Oil Pipelines Research Articles

Numerical analysis of transient soil temperature variation during wildfires

In this study, transient behavior of soil temperature during large forest fires is analyzed using the Comsol© software package. The increase in soil temperature during large wildfires can be very critical, especially when oil or gas pipelines have been laid at a certain depth in the soil mainly near forests. During forest fires, the temperature of the soil surface can reach extreme levels that penetrate deep into the ground if the fire is not extinguished within a short time. This increase in temperature on the soil surface can lead to extremely dangerous situations if the laying depth of the pipeline is not sufficient, as the heat conducted through the soil causes the surface temperature of the pipeline and therefore that of the fluid inside it to reach even high values. This can lead to a sudden rupture of the pipeline and ultimately lead to catastrophic consequences. The present study is conservative due to the assumptions made in structuring the numerical model. However, it is believed to provide invaluable information about the considerations in selecting gas pipeline locations and pipeline laying depths taking into account extreme temperatures due to wildfires. There is limited research on the topic regarding the time dependent conduction heat transfer through soils as a result of fires, but only in one dimension. Current study, being multi-dimensional, is therefore believed to be novel in the field. Future research could include extensive study on the energy content of different species of forest trees, considering their time-dependent heat release rates (HRR) during a forest fire, as well as experimental work if a field setup could be designed.

Path Planning Techniques for Underwater Robots Based on Obstacles in Subsea Oil Pipelines

With the continuous growth of global energy demand, the safety and maintenance of underwater oil pipelines have become a focal point of international concern. Autonomous Underwater Vehicles (AUVs) are increasingly pivotal in inspection, maintenance, and repair of oil pipelines. This paper explores path planning techniques for underwater robots based on obstacles in subsea oil pipelines to enhance operational efficiency and safety. Employing theoretical analysis and simulation, the study systematically addresses key issues in path planning, including environmental modeling, obstacle recognition, path generation, and optimization. By constructing complex underwater environment models and integrating advanced algorithms such as improved ant colony optimization, genetic algorithms, and particle swarm optimization, the research investigates path planning strategies for AUVs under various obstacle distributions. The results demonstrate that the proposed path planning techniques effectively handle obstacles in subsea oil pipelines, significantly improving planning efficiency and robustness. Additionally, the feasibility of multi-robot collaborative path planning is discussed, providing theoretical support for future advancements in underwater robotics. Overall, this study offers new technological insights for the maintenance of underwater oil pipelines and is crucial for enhancing the intelligence level of underwater operations.

Infrared and Visual Fusion Detection Framework for Oil and Gas Pipeline Environmental Inspection

The inspection of oil and gas pipeline retains important. These newly constructed pipelines may have defects near the circumferential welds and potential issues with water accumulation. Improper management of these issues can lead to severe consequences. Thus, the inner pipe structure detection prior to their operation is critically essential. Visual camera provides a direct view of the pipeline environment such as circumferential weld seams and water accumulation. In contrast, infrared thermal camera capture infrared radiation distribution from varied shapes and materials, offering an indirect insight into the pipeline environment. This paper designs an integrated infrared and visual NDT system for pipeline detection, capable of capturing time-synchronized infrared and visible image pairs along with corresponding odometer and gyroscope data for further processing. Moreover, an infrared and visual fusion detection algorithm is proposed, comprising coarse registration, base detectors, and probability-based late fusion strategy. The late fusion strategy enhances detection accuracy by leveraging the complementary information from both infrared and visual modalities. Furthermore, as the focus is primarily on the defects near the circumferential welds, the size of the circumferential welds in forward images can be used to predict their position in the circumferential visual detection system, achieving a 96.7% reduction in computational complexity compared to processing all images. The proposed system and algorithm were actually tested in a 26.8 km 1219 pipeline. The results verified the reliability of the system and the robustness and accuracy of the algorithm. The demo code is available at: [https://github.com/ljcuestc/Probability-based-late-fusion.git].

Investigation of the kinematics behavior of spherical detector with different diameter ratios in oil pipelines

The spherical detector is an important technical equipment for water supply pipeline leakage detection. Its stable operation inside the pipeline will be affected by the fluid state in the pipeline, and the motion law of detectors with different diameters is different. In this paper, the dynamic analysis is carried out using the numerical simulation method, and the motion of spherical detectors with different diameters in horizontal oil pipelines is simulated. It is found that the flow state of the detector changes from the acceleration stage to the stable stage during the motion process, and with the decrease of the diameter ratio, the pressure difference between the front and back of the detector gradually increases, the thrust shows an upward trend, and the speed shows a greater speed in the stable stage. The motion behavior of the detector under different pipe diameter ratios is obtained, which provides help for the subsequent optimization of the shape design of the micro-leakage internal spherical detector.

Non-Contact Magnetometric Diagnostics of Pipelines Using the Metal Magnetic Memory Method

The non-contact magnetometric diagnostics (NCMD) of buried pipelines (oil and gas pipelines, heat lines, water supply lines, etc.) has been developed by Energodiagnostika Co. Ltd. since 2000 based on the 25-year experience of the metal magnetic memory (MMM) method application (ISO 24497-1:2007(E)). NCMD is based on measurement along the pipeline route of the Earth’s magnetic field intensity (HEarth) distortions caused by variation of the pipe metal magnetization in stress concentration zones (SCZs) and in zones of developing corrosion-fatigue damages. The paper describes the experience of complex diagnostics of buried pipelines based on NCMD, the MMM method and conventional methods of non-destructive testing. Based on NCMD results, the most strained pipeline sections are determined for their opening and additional control by the MMM method, ultrasonic testing and other NDT methods. On opened pipeline sections the MMM method is used to determine the presence of defects and the mechanical properties of the metal by hardness parameters. Inadmissible defects are removed, and the actual mechanical properties (yield strength and ultimate strength) are taken into account in check strength calculations. The inspection should provide the answer to the following question: “Where and when should a damage or an accident be expected?”. If this task is solved, then the possibility of timely replacement or repair of a potentially hazardous section is provided. Application of NCMD in combination with additional inspection of pipelines (UT, eddy current, etc.) in prospect holes determined by NCMD is aimed exactly at solution of this problem. The paper presents the experience of NCMD of buried polyurethane foam insulated pipelines in order to detect girth welded joints with developing damage.

Innovative projection acquisition algorithm for optimizing portable LNDCT in oil and gas pipeline imaging

Fluid pipelines, commonly utilized in the oil industry, often face efficiency and reliability issues due to sediment buildup causing erosion, corrosion, and pipe wall thinning. Traditional assessment methods involve disruptive measures like cutting or creating holes and temporarily taking pipelines out of service. A non-destructive alternative, Limited-Number-Detector Computed Tomography (LNDCT), proves cost-effective and superior. Our proposed algorithm enhances data acquisition and projections using discrete detectors, employing Co-60 as a gamma-ray source and thallium-doped sodium iodide, NaI(Tl), detectors in an arc configuration. Monte Carlo simulations aligned closely with experimental data. Optimization involved adjusting the detector aperture angle based on a primary-to-scatter ratio of gamma-ray photons. We investigated the utility of various isotopes (Co-60, Cs-137, Am-241, Ir-192) to determine optimal projection signal amplitude. The algorithm generates a large sinogram matrix, and a filtered back-projection algorithm with a Hamming filter maximizes image quality while ensuring acceptable calculation volume and time. Using four phantoms, including pipelines filled to different scales, our study evaluates LNDCT configuration, performance, and validation. The results highlight its potential for efficiently evaluating sediment in pipelines, confirming the correctness and accuracy of our proposed algorithm.

Oil and Gas Pipeline Integrity Monitoring and Alert System

The oil and gas industry face significant risks of explosions, often due to factors like gas and oil leakage as well as external corrosion. These substances are highly flammable, and even minor leaks can create volatile environments where the smallest spark can lead to catastrophic explosions. While internal corrosion in pipelines receives attention, external corrosion is often overlooked. Over time, pipeline coatings deteriorate, leaving them susceptible to external corrosion, which can result in leaks, endangering workers and the environment. Detecting and addressing corrosion promptly is crucial for preventing accidents and environmental harm. To address these challenges, a pipeline monitoring system has been developed using a Raspberry Pi Model 3B+ and advanced sensors. This system continuously monitors temperature, pressure, and external corrosion along pipeline routes. It utilizes a K-type thermocouple and a 1.2MPa pressure transducer for real-time data collection. Additionally, a laptop camera integrated with YOLOv8 enables visual inspection for detecting corrosion. The Raspberry Pi processes sensor data and images, triggering alerts for anomalies like temperature or pressure drops indicating leaks, or corrosion spots identified by YOLOv8. The system interfaces with ThingSpeak for remote data visualization and analysis, empowering operators to make informed decisions and take prompt corrective actions.

Ni-W composite coating reinforced with CrN nanoparticles on X80 pipeline steel: Preparation and characterization

X80 pipeline steel is crucial for oil and gas pipelines. Friction between particulate matter and the inner wall causes abrasive wear during transport, while corrosive environments further degrade the pipeline, leading to leaks. In this study, a nanoscale Ni-W-CrN composite coating was successfully prepared on X80 steel via electrodeposition for protection. The coating's surface morphology, microstructure, and composition were analyzed. The effects of CrN nanoparticle concentration and deposition temperature on the coating's structure, wear, and corrosion resistance were investigated. At 10 g/L CrN and 60°C, the Ni-W-CrN film showed a fine-grained surface with 8.13 wt% CrN, achieving 810 HV microhardness and improving wear and corrosion resistance by 81 % and 89 % compared to Ni-W coatings.

The invisible risks of the trans-Ecuadorian oil pipeline system: An analysis of social preferences in Quito

The invisible risks of the trans-Ecuadorian oil pipeline system: An analysis of social preferences in Quito

Research on the interaction between trench material and pipeline under fault displacement

With the large-scale construction of oil and gas pipelines, the safety issues of long-distance buried pipelines in the service and construction have become increasingly prominent. The complex geological and topographical conditions of the special zone will put forwards extremely high requirements on pipe trench laying backfill materials and construction technology. For example, pipelines are inevitable to cross the active fault, while the trench backfilled with soil has limitations in protecting them from failure under the active fault displacement caused by the earthquake. Therefore, it is necessary to study the pipe–soil interaction mechanism, determine the stress state of the pipeline and propose a new backfilling material that can protect the pipeline from failure. Foam concrete (FC) provides a new choice to backfill the buried pipeline trench due to its high-homogeneity, lightweight, controllable-strength, and self-compacting. To further determine the applicability of the FC, the pipe-FC interaction mechanism is studied. Then, a FE model of the FC-pipeline-soil interaction system is established by Abaqus to quantitatively analyze the applicability of the FC based on the experimental data of the mechanical performance of the FC. It proves that using FC as trench backfill material has a noticeable protective effect on the pipeline under the earthquake-induced displacement of the normal fault. Furthermore, FC has a better protective effect on the pipeline subjected to compressive than tensile. Therefore, the reference for applying FC in trench backfilling of pipelines crossing normal fault is provided.

Effect of Oil-Water Intermittent Wetting on Corrosion Inhibition of Carbon Steel in CO2 Environment

ABSTRACT Produced water can cause internal corrosion in oil pipelines. The flow of hydrocarbons and water can result in intermittent surface wetting, which can impact corrosion inhibition. However, this is still poorly understood. This research studies the impact of intermittent wetting and the wettability of the steel surface on corrosion inhibition, utilizing electrochemical techniques. An inhibitor model compound and model oil were employed at 25°C and 55°C in CO2 saturated solutions. Corrosion inhibition varied with temperature and steel surface hydrophobicity, altering inhibition significantly after intermittent contact with hydrocarbon at 55°C. EIS and wettability results revealed distinct protective mechanisms when oil was present.

Study on the Flow Characteristics of Heavy Oil-Water Two-Phase Flow in the Horizontal Pipeline.

Aiming at the problem of transportation for heavy oil during the middle-later development stages of the Lvda oilfield, based on the self-developed design of a visual circulating flow experimental apparatus for heavy oil-water two-phase flow-the flow regime characteristics and corresponding drag properties of the two-phase flow of Lvda viscous oil, which is simulated by 500# industrial white oil and water in a horizontal pipeline are investigated experimentally. According to the Kelvin-Helmholtz instability theory, the flow pattern transition criteria from stratified flow to annular flow (AF) are proposed. The effects of 0.11-0.90 m/s oil superficial velocities, 0.06-1.49 m/s water superficial velocities, and 0.09-0.93 input water cuts on the drag reduction effect of different flow regimes are analyzed. The experimental results indicated that with the increase of mixing velocity and water volume fraction, stratified flow, AF, oil plug flow, and dispersed oil lump flow are successively observed in the horizontal heavy oil-water two-phase flow, in which AF is the main flow pattern. As the Froude number increases to 4.0, the input water volume fraction does not change any more and remains at about 10% of the total flow rate in the process of converting from stratified flow to AF. The four delivery approaches can archive the reduction of transportation resistance for heavy oil at different degrees, in which the transportation of heavy oil surrounded by a water ring has the best effect of drag reduction. At the optimal working conditions of 0.61 m/s oil superficial velocity, 0.07 m/s water superficial velocity, and 0.10 input water cut, the pressure drop of water annulus conveying for heavy oil is only 1/62.54 of that of separate transport for pure heavy oil under the same oil flow rate.

Prediction of external corrosion rate for buried oil and gas pipelines: A novel deep learning method with DNN and attention mechanism

Buried pipelines is easily subjected to external corrosion affected by complex underground environment, such as soil resistivity, pH, dissolved ion concentration, water content and coatings condition. Therefore, external corrosion rate prediction is essential to ensure pipelines intrinsic safety. Generally numerous researches focused on mathematical models and degradation analysis are limited to considering comprehensive corrosion factors. In this work, a novel proposed deep learning method involves a deep neural network (DNN) and attention mechanism which has good robust generalization ability. DNN was used to predict external corrosion rate of buried pipelines with extracting corrosion characteristics data, and attention mechanism is carried on weighting operations of corrosion factors furtherly. The results show that main controlling factors are pipeline age and soil bulk density, sulfate ion concentration and redox potential have less effect by analyzing external corrosion factors dataset, and data reduction and standardization of DNN-attention mechanism model are carried out. The external corrosion rate value predicted by the DNN-attention mechanism model is the closest prediction with the real truth, which the evaluation index root mean square error (RMSE) is 0.0064, and prediction accuracy is 91.91 % compared with convolutional neural network (CNN), CNN-residual, DNN. It proves that it is reasonable to predict pipeline external corrosion rate using DNN-attention mechanism based on publicly pipeline corrosion dataset.

Analysis of process of deformation and fracture of oil pipeline under single static loading

Analysis of process of deformation and fracture of oil pipeline under single static loading

Experimental investigation of wax deposition on multiple steel alloys

Paraffin wax deposition is a flow assurance issue that occurs frequently in subsea crude oil and gas condensate flowlines and pipelines. While some mitigation techniques involve coatings, most wax deposition in the oil and gas industry occurs on bare pipe walls made of various steel alloys. Previously, there has not been any investigation into the possibility of differences in the wax deposition that could be attributed to the different types of steel alloys, and this study set out to fill that gap. A cold finger apparatus with interchangeable fingers was used to generate deposits. Deposits were created from waxy model oils across several bulk oil temperatures and rotational speeds. To cover a wide array of materials, six different steels were tested: A2, A36, 1018, 4130, 304, and 316. These materials range from low-carbon steels to high-chrome content stainless steels. Each cold finger's surface was finished with the same process to create a roughness of 4.6 ± 0.5 mm. Deposit mass, thickness, and composition all showed non-negligible differences between deposits formed on the steels investigated: masses varied by 5–15%, thicknesses varied by 30% or more, and deposit compositions were noticeably skewed. Alloy composition, contact angle, roughness, and thermal conductivity were discussed as possible indicators of the effects an alloy would have on wax deposition. These findings facilitate the comparison and interpretation of the results from wax research literature using different steel alloys as well as the design of laboratory wax testing that more closely resembles field conditions.

Model test on cooling performance of a new method for mitigating permafrost thaw around buried oil pipeline

Buried pipelines have been widely used to transport petroleum-based products over long distances in permafrost regions. Field observations reveal that they are endangered by rapid permafrost thawing and resulting massive soil movements, despite adopting some measures to protect pipeline foundation permafrost. A new mitigation technique is proposed to slow down the permafrost thawing ulteriorly. With this technique, a seasonal air-cooled embankment (SACE), mainly composed of a crushed rock layer, supports the pipeline and transfers the heat from the pipeline to ambient air in the cold seasons. A scale model test with the controlled air and oil temperatures was carried out to evaluate the proposed measure. The temperature and volumetric unfrozen water content of the permafrost subgrade beneath both the SACE and the direct-buried pipeline, as well as ground surface displacements, were measured during the whole testing process. A comparison of the hydrothermal process of the subgrade permafrost under the SACE and the direct-buried warm pipeline indicates that the proposed measure can substantially mitigate the rapid thawing of permafrost by controlling the geothermal regimes of the pipeline.

Eco-sabotage as Defensive Activism

AbstractI argue for the conditions that eco-sabotage (sabotage involving the protection of animals or the environment) must meet to be a morally permissible form of activism in a liberal democracy. I illustrate my case with Jessica Reznicek and Ruby Montoya’s oil pipeline destruction, the Sea Shepherd Conservation Society’s whale hunt sabotage, and the Valve Turners’ pipeline shut-off, climate necessity-defense. My primary contention is that just as it is permissible to destroy an attacker’s weapon in self- or other-defense, it is permissible to engage in some forms of eco-sabotage. Taking inspiration from just war theory, I use the conditions of just cause, reasonable chance of success, proportionality, necessity, and discrimination to both conceptualize eco-sabotage as defense and illustrate the justificatory burden the eco-saboteur must meet. Often eco-sabotage is doubly pro-tanto wrong because it is illegal and involves property destruction. Overcoming these hurdles is particularly difficult because in seemingly bypassing democratic means of dispute resolution, the eco-saboteur seemingly coerces the other members of society by forcing idiosyncratic views upon them. Non-anthropocentric eco-sabotage grounded in defense of animal rights has mixed results regarding the democratic objection just described. I argue that anthropocentric eco-sabotage, grounded in defense of human rights, has the best chance of overcoming this objection, provided a persuasive case can be made for its reasonable chance of success. Passing a reasonable chance of success also causes problems for non-anthropocentric eco-sabotage grounded in species defense, while non-anthropocentric eco-sabotage grounded in defense against animal suffering has a lighter justificatory burden.

Reliability-based maintenance optimization of long-distance oil and gas transmission pipeline networks

This paper presents a maintenance model for optimal planning of pipeline network inspections subjected to corrosion and residual stress. The proposed model includes predictive degradation modeling, spatio-temporal reliability, and expected cost minimization. The pipeline networks are formed by linear segments and irregular zones such as elbows, weld joints, and flanges for putting pipes together and changing the direction of gas or liquid flow. The mean of Karhunen-Loève expansion is used to model space-variant corrosion, residual stress, and stochastic dependency in different exposure zones. Monte Carlo simulations are employed to compute the failure probability of individual components. Subsequently, a Bayesian network evaluates the failure probability of the complex pipeline network and identifies the most critical components. Depending on the objective or market demand uncertainties, a cost model is also proposed to optimize the inspection policy. The methodology is applied to a case study, and the results show that it can provide valuable insights to decision-makers to enhance complex systems' safety and reliability.

Research on the defect depth detection for pipeline steel with double defects using metal magnetic memory method

Metal magnetic memory testing is an effective method to detect the stress state of ferromagnetic materials, and shows great application potential in the field of defect detection of oil and gas pipelines recently. In this paper, the correlation between the normal component of residual magnetic field (RMF) and the defect depth, as well as the applied loading were investigated by tensile tests. The X70 pipeline steels were processed into specimens with double defects of six types of depths and three types of spacings. Some magnetic parameters are defined to characterize the distortion of the RMF in the defect area. The effect of defect depth and applied loading on the magnetic parameters is discussed. The RMF signals measured on the smooth side of the specimens were compared with those on the defective side. Results show that the normal parameters, obtained from the front and back of the specimens, are capable of detecting the defect depth. The slope of the linear relationship between the two increases with the increase of defect spacing. The expressions of normal magnetic parameters were derived based on the Jiles model and magnetic dipole model. The simulation results of defective side and smooth side were compared, as well as the simulation results of different defect spacing. The experimental and numerical simulation results show that the defect depth of pipeline steel can be evaluated by the characteristic parameters of the normal RMF signal under a certain stress level.

Analysis of the Processes of Paraffin Deposition of Oil from the Kumkol Group of Fields in Kazakhstan

The oil pipeline transportation of highly waxy oils when it is cold is accompanied by the deposition of paraffins in the inner surface of the pipeline. This study of the initial properties of the oil; the composition, structure, and nature of the components of normal alkanes in oil; and their influence on the aggregative stability of the resulting system makes it possible to find the best solutions to optimize the conditions of oil transportation with the lowest energy costs. This study shows that, according to the content of solid paraffin (14.0–16.2%), the oils of the Kumkol group of fields in Kazakhstan are highly waxy. They are characterized by high yield loss temperature values (+9–+12 °C), which also correlate with the values of the rheological parameters (τ0 1.389 Pa, 3.564 Pa). The influence of the temperature and shear rate on the shear stress and effective viscosity of the initial oils was studied. At temperatures below 20 °C, depending on the shear rate, there is an increase in the effective viscosity values (0.020 Pa∙s, 0.351 Pa∙s). The influence of the nature of solid hydrocarbons on the parameters of the paraffinization process and of the intensity of the paraffinization of the metal surfaces was studied. Our study shows that the main share of n-alkanes in the Kumkol and Akshabulak oils falls on paraffins of the C15–C44 group. The greater the temperature difference between the oil and the cold steel surface (≤40 °C), the lesser the amount of asphalt–resin–paraffin deposits (ARPDs) that fall out on the surface of the rod, although the content of long-chain paraffins prevails in these ARPDs. At the same time, the consistency of the released asphalt–resin–paraffin deposits (ARPDs) becomes denser, which makes their mechanical removal more difficult. Furthermore, the results of this study of the cooling rate shows that the rapid cooling of oils leads to the formation of a large number of crystallization centers, which leads to an increase in the values of the yield loss temperature and kinematic viscosity of the oils.