Internal Corrosion Defects Research Articles

Consistency analysis of burst pressure in corroded pipelines

Abstract Due to the influence of the working environment and transport medium, corrosion defects inevitably occur on the inner and outer walls of natural gas pipelines. Scholars often studied the influence of internal and external corrosion defects on pipe burst pressure based on finite element method and experiment. However, it is not clear whether internal corrosion defects and external corrosion defects are consistent in burst pressure of pipelines. For this reason, this paper establishes the internal and external corrosion defect model of the pipe. Then, the burst pressures of pipelines with internal corrosion defects are compared with that with external corrosion defects. Finally, a burst pressure equation is proposed for the pipelines with internal corrosion defects and external corrosion defects. It was found that the burst pressure of the natural gas pipeline with internal and external corrosion defects was consistent. It provides a new idea for the establishment of a unified model to predict the burst pressure of corroded pipelines.

A quantitative assessment of the rehabilitative impact of Kevlar liners on offshore pipelines

Offshore pipelines transport oil and natural gas that contain different corrosive contaminants, leading to internal corrosions. The presence of internal metal loss problems can significantly degrade the load-bearing capacity and reliability of pipelines over time. To address this issue, a Kevlar liner, offering a more accessible and cost-effective solution, is employed for repairing corroded pipelines. However, a quantitative assessment of the rehabilitating effect of Kevlar liner has been lacking. This study performed an investigation of the burst pressure of internal corroded pipelines reinforced with the Kevlar liner through a combination of experimental testing and finite element numerical simulations. While previous research primarily concentrated on single external defect, this study has investigated the burst pressure of pipelines in the presence of both single and dual internal corrosion defects. The results indicated that the presence of two corrosion defects further decreases the burst pressure of the pipelines. This study examined the reinforcement mechanism of Kevlar liner, revealing that it largely postpones the stress development in the corrosion zone and thereby enhances the ultimate internal pressure load-bearing capacity of the pipelines. Moreover, the contact stress resulting from the friction between the Kevlar liner and the steel pipeline contributes to the overall improvement in the load-bearing capacity of the corroded offshore pipelines.

Design and study of novel square electromagnetic sensing based on stepped eddy current thermography

Nondestructive testing of internal corrosion defects is a key task to evaluate whether the material is repaired and replaced. In this paper, a novel square ferrite magnetic open sensing structure is designed for detecting volumetric corrosion defects on the inner surface of oil and gas storage tanks. A theoretical model of the structure is developed and the characteristics of the guided distribution of the electromagnetic field are resolved. The proposed model provides a region of interest with a uniform magnetic field. This greatly improves the detectability and thermal comparison of corrosion defects on the inner surface. In addition, the inspection is performed under weak excitation conditions and in the full open field of view of the infrared camera. This configuration greatly improves the portability and efficiency of workpiece inspection. Several open architecture sensors are evaluated and compared regarding temperature rise uniformity, model passability, and lightweight level. Meanwhile, the geometrical parameters of the square sensor, the operating parameters, and the material properties of the detected samples are investigated, including the coil height, the cross-arm length, the lifting distance, the operating frequency, the relative magnetic permeability of the sample, and the electrical conductivity of the sample. Finally, the detection capability of the sensors was verified through experiments with different steel plate thicknesses and defect morphologies.

Investigation into flow-induced internal corrosion direct assessment in small-diameter dry gas fluctuating pipeline

Small-diameter undulating natural gas pipelines with low gas transmission capacity do not have internal inspection conditions to grasp the internal corrosion status of the pipeline. This study focuses on a small-diameter undulating dry natural gas gathering and transportation pipeline, the internal corrosion mechanism of the pipeline is studied through corrosion products, and the specific location of the internal corrosion sensitive pipe segment is determined based on multiphase flow simulation and PMDT(pipeline non-contact magnetic anomaly detection); the excavation inspection is ultimately used to evaluate the internal status of the pipeline. The results demonstrate that the internal corrosion mechanism of ZL (ZI Lai) pipeline is O2 and CO2 synergistic corrosion in which O2 plays a dominant role, while the increasing flow rate will aggravate corrosion; The maximum general corrosion rate and critical inclination along the pipeline are 0.0218 mm/a and 18.4°, respectively. Furthermore, twelve corrosion sensitive segments have been identified, including two II-level and six III-level magnetic anomaly segments. The internal corrosion defects are localized at the 3–9o’clock position of the pipeline, with a maximum general corrosion rate not exceeding 0.0228 mm/a. Furthermore, the pipeline failure pressure of 12.27 MPa surpasses the maximum allowable working pressure of 8.84 MPa, ensuring its continued operational safety. The corrosion protection measures of reducing the water content of natural gas, adding vapor corrosion inhibitor and regularly detecting magnetic anomaly pipeline are developed.

Effects of external corrosion defect growth on wall pipeline under internal pressure and various defect sizes with mechano‐electrochemical interaction

AbstractThe assessment of the impact of corrosion defects on the integrity and safe operation of through‐wall pipelines is critical. In this work, a finite element‐based model was developed to study the mechano‐electrochemical (M‐E) effects of external corrosion defects on 10CrMoAl steel pipelines. The effects of parameters such as defect sizes and internal pressures on pipeline conditions are also studied. The results show that increased corrosion depth leads to stress concentration at the center of the defect. The increase in internal pressure causes local plastic deformation and anodic current density concentration at the inner edge of the defect and in the adjacent areas of the defect. M‐E interaction causes the growth of corrosion defects significantly at higher internal pressures. The corrosion defects increase with time. As the pressure increases, the failure pressure of the pipeline gradually decreases. The influence of defect depth on the corrosion rate at the defect is greater than that of defect width. With increasing in internal pressure and corrosion defect size, it will lead to more severe plastic deformation, resulting in accelerated corrosion.

Statistical study of localized internal corrosion defects in oil and gas pipelines through sampling inspection

Historical failure data of corroded oil and gas pipelines helps estimate risk and reliability using statistical models if the distribution of the characteristics of corrosion defects is known. This research presents a field survey of corrosion defect characteristics in Mexican oil and gas pipelines. Because of the different conditions that pipelines typically undergo and the different fluids that they transmit, it was found that corrosion defect depth has a bimodal behavior. This unusual characteristic is a reason to study the cause of this conduct in more detail. The fluid properties are of great importance to characterize statistically the internal corrosion damage. A Bayesian methodology allows the statistical estimation of the distribution for the depth of internal corrosion defects using limited information obtained from “unpiggable” pipelines.

Application of Improved Support Vector Machine in Predicting Failure Pressure of Oil and Gas Pipelines with Internal Corrosion Defects

In this study, the failure pressure of submarine oil and gas pipelines was predicted by using five commonly used machine learning models and derivative models. Firstly, an efficient local time-intensive finite element algorithm is constructed and used to generate a machine learning database. Secondly, in order to improve the accuracy of machine learning algorithm, the frontier optimization algorithm is improved to form a new predictive regression model IAEO-SVM model. To compare the accuracy of commonly used machine learning models and IAEO-SVM models, a comprehensive evaluation standard consisting of k-fold cross-validation and three statistical indicators was used. Finally, the influence of seawater depth and geometric factors of corrosion defects on the blasting pressure of submarine oil and gas pipelines was comprehensively analyzed through the high-dimensional surface built by the IAEO-SVM model. The IAEO-SVM model shows superior stability and accuracy compared to the comparison model, as demonstrated by its MSE’ of 0.0482, R2’ of 0.9982, MAE’ of 0.1295, and SD of 0.2198. The high-dimensional surface obtained through inversion shows a linear relationship between seawater depth and failure pressure. Meanwhile, the width of corrosion defects has a significant impact on failure pressure, accounting for up to 23% and thus cannot be overlooked.

Quantification of depth and morphology of internal corrosion defects by stepped eddy current thermography skewness under weak excitation conditions

In the nondestructive testing (NDT) of eddy current thermography of oil and gas tanks, the low and non-uniform temperature rise due to weak excitation conditions makes the quantitative estimation of the depth and area of defects still challenging. This work proposes a mathematical-physical model of skewness to characterize defect depth quantitatively. The skewness image is estimated in Gaussian scale space using the background difference method combined with the chunked threshold segmentation method to characterize the defect morphology. The experimental results show that the skewness is affected by the combination of defect depth and area. As the defect area decreases, the relationship between defect depth and skewness gradually degrades from nonlinear to linear, while the rate of change of skewness becomes insignificant. The skewness analysis model predicted the maximum MRE of 5.15%, the minimum R2 of 0.94 for defect depth, and the MRE of 8.39% for defect area. It shows that the skewness can effectively characterize the depth and morphology of internal corrosion defects.

Investigation into the mechano-electrochemical interaction of internal and external corrosion defects on pipe surfaces

Revealing the mechanical-electrochemical interactions (M-E) on internal and external defects in pipelines is of paramount importance for ensuring the safe operation of pipelines. The present study establishes a mechano-electrochemical multi-physics coupling model and develops a two-dimensional finite element (FE) model of internal and external defects on the pipe surface to investigate the M-E interaction of X100 steel pipe with corrosion defects on both internal and external surfaces. The results demonstrate that the M-E interaction is significantly influenced by the geometrical shape, relative position, and internal pressure of defects. Moreover, altering a single defect parameter can simultaneously impact the M-E interaction of two defects. As the depth of defects increases, the cross-sectional area between internal and external defects decreases, leading to an intensified interaction between mechanics and electromagnetics and a gradual concentration of M-E interaction at the center of defects. The magnitude of the M-E interaction exhibits a negative correlation with the length of the defect, while the presence of a long defect minimally impacts the M-E interaction on the opposing side. As the external defects gradually distance themselves from the internal defects, the M-E interaction diminishes and the concentration area of M-E interaction shifts in the opposite direction to defect migration, while stress in the non-defect region adjacent to both internal and external defects progressively intensifies. The increase in internal pressure significantly enhances the M-E interaction of internal and external defects, with the M-E interaction primarily focused on the minimum cross-sectional area of radial overlap between these defects. At low internal pressures, however, the M-E interaction becomes negligible.

An investigation on the effect of widespread internal corrosion defects on the collapse pressure of subsea pipelines

Deepwater subsea pipelines are an essential part of offshore oil and gas infrastructure, and it is a statutory requirement for operators to monitor the degradation of pipelines left-in-place at cessation of production. Collapse is one of the failure modes for subsea pipelines subjected to external pressure. Surface corrosion defects in subsea pipelines, either while still operational or after cessation of production, usually manifest as widespread or localized corrosion pits that are randomly spread on the steel surface. Extensive work has been done on predicting the collapse pressure of pipelines containing single corrosion defects however, the same cannot be said for randomly distributed corrosion defects. In this study, we investigate, for the first time, the effects of the geometry and coverage extent of widespread internal corrosion defects with random spatial distribution on the collapse pressure of pipelines using finite element analysis. The results show that corrosion defect depth and coverage surface area are the main defect geometric parameters that significantly influence the collapse strength of pipelines with randomly distributed internal corrosion. An empirical function for predicting the collapse pressure of a corroded pipeline is developed to reduce the need for recurrent computational effort.

Dense metal corrosion depth estimation

Introduction: Metal corrosion detection is important for protecting lives and property. X-ray inspection systems are widely used because of their good penetrability and visual presentation capability. They can visually display both external and internal corrosion defects. However, existing X-ray-based defect detection methods cannot present and estimate the dense corrosion depths. To solve this problem, we propose a dense metal corrosion depth estimation method based on image segmentation and inpainting.Methods: The proposed method employs an image segmentation module to segment metal corrosion defects and an image inpainting module to remove these segmented defects. It then calculates the pixel-level dense corrosion depths using the X-ray images before and after inpainting. Moreover, to address the difficulty of acquiring training images with ground-truth dense corrosion depth annotations, we propose a virtual data generation method for creating virtual corroded metal X-ray images and their corresponding ground-truth annotations.Results: Experiments on both virtual and real datasets show that the proposed method successfully achieves accurate dense metal corrosion depth estimation.Discussion: In conclusion, the proposed virtual data generation method can provide effective and sufficient training samples, and the proposed dense metal corrosion depth estimation framework can produce accurate dense corrosion depths.

Pipelines reliability assessment considering corrosion-related failure modes and probability distributions characteristic using subset simulation

A methodology using the subset simulation and the modified Metropolis-Hastings algorithm with delayed rejection (SS-MMHDR) is developed to evaluate the time-dependent reliability of corroded pipelines under multiple failure modes. This methodology considers the competition between the small leak and burst failures and the correlated non-normal distribution of the defect variables, and characterizes the defect geometric probability distribution from extensive inspection data. Results demonstrate that SS-MMHDR has high accuracy and low variability in evaluating the pipeline failures, outperforming the SS-MMH and Monte Carlo simulation algorithms, especially under low probability levels, but with slightly increased computation time. The Generalized Extreme Value Type II (GEVII) distribution is the optimal distribution for internal corrosion defect lengths from the Kolmogorov-Smirnov test. Lognormal, Weibull and Normal distributions provide more conservative estimates on burst and composite failure probabilities and limiting maintenance times than GEVII. Effects of operating pressure and its variability, corrosion rate on failure probability, and pipeline limiting maintenance time are also revealed through numerical cases.

Investigating the effects of defects and the effect of geometric anisotropy in stainless steel pipes: phased array ultrasonic test, SH-wave

Today, Phased Array Ultrasonic Testing (PAUT) is a suitable method for detecting defects in Non-destructive Testing (NDT). This simulation was done with a new method on a stainless steel pipe with a diameter of 500 mm and a length of 1,000 mm, and cracks were modeled on the external and internal surfaces and corrosion defects on the internal surface. Four probes with a characteristic of 2 MHz were used simultaneously, each probe having 64 elements. By increasing the number of probes and their elements, more accurate information about the defects is obtained, which makes it easier to detect the location and leads to a reduction of scattered signals and noise, which can detect even small size defects. Considering this important advantage, a new use of the method of increasing the number of probes in PAUT is reported in this study to detect defects, especially corrosion defects. The results of geometric anisotropy studies of group velocity and phase of horizontally polarized shear waves (SH-waves) for stainless steel pipe were presented. Due to the isotropic properties of the pipe material, the speed on the outer surface of the pipe in the direction of the cover is 40 m/s higher than the generatrix.

Data-driven collapse strength modelling for the screen pipes with internal corrosion defect based on finite element analysis and tree-based machine learning

Aiming to address the difficulties in predicting the collapse strength of sand control screen pipes with internal corrosion defects under the external pressure in offshore unconsolidated sandstone oil and gas reservoirs development, a parametric analysis model of a screen pipe with corrosion defects was established based on secondary development of ABAQUS by Python script, and was verified by the published experimental data. Then, the effect of corrosion defect and hole parameters on the collapse strength of the screen pipes was analyzed. Furthermore, a novel data-driven model with the gradient boosting regression tree (GBRT) method was used to explore and characterize the laws contained in the numerical simulation data based on a large volume of numerical simulation data. The results demonstrated that the proposed data-driven prediction model for the collapse strength of screen pipes exhibited a stable prediction average difference of 3.97% in the test set. And a large number of generalization practices based on data-driven prediction model indicated that corresponding corrosion parameter warning interval existed when the screen pipe design structure was determined, and when the corrosion defect size was greater than the warning interval, the collapse capacity of the screen pipe was considerably weakened. Moreover, the collapse strength was the lowest when the corrosion defect was located at the center of the screen pipe. And the collapse strength of the screen pipe gradually decreased with an increase of corrosion defects parameter and hole arrangement parameter. This study can provide a reference for evaluating the strength and establishing a safety-related warning mechanism of sand control screen pipes with corrosion defects.

Gas-Driven Endoscopic Robot for Visual Inspection of Corrosion Defects Inside Gas Pipelines

The internal inspection of corrosion in large natural gas pipelines is a fundamental task for the prevention of possible failures. Photos and videos provide direct proof of internal corrosion defects. However, the implementation of this technique is limited by fast robot motion and poor lighting conditions, with high-quality images being key to its success. In this work, we developed a natural gas-driven pipeline endoscopic robot (GDPER) for the visual inspection of the inner wall surfaces of pipelines. GDPER consists of driving, odometer, and vision modules connected by universal joints. It is designed to work in a 154 mm gas-pressurized pipeline up to a maximum of 6 MPa, allowing it to smoothly pass through bends and cross-ring welds at a maximum speed of 3 m/s using gas pressure driving. Test results have shown that HD MP4 video files can be obtained, and the location of defects on the pipelines can be detected by intelligent video image post-processing. The gas-driven function enables the survey of very long pipelines without impacting the transport of the pipage.

Finite element modeling of hydrogen atom diffusion and distribution at corrosion defect on aged pipelines transporting hydrogen

Repurposing existing natural gas pipelines for hydrogen transport has attracted wide interests. However, the corrosion defect present on these aged pipelines can affect hydrogen (H) atom accumulation, potentially causing hydrogen embrittlement. In this work, a finite element-based model was developed by coupling solid mechanics and H atom diffusion to investigate the distribution of H atoms at a corrosion defect on a steel pipe segment under applied longitudinal tensile strains. The applied strain causes local stress (both Mises stress and hydrostatic stress) and strain concentrations at the corrosion defect, affecting the H atom diffusion and distribution. In the absence of the tensile strain, the H atoms, once entering the interior of pipe, diffuse uniformly into the pipe body along the radial direction driven by a concentration gradient. When a strain is applied on the pipe, the H atom diffusion is driven by hydrostatic stress. The maximum H atom concentration exceeds the initial concentration of H atoms entering the steel pipe, indicating the H atom accumulation at the corrosion defect. The applied tensile strain also affects the location where the H atoms accumulate. For both internal and external corrosion defects, more H atoms will be concentrated at the defect center when the defect length reduces and the depth increases.

Automatic detection of internal corrosion defect in a natural gas gathering pipeline using improved YOLOv5 model

The detection of internal corrosion of the very long gas pipeline is a fundamental task for the prevention of possible failures, also one of the major challenges facing gas companies. Pipeline endoscopy based on the corrosion inspection method provides direct visual observation of defects, but the post-video analysis is time-consuming and not practical. In this work, we propose an improved YOLOv5 model-based software approach to automatically detect inner corrosion defects in nature gas-gathering pipelines. Video streaming of pipe interiors is provided by an endoscope robot. Sample augmentation strategies such as affine transformation and defect segmentation with background fusion are used to generate defect images and expand the data set. The region-based recursive localization method can be effectively optimized to improve the localization of corrosion regions.

Reliability evaluation of corroded pipeline under combined loadings based on back propagation neural network method

Corrosion is a common type of defect that causes failure of oil and gas pipelines. Pipelines often bear the combined loadings of axial compression force, bending moment and internal pressure in operation; therefore, it is of great significance to study the reliability of pipeline under different combined loadings. First, this work established a nonlinear finite element model of corroded pipeline for the typical internal corrosion defects of groove shape, and the reliability of the model and the accuracy of the finite element analysis method are verified. Then the burst pressure of pipeline under combined loadings is investigated. Second, this work established the BP network analysis and prediction model. The results of numerical simulation are used as samples to train the neural network. The prediction limit function value is output through the forward simulation function, which is compared with the objective function to judge whether the pipeline is reliable. Finally, back propagation neural network model calculated the reliability of pipeline under different working conditions combined with Monte Carlo method. The effects of load, corrosion depth, axial corrosion length, circumferential corrosion width and variation coefficient of parameters on pipeline reliability are analyzed. It is found that axial force and bending moment affect the reliability of corroded pipeline. Generally, the higher the combined loadings are, the lower the reliability is, but this law will be different due to the influence of corrosion parameters. In addition, the corrosion depth has the greatest influence on the reliability of corroded pipeline, followed by the corrosion width and the corrosion length. The coefficient of variation of corrosion depth has a great influence on the reliability of pipeline with high depth corrosion defect. These conclusions can provide references for the reliability evaluation of pipelines.

Experimental and numerical studies on collapse of subsea pipelines with interacting corrosion defects

The pipeline is prone to collapse under the combined external pressure and multiple corrosion defects. Experiments of the full-scale pipelines with longitudinally, circumferentially and diagonally dual defects are conducted, respectively. Finite element models are established to simulate the experimental process, and achieved good consistency. Then the influences of corrosion defect dimensions on the interaction are analyzed, and the corresponding critical spacing is determined. Moreover, the collapse modes of the pipeline under different defect forms are studied. The collapse mode of the pipeline with two external corrosion defects changes from U-shaped to ∞-shaped mode. However, the collapse modes for the pipeline with internal and external corrosion defects or two internal corrosion defects are irregular and the deformation is mainly concentrated on the region of corrosion defects. In addition, the critical pressure of the pipeline is sensitive to the defect distribution type (distributed axially, circumferentially, or diagonally along the pipeline, etc.). Finally, a formula for estimating the collapse pressure of the pipeline with dual corrosion defects is proposed. The comparison between the proposed formula and finite element results proves that this formula can be used for the collapse pressure of the pipeline with multiple corrosion defects in a slightly conservative manner.

CFRP Strengthening and Rehabilitation of Inner Corroded Steel Pipelines under External Pressure

The objective of this study was to investigate the performance of pipelines repaired with carbon-fibre-reinforced polymer (CFRP) under external pressure. The repaired pipeline experienced defects in terms of thinning of its local inner wall. The three-dimensional finite element method was used to analyse the collapse pressure of repaired pipes with internal corrosion defects. The traction–separation law and interlaminar damage criterion were applied to simulate the collapse process of repaired pipes. The results show that the collapse pressure of the composite-repaired pipe increased and the CFRP significantly reduced the strain in the defect region. It was observed that the ovality of the corrosion defect region was reduced and that the repair effectiveness mainly depended on the length, thickness, and interlayer cohesion.