kalman filter (EKF) for precise leak location estimation, addressing the limitations of traditional methods. This paper showcases the application of MRTTM through a case study using the K-nearest neighbors (KNN) method on a water transmission pipeline for leak detection. KNN aids in classifying leak patterns and identifying the most likely leak location. Additionally, MRTTM incorporates the EKF, enabling real-time updates during transient events for faster leak identification. Preprocessing sensor data before comparison with the leakage pattern bank (LPB) minimizes false alarms and enhances detection reliability. Overall, the AI-powered MRTTM framework offers a powerful solution for swift and precise leak detection and localization in pipeline systems. The functionality of the framework is examined, and the results effectively approve the effectiveness of this methodology. The experimental results validate the practical utility of the MRTTM framework in real-world applications, demonstrating up to 90% detection accuracy and an F1 score of 0.92. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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15 pages, 6330 KiB

Open AccessArticle

Study on Wax Deposition Process of Crude Oil System under Shear Flow Field Conditions

by Haibo Liu, Chao Yang, Jingjing Qi, Chao Liu, Haijun Luo and Bingfan Li

Processes 2024, 12(8), 1774; https://doi.org/10.3390/pr12081774 - 21 Aug 2024

Cited by 1 | Viewed by 1204

Abstract

This paper adopted numerical simulation based on the MD method to research the effect of different shear rates and wax contents on wax deposition focused on crude oil. The findings indicated that under shear flow conditions, there were primarily four steps during deposition. [...] Read more.

This paper adopted numerical simulation based on the MD method to research the effect of different shear rates and wax contents on wax deposition focused on crude oil. The findings indicated that under shear flow conditions, there were primarily four steps during deposition. Diffusion was the initial stage when wax diffused onto the metal surface. In the second stage, wax adsorbed onto a metal surface aligned itself parallel to the surface via Brownian motion, generating two different kinds of deposits. Subsequently, agglomerates were formed between the adsorbed deposits and the wax as a result of molecular interactions and bridging effects. Furthermore, the second and third deposited layers gradually showed peeling off and sliding under shear force. The wax deposition process was comparable for crude oil systems with varying shear rates and wax concentrations, and the deposited layer’s thickness on the metal surface was constant. The first, second, and third deposits were mainly adsorbed at 0.122 nm, 0.532 nm, and 1.004 nm away from the Fe surface, and the interaction energy between crude oil molecules and the Fe surface was mainly vdW force. The contact between Fe and wax progressively increased as the shear rate and wax content rose, promoting the wax adsorption on the metal surface and causing more of the wax to congregate in the deposited wax. The findings of the research can theoretically help a more thorough comprehension of the wax deposition. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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22 pages, 5866 KiB

Open AccessArticle

Structure Analysis of the Fractionator Overhead Vapor Line of a Delayed Coker Unit

by Chun-Lang Yeh and Yu-Hsi Chung

Appl. Sci. 2024, 14(16), 7193; https://doi.org/10.3390/app14167193 - 15 Aug 2024

Viewed by 914

Abstract

In view of the great impact of the pipeline system in a delayed coker unit (DCU) on production and operation safety, we applied computational fluid dynamics (CFD) to investigate the flow in a fractionator overhead vapor line connected to an air cooler in [...] Read more.

In view of the great impact of the pipeline system in a delayed coker unit (DCU) on production and operation safety, we applied computational fluid dynamics (CFD) to investigate the flow in a fractionator overhead vapor line connected to an air cooler in a previous study. The causes of the pipeline damage and the strategies to alleviate the occurrence of the damage were discussed. It is found that if two 24″ pipes are connected and five 18″ pipes are also connected, the force uniformity can be improved, and the forces on the caps, reducers, and T-junctions can be reduced. In this paper, we further applied the finite element method to perform structure analysis to confirm the strength of the original and the improved pipeline system. It is found that the static stress is larger when the pipelines are connected. The first four modes of the pipeline vibration are primarily affected by the vibration of the 30″ main pipe, while the fifth and the sixth modes are primarily affected by the vibration of the smaller pipes. In the case of a magnitude 1 earthquake (parallel mode) and a magnitude 2 wind, the maximum harmonic response stresses (stresses obtained from harmonic response analysis) occur at the same locations. After the pipelines are connected, some positions of the maximum harmonic response stresses are shifted from the 30″ main pipe to the 24″ pipe. In terms of the wind effect, the pipelines connected or unconnected can both withstand moderate typhoons of magnitude 13 without fatigue damage. In terms of the seismic effect, the pipelines connected can withstand a strong earthquake of magnitude 5(+) without fatigue damage, while the pipelines unconnected can withstand a very strong earthquake of magnitude 6(−) without fatigue damage, which is better than the pipelines connected. Under the action of a magnitude 17 severe typhoon, the stresses for the pipelines connected or unconnected are both lower than the yield strength and the ultimate tensile strength (UTS). There is no danger of immediate damage in terms of the wind effect. The pipelines connected or unconnected can withstand magnitude 7 earthquakes up to accelerations of 1718 gal (17.18 m/s²) and 2236 gal (22.36 m/s²), respectively, without exceeding the UTS. The pipelines unconnected are slightly better than the pipelines connected in terms of earthquake resistance. The purpose of this series study is to explore the flow development and the structural strength of the DCU pipeline system to improve its operational safety. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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10 pages, 3876 KiB

Open AccessArticle

Research on the Effect of Static Pressure on the Rheological Properties of Waxy Crude Oil

by Chao Yang, Jingjing Qi, Bingfan Li and Haijun Luo

Processes 2024, 12(8), 1712; https://doi.org/10.3390/pr12081712 - 15 Aug 2024

Viewed by 931

Abstract

In this paper, with the application of a MARS 60 high-pressure rheometer, experimental tests are conducted on Shengli crude oil to test its gel point, viscosity and thixotropy under different static pressures. Consequently, the effect of static pressure on the rheological parameters of [...] Read more.

In this paper, with the application of a MARS 60 high-pressure rheometer, experimental tests are conducted on Shengli crude oil to test its gel point, viscosity and thixotropy under different static pressures. Consequently, the effect of static pressure on the rheological parameters of waxy crude oil is revealed. It is proven that with the increase in the static pressure, the gel point of Shengli crude oil increases linearly, and the viscosity also gradually increases. The power law equation is employed to describe the relationship between the apparent viscosity and shear rate of Shengli crude oil under different static pressures. With the increase in the static pressure, the consistency coefficient (K) increases linearly, and the rheological index (n) decreases linearly. The relationship between the viscosity of Shengli crude oil and the static pressure and shear rate can be obtained. The Cross thixotropic model is used to describe the thixotropic curve of Shengli crude oil under different static pressures. With the increase in the static pressure, the thixotropic coefficient of consistency (ΔK) and the structure fracture constant (b) increase linearly. This is because a high pressure results in high structure strength and strong non-Newton rheological behavior in gelled crude oil and also causes remarkable structure fracture in crude oil. The results in this paper can provide an important theoretical basis for crude oil production and transportation. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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15 pages, 5946 KiB

Open AccessArticle

A Reliability Assessment Method for Natural Gas Pipelines with Corroded Defects That Considers Detection Cycles

by An Li, Feng Jin, Yuan Li, Wen Lan, Pan Liu, Zhifeng Yu and Kai Wen

Energies 2024, 17(14), 3366; https://doi.org/10.3390/en17143366 - 9 Jul 2024

Viewed by 1304

Abstract

With the development of natural gas pipelines, the proportion of aged pipelines in service has been increasing, and corrosion remains a primary cause of pipeline failure. Regular inspections and reliability assessments are crucial to ensure the safe operation of pipelines. This study investigated [...] Read more.

With the development of natural gas pipelines, the proportion of aged pipelines in service has been increasing, and corrosion remains a primary cause of pipeline failure. Regular inspections and reliability assessments are crucial to ensure the safe operation of pipelines. This study investigated an efficient reliability assessment method for corroded pipelines that considers in-line inspection intervals. First, this study compared the commonly used limit state equations for corrosion defects to select one suitable for X80-grade steel pipelines. Additionally, a Tail-Fit Monte Carlo Simulation (TF-MCS) algorithm was proposed to improve the computational speed by 30 times compared to traditional Monte Carlo simulations. Then, this study explored the inspection intervals used for reliability assessments of corroded pipelines. Finally, the parameter sensitivity was analyzed considering the yield strength, maximum operating pressure, and pipe diameter. This study ensures the reliable operation of corroded gas pipelines. Full article

(This article belongs to the Topic Oil and Gas Pipeline Network for Industrial Applications)

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