Metal Loss Defects Research Articles

A Novel Magnetoelectric Composite Probe for Dynamic and Rapid Inspection of Minor Metal Loss Defects in Pipelines

A Novel Magnetoelectric Composite Probe for Dynamic and Rapid Inspection of Minor Metal Loss Defects in Pipelines

Plastic behavior and shakedown limit of defected pressurized pipe under cyclic bending moment

Pipelines subjected to thermal or mechanical loads may fail due to plastic strain accumulation which leads to ratcheting. In this research, cyclic plastic behavior and shakedown limit are investigated experimentally and numerically for a defected pressurized pipe under cyclic bending moment. In the numerical model, the combined isotropic/kinematic hardening model based on the Chaboche model is adopted to represent the cyclic plastic flow of the material. The hardening parameters are determined experimentally and used in the finite element (FE) model. A four-point bending test rig is manufactured to test a pressurized API 5L steel pipe under cyclic bending. An elliptical defect is created by machining to depict corrosion pits in pipes. The plastic strains are measured experimentally and the results are used to tune the parameters of the FE model. The shakedown limit of the defected pipe is determined numerically by tracking the critical points behavior and the results are verified experimentally. Furthermore, the plastic work dissipated energy (PWD) is estimated within the defective structure to study the behavior of the pipe. By running this compatible model, it is found that the yield and the shakedown limits are lowered by mean values of 55% and 25% respectively due to the presence of metal loss defect occupying almost half of the pipe thickness.

Probabilistic finite element-based reliability of corroded pipelines with interacting corrosion cluster defects

The random distribution of pitting corrosion defects in pipelines normally leads to interacting cluster defects that behave noticeably different from single metal loss defects. Generally, the probabilistic approaches employ explicit burst pressure limit states for corroded pipelines subjected to only internal pressure. However, a significant level of conservatism is typically associated with the probabilistic assessments of corroded pipelines using the closed-form explicit limit state functions, which presents considerable challenges in maintenance planning and risk management. Therefore, this paper proposes a pathway for developing efficient performance functions for the assessment of interacting pipeline corrosion clustering defects using probabilistic finite element-based reliability method. This seven-stage framework combines multiple uncertainty representation schemes to evaluate the probability of failure. The impact of the critical design variables such as the elastic and plastic material properties, corrosion features, and interacting cluster defect characterisations are identified to guide the burst pressure design, operations and maintenance optimisation. The employed surrogate-based active learning reliability approach yielded an efficient probability estimate at a lesser computational cost than the simulation-based reliability methods. The proposed framework reduces the conservatism and computational cost related with explicit burst pressure limit state functions for corroded pipelines and offers informed decision-making on risk and maintenance management.

Metal-loss defect depth inversion in oil and gas pipelines based on Bayesian regularisation neural network

Defect depth inversion is generally considered as a challenge in magnetic flux leakage (MFL) testing and evaluation because of its strong non-linearity and low prediction accuracy. Current inversion models focus on the inversion accuracy of specific datasets, ignoring consideration of the generalisation ability of inversion models under different conditions. In order to solve such problems, this paper proposes a novel pipeline defect inversion method based on a Bayesian regularisation neural network (BRNN) model. This method consists of two parts. Firstly, three domain features are extracted and a Boruta algorithm is introduced to reduce the feature dimension and obtain the best feature subset. Secondly, in order to approximate the complex non-linear relationship between multi-dimensional features and defect depth, a back-propagation neural network (BPNN) model based on Levenberg-Marquardt optimisation and a Bayesian learning algorithm is constructed. The model can effectively find a close global minimum and overcome the phenomena of overfitting and overtraining. In order to evaluate the performance of the proposed defect inversion method, a comparative experiment is carried out with other well-known inversion algorithms. The results obtained confirm that the inversion method can improve the prediction accuracy of defect depth. More importantly, this method enhances the generalisation ability of defect inversion problems with different sample sets.

A Novel Crack Quantification Method for Ultra-High-Definition Magnetic Flux Leakage Detection in Pipeline Inspection

Cracks that may cause pipeline cracking and leakage become the main risk of in-service pipelines after conventional metal loss defects have been detected. Therefore, it is imperative to develop ultra-high-definition magnetic flux leakage (MFL) detection for cracks. Due to the larger spatial sampling interval of conventional MFL inspections than the crack defect width, sparse sampling will result in problems such as missed detection of crack defects or insufficient signal sampling of crack defect MFL signals. To address the problem, this paper presents a detection topology in which the magnetic field signal is integrated first and then sampled, and it can effectively sample the leakage magnetic field of cracks. Furthermore, a magnetic field spatial integration (MFSI) method is proposed based on the magnetic dipole model, which develops an analytical solution for the depth quantification of crack defects. Using the multi-MFL spatial integral values under different lift offs, iterative equations are constructed, and the numerical solution for the width quantification of crack defects is provided. The finite element simulation and physical experiment are constructed. And, the results show that the proposed MFSI method can realize the quantification of crack size. When the crack defect aspect ratio is greater than 4, the quantization error of the crack depth and width does not exceed 0.7 mm and 0.1 mm, respectively. The robustness of the MFSI method for crack quantification is also discussed and verified. Moreover, based on theoretical analysis and simulation data, this paper concludes that the distribution of cracks MFL signal is width-insensitive, which would cause that classic MFL opening profile recognition methods for metal loss defects are no longer applicable to crack defects. Therefore, the proposed MFSI method is useful and meaningful for crack defect quantification in ultra-high-definition MFL detection.

A novel identification approach for corrosion and gouging of oil and gas pipelines based on low magnetisation level MFL inspection

The ability to characterise corrosion and gouging associated with metal loss and the identification of gouge type from metal loss defect types are two of the primary obstacles affecting magnetic flux leakage (MFL) internal inspection technology. Gouges in pipelines are not extraordinarily severe; however, the depth of corrosion increasing due to a certain corrosion rate can be quite serious. In this paper, a novel theoretical model combined with a new approach for the analysis of the signals that distinguish gouging and corrosion using a low magnetisation level is presented for MFL detection, since the traditional MFL internal detection tools are insensitive to stress characteristics in the case of saturation magnetisation. A two-stage finite element (FE) model for the prediction of magnetic flux leakage resulting from two types of defect is built. In the first stage, the stress distribution associated with gouging is obtained from a solid mechanics model and, in the second stage, the stress distribution is incorporated into a magnetic finite element model by mapping the stress levels to permeability. The possibility of detection and identification of corrosion and gouging using the MFL technique at low-level magnetisation was confirmed by experimentally comparing the characteristics of the MFL signals for each defect type.

Defect and Cluster Characterization: A Python-Based Plugin for Wellbore Intergrity Analysis

Abstract Over time, corrosion in a pipe causes metal loss which reduces the amount of stress a pipe can be exposed to before failure. A radial thickness measurement of the corroded pipe allows for a quantitative analysis of the pipe's strength by identifying areas of significant material loss. The effects of metal loss defects on a pipe compound when the defects are close enough to interact. Thus, the identification and characterization of interacting defects as a defect cluster is required when calculating the remaining pipe strength. A Python-based Techlog* wellbore software platform plugin was developed to provide an analytical workflow to detect and characterize the impact of metal loss defects and defect clusters on remaining pipe strength for downhole wellbore integrity applications. The developed plugin is a fully customizable workflow which can be adapted to any well integrity scenario and pipeline regulatory body standards such as ASME B31G, subsequently meeting clients' reporting requirements. The innovative workflow has additional potential to be ported to completely new applications utilizing various alternative downhole measurements.

An Automated Pipeline for Dynamic Detection of Sub-Surface Metal Loss Defects across Cold Thermography Images.

Utilising cooling stimulation as a thermal excitation means has demonstrated profound capabilities of detecting sub-surface metal loss using thermography. Previously, a prototype mechanism was introduced which accommodates a thermal camera and cooling source and operates in a reciprocating motion scanning the test piece while cold stimulation is in operation. Immediately after that, the camera registers the thermal evolution. However, thermal reflections, non-uniform stimulation and lateral heat diffusions will remain as undesirable phenomena preventing the effective observation of sub-surface defects. This becomes more challenging when there is no prior knowledge of the non-defective area in order to effectively distinguish between defective and non-defective areas. In this work, the previously automated acquisition and processing pipeline is re-designed and optimised for two purposes: 1—Through the previous work, the mentioned pipeline was used to analyse a specific area of the test piece surface in order to reconstruct the reference area and identify defects. In order to expand the application of this device over the entire test area, regardless of its extension, the pipeline is improved in which the final surface image is reconstructed by taking into account multiple segments of the test surface. The previously introduced pre-processing method of Dynamic Reference Reconstruction (DRR) is enhanced by using a more rigorous thresholding procedure. Principal Component Analysis (PCA) is then used in order for feature (DRR images) reduction. 2—The results of PCA on multiple segment images of the test surface revealed different ranges of intensities across each segment image. This potentially could cause mistaken interpretation of the defective and non-defective areas. An automated segmentation method based on Gaussian Mixture Model (GMM) is used to assist the expert user in more effective detection of the defective areas when the non-defective areas are uniformly characterised as background. The final results of GMM have shown not only the capability of accurately detecting subsurface metal loss as low as 37.5% but also the successful detection of defects that were either unidentifiable or invisible in either the original thermal images or their PCA transformed results.

Experiment and Simulation Analysis of the Pressure Carrying Capacity of X80 Pipe with Metal Loss Defect on the Girth Weld

In order to study the pressure carrying capacity of X80 pipe with metal loss defect on the girth weld the water-pressure blasting test of the pipe with metal loss defect was analyzed by experiment and finite element simulation. Based on this, the sensitivity analysis of the factors affecting the pressure carrying of the pipeline, such as the circular size, the axial size, and the depth of the metal loss defect, was carried out. The research results show that the circular size of the metal loss defect on the girth weld had little impact to the pressure carrying capacity of the pipe while it reduced with the increasing of the axial size and the depth of the metal loss defect.

Sub-surface metal loss defect detection using cold thermography and dynamic reference reconstruction (DRR)

Corrosion is considered a destructive phenomenon that affects almost all metals. Active infrared thermography is an online (no result delay) and non-intrusive (no process disruption) method of non-destructive testing (NDT), which has shown profound capabilities of detecting sub-surface metal loss. However, thermal reflections, non-uniform stimulation and lateral heat diffusion will remain as the most undesirable phenomena preventing the effective observation of sub-surface defects. This becomes more challenging when there is no a priori knowledge of the anomalies to effectively distinguish between defective and non-defective areas. In this work, cooling stimulation is considered as the thermal excitation mean as 1- a very few reports in this regard have been mentioned in the body of literature and 2- a dynamic setup was achieved that is found to be effective to minimise the possibility of disrupting reflections or artefacts registered by thermal camera similar to the case of using heating stimulation. A state-of-the-art prototype mechanism was manufactured. This equipment includes a carrier carrying a thermal camera and a cooling medium reservoir operating in reciprocating motion setup. This equipment is able to scan the test piece while cold stimulation is in operation, and immediately after that the camera registers the thermal evolution. An automated contrast enhancement pipeline using a variation of adaptive histogram equalisation (AHE) combined with principal component analysis (PCA) method was developed. The enhanced image results demonstrated the capability of accurately detecting sub-surface metal loss as low as 37.5% as well as an efficiently reconstructed reference (non-defective) area.

Corrosion Repair of Pipelines Using Modern Composite Materials Systems: A Numerical Performance Evaluation

Pipe corrosion is a frequent phenomenon, and if repairs are delayed it could lead to environmental damage. Drilling activities can expand only when sufficient surface transportation capacity for the produced fluids exists and thus good maintenance of the transportation system is important. Furthermore, the technology presented herein can be easily upgraded as a repair solution for surface casing section below the casing head, which have been repeatedly reported as being highly corroded for older wells. This paper presents the results of the research work carried out by the authors in order to evaluate the design methods of the modern composite material systems used to repair steel pipes carrying hydrocarbons upon which local metal loss defects (generated by corrosion and/or erosion processes) have been detected. The pipe repair technologies consisting of the application of composite material wraps (made of a polymeric matrix and reinforcing fabric) are perceived as being advantageous alternative solutions for substituting the conventional technologies, which require welding operations to be performed in the corroded pipe areas. The performance and the design methods of the composite repair systems have been investigated by evaluating the reinforcement effects (the restoration level of the damaged pipe mechanical strength) generated by the applied composite wraps as a function of their geometry and mechanical properties. To that purpose, numerical models based on finite elements (previously developed by the authors and certified by comparing them with the results of several experimental programs performed within our university) have been used. The calculation methods proposed in literature (among which a method previously proposed by the authors) to define the composite wrap dimensions (thickness and length) for a given pipe have been compared to the numerical results in order to select the most adequate solution for the design of the composite repair system. The influence in the design process of the defect orientation and of its width has also been investigated.

Mapping of ultrasonic thickness measurements using laser grid projection and image processing

A three-dimensional surface mapping method for ultrasonic thickness measurements is proposed to enable the dimensions and positions of measured values obtained by the conventional ultrasonic thickness gauges and flaw detectors on curved surfaces to be determined. The proposed system consists of a laser pattern generator and image processing methods. The laser grid produced by the pattern generator is projected onto the surface of the item to be inspected, mathematical relationships are developed to localise the grid nodes on the inspection surface and images are then captured using a complementary metal-oxide semiconductor (CMOS) camera. An image processing algorithm is developed to plot the scanned surface. The measurements performed using a thickness gauge are correlated with the plotted surface, which will enable thickness mapping. The experiments were carried out on a pipe with an artificial metal loss defect and the results showed that the developed method can accurately locate measured thickness values on a three-dimensional plotted surface.

Comparative Study of three non-destructive techniques for metal loss inspection in pipe walls

Identifying and describing metal loss defects in pipe walls is an indispensable task in transporting operations, this abnormal condition mainly appears as a result of corrosion and gouging. These metal losses can lead the pipeline to unsafe conditions originating leaks, rupture of the structure and associated hazards. In this work is presented a comparative study to assess the capabilities of detecting and describing the metal loss in a pipe wall based on three non-destructive techniques: Magnetic Flux Leakage, Eddy Current Testing, and Guided Waves. These are compared by revising their physical principle and presenting a brief review of results obtained in metal loss inspection by considering some criteria as its sensitivity, depth of penetration, the range of inspection, and implementation easiness. Finally, the discussion is focused on of establishing which technique is most adequate for the inspection according to some characteristics of the metal loss defect.

ПРОГНОЗИРОВАНИЕ РАЗВИТИЯ ДЕФЕКТОВ ПОТЕРИ МЕТАЛЛА НА МАГИСТРАЛЬНЫХ ТРУБОПРОВОДАХ НА ОСНОВАНИИ МАТЕМАТИЧЕСКОЙ МОДЕЛИ, РЕАЛИЗУЕМОЙ В ПРОГРАММЕ ANSYS

ПРОГНОЗИРОВАНИЕ РАЗВИТИЯ ДЕФЕКТОВ ПОТЕРИ МЕТАЛЛА НА МАГИСТРАЛЬНЫХ ТРУБОПРОВОДАХ НА ОСНОВАНИИ МАТЕМАТИЧЕСКОЙ МОДЕЛИ, РЕАЛИЗУЕМОЙ В ПРОГРАММЕ ANSYS

Investigation of the stress-strain state of the pipeline in the area of single dent and dent interacting with metal loss defect

Investigation of the stress-strain state of the pipeline in the area of single dent and dent interacting with metal loss defect

Solving the Inverse Geometric Problem of Magnetostatics for Corrosion Defects with Allowance for Nonlinear Properties of Ferromagnet

A method is proposed for solving the inverse problem of magnetostatics with allowance for a nonlinear dependence of the relative magnetic permeability of a ferromagnet on the applied external field. The method has been investigated for metal loss defects located on the ferromagnetic-plate side opposite to magnetic transducers, without imposing any conditions on defect shape. The ferromagnetic plate is magnetized in the direction of the abscissa axis; the dependence of the magnetic induction of metal on the applied external magnetic field corresponds to a nonlinear segment of the magnetization curve. The problem has been solved for the three-dimensional case. Defects were simulated and the direct problem was solved with software developed by the authors in FORTRAN language. The program for constructing lines of force and solving the inverse problem of reconstructing magnetic field components was written using the Scilab package of applied mathematical programs.

Solving the Inverse Geometric Problem of Magnetostatics for Corrosion Defects

A method is proposed for solving the inverse problem of magnetostatics. The method has been investigated for metal-loss defects located on the side of a ferromagnetic plate opposite to magnetic transducers, without imposing any conditions on defect shape. The method is illustrated by numerical simulation. The ferromagnetic plate is magnetized in the direction of the abscissa axis; the dependence of the magnetic induction of metal on the applied external magnetic field corresponds to the linear segment of the magnetization curve. This configuration of defects and magnetizing system is typical, for example, of in-tube inspection problems. The problem is solved for the two-dimensional linear case. The applicability limits of the method are considered. The defects were simulated and the direct problem was solved using the FEMM software package. The program for constructing lines of force and solving the inverse problem of reconstructing magnetic field components has been written in the Scilab package of applied mathematical programs.

An experimental investigation of the effect of defect shape and orientation on the burst pressure of pressurised pipes

The burst pressure of commonly used ductile steel pipes in oil and gas industries, i.e. X52 and X60, is measured under internal pressure loading. The pipes were machined with circular and boxed defects at different orientations to simulate actual metal loss defects. Defect shapes and orientations were investigated in detail to study how they affect the failure behaviour of interacting defects. The experimental burst pressure results were compared with those obtained using existing analytical methods from Design Codes. Comparison of the results showed conservatism in the existing analytical methods which may potentially lead to unnecessary plant shutdowns and pipe repairs. The outcome of the experimental tests revealed that the shapes of the defects have very small influence on the defect interaction behaviour. The burst tests interestingly showed that the defect orientation has an important effect on defect interaction. Defects oriented in the hoop and diagonal directions showed no defect interaction even when spaced by a distance of one wall thickness, while defects oriented in the longitudinal directions showed that defects interact even when the spacing is up to six wall thickness but the interaction fades away for defects spaced at longer distances.

Corrosion risk-based subsea pipeline design

Subsea oil and gas pipelines are commonly designed with 3–6 mm internal corrosion allowance added to pipeline wall thickness often without pragmatic thought. The corrosion allowance is neither calculated with due diligence to localized effect nor address the uncertainty of corrosion input variables. Since inspection and monitoring are difficult and expensive task for subsea pipeline, the design could be made more robust if potential metal loss defect caused by internal corrosion were properly quantified and consolidated in the design. This paper exactly did that by characterizing all sorts of uncertainty related to metal loss defect and incorporating them in the design. Based on calculated failure probability for metal loss defect, design variables are revisited to ensure recommended target safety level is meet/achieved. Hence, the risk-based design is also optimized since under or overconservative design is avoided. As internal corrosion defect is dominant mode of failure other corrosion related failure probabilities, which could be integrated using FTA, are not considered in this study. One representative failure incident's basic variables have been excavated from Monte Carlo simulation to develop finite element model to assess the mechanical integrity of the pipeline when it fails according to burst models. Recommendations are provided where appropriate.

Experimental Investigation and Simulation of Magnetic Flux Leakage from Metal Loss Defects

Magnetic flux leakage (MFL) principle is widely used in detecting defects in cross-country pipelines. The tools based on the MFL techniques termed as instrumented pipeline inspection gauge (IPIG) are frequently used as per statutory requirement. The tool identifies the location of metal loss and also characterizes the size of metal loss defects in terms of length, width along circumference and depth in terms of percentage loss. Tool velocity in terms of frequency of data acquisition is important parameter whose effect on the MFL signal and on the defect quantification has been studied. Operation of linear pull through rig under various combinations of MFL tool parameters such as velocity, frequency and spatial sampling has been developed. A set of experiments by varying velocity from 0.25 to 2 m/s keeping frequency constant at 450 Hz have been carried out. MFL signals obtained from all known defects have been analyzed for its nature and quantifying the dimension of defect. The effect of velocity on individual dimensions of the defect has been studied in this work. Within the limitation of the experiments carried out, the present work indicates that smaller defects cannot be reported with better accuracy. Also, the velocity is seen to have a significant effect in characterizing the length of the defect using IPIG especially for defects of larger area.