Oil Pipelines Research Articles

Impact radius of light oil pipeline leakage under different operating conditions

This study investigated the impact range of pipeline leaks for light oil pipelines under different operating conditions. Three different calculation methods were employed to study the influence of various factors, including obstacle height, wind speed, leak hole diameter, and slope, on the leak impact range of flowing fires, pool fires, and overpressure waves. The results indicate that the impact range decreases as the height of obstacles increases. The most significant decrease occurs when obstacles are 2 meters high, and further increasing the obstacle height leads to a less pronounced decrease. Wind speed has a complex influence on the impact range. For flowing fires, the impact range initially increases and then decreases with higher wind speeds. For pool fires, a higher wind speed leads to a larger impact range, while for overpressure waves, higher wind speeds result in a smaller impact range. Larger leak hole diameters lead to larger impact ranges for both fire radiation and overpressure waves. Increasing the environmental slope has a slight effect on the impact range. Sensitivity analysis indicates that wind speed has the most significant impact, followed by leak hole diameter, while the environmental slope has the least influence on the impact range.

Study on metal corrosion behavior of heat-affected zone of oil pipeline

Due to the influence of welding technology, a series of non-uniform and continuous heat-affected zones formed by welding seams is the weakest link of pipeline steel. Compared with the X70 steel, the heat-affected area is in the form of coarse acicular and massive ferrite, granular bainite, and a small amount of pearlite, with weak strength and corrosion resistance. Therefore, this paper simulated the heat-affected zone of the high-strength steel welding seam by the Gleeble 3500 thermal/force simulation testing machine for two heat cycles. Taking Shengli crude oil as the experimental medium, the metal corrosion morphology of heat-affected zones at different temperatures and transmission rates during hot oil transportation was analyzed through immersion experiment and corrosion morphology characterization. The results show that the increase in temperature and flow rate will increase the overall corrosion rate of the metal in the heat-affected area. In the range of 30∼50°C, pitting corrosion was the main corrosion feature of the metal, and in the range of 50∼70°C, the corrosion morphology of the metal changed from pitting corrosion characteristics to comprehensive corrosion characteristics. In the range of the flow rate studied (1∼4 m/s), the metal in the heat-affected area was mainly the overall corrosion rate, and the metal surface showed the erosion-corrosion characteristics along the flow rate direction.

Mechanical responses of shallowly buried pipelines to adjacent deep excavations considering heavy rainfall influence

Climate change has resulted in a high global incidence of heavy rainfall, severely damaging the urban infrastructure. The analytical method used to predict the mechanical response of pipelines under the influence of rainfall influence could serve as a valuable design basis in the preliminary stage. This study developed an analytical solution based on the stratified Green-Ampt model and displacement-controlled two-stage method. The first stage evaluates the greenfield soil displacement at pipeline elevation by employing the Mindlin solution and considering the superposed effects of excavation (unloading) and rainfall infiltration. The second stage predicts the mechanical responses of the pipeline by simplifying the pipeline–soil interaction into a continuous Euler–Bernoulli beam resting on a Winkler foundation model. The analytical solution was calculated using the finite difference method and verified against a published study. Finally, parametric studies were conducted to investigate the rainfall– excavation–pipeline interaction, including the rainfall intensity and duration, maximum lateral wall deflection, and pipeline location. The results showed that a 48-8-mm/h rainfall increased the maximum displacement and maximum bending moment of the pipeline by 6.54% and 7.93%, respectively. The prediction results provide practical guidance for designing deep excavations adjacent to pipelines buried under heavy rainfall conditions.

CRISIS IN NAMUN VILLAGE: UNRAVELING PT PERTAMINA EP TANJUNG'S LEGAL OBLIGATIONS AMID CRUDE OIL PIPELINE LEAKAGE

<p>Amidst the serene landscapes of Namun Village in Tabalong District, a rupture in an oil pipeline has disrupted the tranquility, prompting a closer examination of the environmental ramifications and legal accountabilities of PT Pertamina EP Tanjung within Indonesia's regulatory landscape. Through qualitative normative analysis utilizing secondary data, this study delves into the aftermath of the spillage, revealing its profound impact on the local ecosystem and community. It becomes evident that PT Pertamina EP Tanjung bears a significant responsibility in averting future incidents and ensuring adherence to environmental laws. Hence, a nuanced understanding of the legal framework emerges as pivotal in enhancing environmental stewardship, fostering corporate responsibility, and advancing sustainable practices in Indonesia's extractive industries.</p><p>Keywords: Cipta Kerja, Environtmental, Oil Leakage, Pertamina</p>

TRANSFORMATION OF THE RUSSIAN OIL INDUSTRY IN 2022-2023

The article examines the state of Russia’s oil industry over the period 2022 and 2023 as geopolitical changes shifted from one year to the next. The author notes that despite the sanctions pressure, Russia has successfully managed to reorient its oil markets towards Asia. Exports to India are the most actively developing; the ease of transition was due, among other things, to the availability of ready-made business in India: new refineries were built on the coast, for which oil was purchased from the nearest markets. In 2022-2023, India became the largest market for Russian oil delivered by sea. As for supplies via oil pipelines, China remains the largest consumer. Under these conditions, Russian companies have an opportunity use the competition between the countries to their advantage by reducing the discount on their products.The USA used to be the biggest buyer of Russian oil products until 2022, currently this role is taken by Turkiye. The state buys large volumes from Russia and then resells similar volumes to the EU countries. Despite the statements about different origin of oil products, formally the volumes of purchases and sales coincide.A significant role in the supply of Russian resources by sea is played by the shadow fleet, which began operating after the introduction of the «price ceiling». The fleet’s tankers have been bought off the world market by various companies that are registered offshore.There has been no reduction in production and exports due to technical problems caused by sanctions on the supply of equipment and technologies to Russia, or due to the withdrawal of Western oil service companies. Domestic structures quickly managed to establish a system of parallel imports, as well as to find alternative equipment in China.

Corrosion inhibition properties of sweet crude oil for carbon steel 1018 in NaCl solution

Abstract Aged oil pipeline production systems, historically designed without corrosion protection due to predominantly oil-wetted conditions, now face significant changes as increased water content in produced oil arises from field maturation. This work investigates the corrosion inhibition properties of sweet crude oil on carbon steel 1018 in a CO2-saturated NaCl solution using electrochemical testing (open circuit potential, polarization resistance, electrochemical impedance, potentiodynamic polarization) and surface characterization (SEM, EDS) techniques at 50 °C and pH 6. Carbon steel specimens were immersed in crude oil for durations ranging from 0 to 144 h before undergoing corrosion testing. Results showed that a 144-h immersion in crude oil led to an 88 % reduction in corrosion rate, comparable to the efficiency of standard quaternary ammonium-based inhibitors. Furthermore, a semi-empirical model predicting uniform CO2 corrosion rates for varying oil immersion durations is proposed and validated by comparing its predictions with experimental data from the electrochemical tests.

Insights into the synergistic effect of polylactam kinetic hydrate inhibitor and amino acid via molecular dynamics simulations

Technological innovation is urgently needed to solve the problem of hydrate formation in oil and gas transmission pipelines for the flow assurance guarantee. Typical kinetic hydrate inhibitors for industrial application are the combination of lactam-based polymers with solvent synergists. In this study, a novel non-solvent synergist leucine (Leu) was proposed for improving the kinetic inhibition effect of polyvinyl caprolactam (PVCap). The synergism of PVCap and Leu was investigated via molecular dynamics simulations. Results showed that the 1 wt% PVCap + 2 wt% Leu system can totally inhibit methane hydrate formation within the simulation period, and the combination systems with other concentrations have negligible effects on delaying hydrate nucleation but can significantly slow down the hydrate growth rate. The excellent synergism of PVCap and Leu may be due to the large diffusion coefficient of the molecules in the systems, which provides a high probability for the aggregation of methane molecules and induces the formation of bubbles. In addition, the bubbles can be further stabilized by the amphiphilic PVCap and Leu molecules around it. This study also provides new insights to develop powerful synergists for PVCap, which would be helpful to the design strategy of KHIs with high efficiency.

Effect of the Material of Oil Pipelines with 90° Elbows on the Degree of Erosion Using Computational Fluid Dynamics

Effect of the Material of Oil Pipelines with 90° Elbows on the Degree of Erosion Using Computational Fluid Dynamics

ВИКОРИСТАННЯ МОДУЛІВ КОМП’ЮТЕРНОЇ ПРОГРАМИ KDAM ДЛЯ ДИНАМІЧНОГО АНАЛІЗУ БАТАННОГО МЕХАНІЗМУ ПРИ ФОРМУВАННІ БАГАТОШАРОВИХ ТКАНИН

In the work, using the KDAM computer program module, a dynamic analysis of the batten mechanism of a heavy loom in the production of multilayer technical fabrics was carried out. The computer module allows you to determine the projections and full reactions in the hinges of the batten mechanism at the time of the weft thread surf in the zone of formation of multilayer fabrics, taking into account the structure of protective layers, main power layers and the method of connecting layers to each other. The influence of the structure of multilayer fabrics on the magnitude of dynamic reactions in the hinges of the batan mechanism was established. Multi-layer technical fabrics are used for the production of power grabs for laying pipes of oil and gas pipelines. Pipes are delivered with factory insulation. These fabrics have a high density of the main threads in the cross section of the power grip. The main thread system consists of the warp threads of the protective layers, the warp threads of the power layers, and the warp threads that bind the layers together. The formation of an element of multilayered technical fabric takes place by wefting the weft thread in the working area. Taking into account the very significant tension of the threads of the base, the strength of the surf can reach significant indicators. In the process of surf, there is a shock impact on the batting mechanism of the weaving loom. The resulting dynamic reactions in the hinges need to be evaluated, namely how the structure of multilayer fabrics affects the magnitude of the dynamic reactions in the hinges of the baton mechanism. Changing the structure of the multilayer technical fabric allows to reduce the tension of the base of the protective layers and power layers, which will lead to a decrease in the magnitude of the surf force and, as a result, to a decrease in dynamic reactions in the hinges of the batten mechanism. This will significantly reduce the wear in hinge pairs and increase the durability of the mechanism. To solve the complex task of dynamic analysis of the batting mechanism during the formation of multilayer fabrics, it is necessary to use specialized software complexes. The use of special computer modules allows you to determine the projections and full reactions in the hinges of the batting mechanism at the moment of the weft thread in the zone of formation of multilayer fabrics, taking into account the structure of protective layers, main power layers and the method of connecting the layers together.

Study on the Impact of Different Pile Foundation Construction Methods on Neighboring Oil and Gas Pipelines under Very Small Clearances

With the acceleration of transportation infrastructure and the densification of transportation networks, there has been an increase in bridge pile construction near oil and gas pipelines. Selecting bridge pile construction methods with minimal impact and reducing the adverse effects of bridge pile construction on nearby oil and gas pipelines are of great importance. This paper uses FLAC3D 6.0 software to simulate and analyze the impact of two different pile construction methods, rotary drilling and impact drilling, on adjacent oil pipelines. The results show that the horizontal displacement of oil pipelines during rotary drilling construction is nearly 90% lower than that of the traditional impact drilling method, and the axial stress is reduced by nearly 85%. Furthermore, numerical simulations of rotary drilling under different conditions were conducted to analyze and summarize the patterns of how different conditions affect construction vibration and stress. This study provides a reference for bridge pile construction near oil and gas pipelines or important buildings.

Systematic Evaluation of Ultrasonic In-Line Inspection Techniques for Oil and Gas Pipeline Defects Based on Bibliometric Analysis.

The global reliance on oil and gas pipelines for energy transportation is increasing. As the pioneering review in the field of ultrasonic defect detection for oil and gas pipelines based on bibliometric methods, this study employs visual analysis to identify the most influential countries, academic institutions, and journals in this domain. Through cluster analysis, it determines the primary trends, research hotspots, and future directions in this critical field. Starting from the current global industrial ultrasonic in-line inspection (ILI) detection level, this paper provides a flowchart for selecting detection methods and a table for defect comparison, detailing the comparative performance limits of different detection devices. It offers a comprehensive perspective on the latest ultrasonic pipeline detection technology from laboratory experiments to industrial practice.

Interpretable machine learning models for failure cause prediction in imbalanced oil pipeline data

Pipelines are critical arteries in the oil and gas industry and require massive capital investment to safely construct networks that transport hydrocarbons across diverse environments. However, these pipeline systems are prone to integrity failure, which results in significant economic losses and environmental damage. Accurate prediction of pipeline failure events using historical oil pipeline accident data enables asset managers to plan sufficient maintenance, rehabilitation, and repair activities to prevent catastrophic failures. However, learning the complex interdependencies between pipeline attributes and rare failure events presents several analytical challenges. This study proposes a novel machine learning (ML) framework to accurately predict pipeline failure causes on highly class-imbalanced data compiled by the United States Pipeline and Hazardous Materials Safety Administration. Natural language processing techniques were leveraged to extract informative features from unstructured text data. Furthermore, class imbalance in the dataset was addressed via oversampling and intrinsic cost-sensitive learning (CSL) strategies adapted for the multi-class case. Nine machine and deep learning architectures were benchmarked, with LightGBM demonstrating superior performance. The integration of CSL yielded an 86% F1 score and a 0.82 Cohen kappa score, significantly advancing prior research. This study leveraged a comprehensive Shapley Additive explanation analysis to interpret the predictions from the LightGBM algorithm, revealing the key factors driving failure probabilities. Leveraging sentiment analysis allowed the models to capture a richer, more multifaceted representation of the textual data. This study developed a novel CSL approach that integrates domain knowledge regarding the varying cost impacts of misclassifying different failure types into ML models. This research demonstrated an effective fusion of text insights from inspection reports with structured pipeline data that enhances model interpretability. The resulting AI modeling framework generated data-driven predictions of the causes of failure that could enable transportation agencies with actionable insights. These insights enable tailored preventative maintenance decisions to proactively mitigate emerging pipeline failures.

Indonesia’s offshore oil and gas: decommissioning uncertainty and the legal struggle

ABSTRACT Hydrocarbon extraction is generally associated with various environmental obligations, especially during the construction of oil platforms, pipelines, wells, and other facilities, as well as in the post-production phase. The offshore oil and gas industry creates problems for the environment and shipping safety. The contractor is required to decommission all production facilities that were built prior to the post-mining stage. However, this obligation is not easily met by Indonesia despite various international regulations. From the perspective of national law, decommissioning of oil and gas facilities is only a recent obligation due to weaknesses in the law regulating oil and gas activities involving multinational companies. Therefore, decommissioning has not been implemented to date. The delay in decommissioning contributes to Indonesia’s weakness in the protection of the marine environment and shipping security.

ШВИДКІСТЬ КОРОЗІЇ НИЗЬКОВУГЛЕЦЕВИХ ТРУБНИХСТАЛЕЙ У РІЗНИХ АГРЕСИВНИХ СЕРЕДОВИЩАХ

Low-carbon steels are the main material for the production of main oil and gas pipelines. Currently, new generation steels of the X70, X80 type are used in global practice, however long-term pipelines are made of 17Г1C steels (X50, X52). Corrosion of the inner and outer parts of pipes is the main factor in the failure of pipelines. The study examines the influence of aggressive environments on the corrosion rate of low-carbon steels of different generations. It was found that for a more aggressive environment the difference in corrosion rate for different steels becomes more significant, and X80 steel showed the best indicators of corrosion resistance in various aggressive environments.

Fire analysis using Sentinel-2 and Sentinel-5P data: Oil pipeline explosion near Strymba Village

Fire analysis using Sentinel-2 and Sentinel-5P data: Oil pipeline explosion near Strymba Village

A comparison of onshore oil and gas transmission pipeline incident statistics in Canada and the United States

This study analyzes the mileage and incident data between 1995 and 2016 corresponding to the onshore oil and natural gas transmission pipelines regulated by the Canada Energy Regulator (CER) and Pipeline and Hazardous Materials Safety Administration (PHMSA) of the United States. The analysis indicates that the material/weld/equipment failure is the leading failure cause for both CER and PHMSA pipeline incidents. The annual average incident rates of the CER and PHMSA pipelines are in the order of 10−3 per km except for the PHMSA gas pipelines, the annual incident rate of which is in the order of 10−4 per km. The annual average rupture rates of the CER and PHMSA pipelines vary from 3.5 × 10−5 to 4.5 × 10−5 per km. The F-N curves for the PHMSA pipelines are developed based on the mileage and incident data to quantify the societal risks posed by the pipeline in general.

Diagnostics of stationary regime in oil pipelines

Information on the evaluation of different modes of movement of liquids in pipelines is very important for the analysis and design of systems and facilities related to hydraulics and hydrodynamics, including hydrocarbon production and transportation systems. Knowledge of stationary and non-stationary types of motion makes it possible to predict and control the behavior of a fluid under various conditions. The paper discusses the issues of diagnosing stationary and non-stationary operating modes for horizontal and gravitational flows. It has been established that the time of transition to stationary mode in pipelines mainly depends on the geometric parameters of the pipeline and the rheological properties of the pumped systems.

Air–Water Two-Phase Flow Dynamics Analysis in Complex U-Bend Systems through Numerical Modeling

This study aims to provide insights into the intricate interactions between gas and liquid phases within flow components, which are pivotal in various industrial sectors such as nuclear reactors, oil and gas pipelines, and thermal management systems. Employing the Eulerian–Eulerian approach, our computational model incorporates interphase relations, including drag and non-drag forces, to analyze phase distribution and velocities within a complex U-bend system. Comprising two horizontal-to-vertical bends and one vertical 180-degree elbow, the U-bend system’s behavior concerning bend geometry and airflow rates is scrutinized, highlighting their significant impact on multiphase flow dynamics. The study not only presents a detailed exposition of the numerical modeling techniques tailored for this complex geometry but also discusses the results obtained. Detailed analyses of local void fraction and phase velocities for each phase are provided. Furthermore, experimental validation enhances the reliability of our computational findings, with close agreement observed between computational and experimental results. Overall, the study underscores the efficacy of the Eulerian approach with interphase relations in capturing the complex behavior of the multiphase flow in U-bend systems, offering valuable insights for hydraulic system design and optimization in industrial applications.

Ecological indicators and biological resources for hydrocarbon rhizoremediation in a protected area.

Spillage from oil refineries, pipelines, and service stations consistently leads to soil, food and groundwater contamination. Bacterial-assisted phytoremediation is a non-invasive and sustainable solution to eliminate or decrease the concentration of xenobiotic contaminants in the environment. In the present study, a protected area interested by a fuel discharge was considered to assess a bioremediation intervention. From the spill point, a plume of contamination flowed South-West into the aquifer, eventually reaching a wetland area. Soils, groundwaters and plants belonging to the species Scirpus sylvaticus (L.) were sampled. In the majority of the soil samples, concentrations of total petroleum hydrocarbons, both C ≤ 12 and C > 12, exceeded legal limits set forth in Directive 2000/60/EC. The analysis of diatom populations, used as ecological indicators, evidenced morphology alterations and the presence of Ulnaria ulna and Ulnaria biceps species, previously detected in hydrocarbon-polluted waters. Tests for phytotoxicity and phytodegradation, carried out in soil mesocosms, planted with Zea mays and Helianthus annuus, demonstrated that both species significantly contributed to the removal of total petroleum hydrocarbons. Removal of C ≤ 12 and C > 12 petroleum hydrocarbons was in the range of 80%-82% for Z. mays and 71%-72% for H. annuus. Microbial communities inhabiting high organic carbon and vegetated soils were more active in hydrocarbon degradation than those inhabiting subsoils, as evidenced by soil slurry experiments. The abundance of functional genes encoding toluene-benzene monooxygenase (tbmD) and alkane hydroxylase (alkB), quantified in environmental samples, confirmed that the plant rhizosphere recruited a microbial community with higher biodegradation capacity. Bacterial strains isolated from the sampling site were able to grow on model hydrocarbons (hexane, hexadecane and o-, m-, p-xylene) as sole carbon and energy sources, indicating that a natural bio-attenuation process was on-going at the site. The bacterial strains isolated from rhizosphere soil, rhizoplane and endosphere showed plant growth promoting traits according to in vitro and in vivo tests on Z. mays and Oryza sativa, allowing to forecast a possible application of bacterial assisted rhizoremediation to recover the protected area.

Magnetic Flux Leakage Defect Identification Method for Small-Diameter Pipeline Elbow Based on the Improved YOLOv5

Abstract The elbow is an important constituent of oil and gas pipeline systems and plays a key role in changing the direction of pipelines. Corrosion defects pose a significant risk to the safe operation of elbows. Magnetic flux leakage (MFL) detection has been developed as a suitable technique for identifying defects in pipelines. To address the distortion of elbow defect signals in the images arising from variations in the liftoff value of the leakage detector, this paper proposed an image identification method based on an improved YOLOv5 network. The differences in defect images are simulated by analyzing the liftoff value of the magnetization unit. A defect image enhancement method of multiscale retinex with color restoration fusion homomorphic filtering (MSRCR-HF) is employed to enhance the features of defective MFL signal images. To further improve the accuracy of the model, the YOLOv5 network is optimized by integrating the convolutional block attention module (CBAM) and the space-to-depth-nonstrided convolution (SPD-Conv) module. The results show that the proposed image enhancement method effectively accentuates the features of defect images. Moreover, the suggested image identification method exhibits superior accuracy in identification. The mean average precision (mAP) values for the original image set and the enhanced image set are 85.0% and 91.4%, respectively. Consequently, the proposed method is shown to be highly viable for the automatic identification of MFL defects in small-diameter pipe elbows.