Corrosion Rate Model Research Articles

Research on Wellbore Integrity Evaluation Model of CO2 Enhanced Composite Fracturing

CO2 injection composite fracturing is an effective method for shale oil and gas well development. The downhole casing is prone to uniform corrosion, pitting, perforation, and even corrosion fracture in the CO2 environment. Therefore, it is particularly important to reveal the physical characteristics of CO2 under actual geological conditions and the impact of CO2 corrosion on the performance of casing. A mathematical model for the temperature and pressure field of CO2 in the wellbore under fracturing conditions is established in this paper, and the temperature and pressure distribution along the depth of the well is calculated. By optimizing the CO2 state equation and using the S-W equation, Lee model, and RK model to calculate the CO2 density, viscosity and compression factor, respectively, the phase distribution pattern of CO2 along the actual wellbore is obtained. Through CO2 corrosion tests on the casing, the influence of temperature and CO2 concentration on the corrosion rate of the casing is clarified. The peak corrosion rate of Q125 steel corresponds to 80 °C, and the corrosion rate increases with the increase in CO2 concentration. Finally, a prediction model for the uniform corrosion rate of casing under different temperatures and CO2 concentration conditions is obtained, which can provide technical support for the design of CO2-enhanced fracturing technology.

Assessing sulfate-reducing bacteria influence on oilfield safety: Hydrogen sulfide emission and pipeline corrosion failure

With the further development of oilfield, excessive sulfate-reducing bacteria (SRB) has intensified odors and increased pipeline leakage incidents. Accurate predictive models of H2S emission and pipeline corrosion based on SRB content are essential for safety. This study analyzed the correlation between sulfide content and SRB content at different nodes in the injection-production system of Daqing Oilfield, and characterized the pipeline corrosion products using scanning electron microscopy (SEM), X-ray diffraction (XRD), and stereo microscope. Corrosion rates were investigated through 18 sets of orthogonal experiments, considering factors such as SRB, temperature, pH, liquid flow rate, CO2 partial pressure, and H2S partial pressure, and the main controlling factors of corrosion were identified. Finally, the risk models for H2S emission and corrosion rate based on SRB content were established under on-site operating conditions. The results show that a significantly positive correlated between SRB and sulfide content at different nodes, with the highest levels observed at the settling tank, indicating the highest risk of H2S emission. SRB contributed to corrosion in both water injection and oil collection pipelines, with more serious corrosion in the water injection pipeline. SRB and pH were identified as the main factors influencing corrosion rate. The H2S emission prediction model based on the correlation of SRB and sulfide was reliable, with an accuracy exceeding 90 % compared to the measured results. Additionally, the corrosion rate model for pipelines, related to SRB content, had an error of less than 7 %. To minimize risks, it is recommended to maintain a low risk environment in the injection-production system by sterilization and increasing the pH of water. This study has significant theoretical importance for ensuring the safe operation of injection-production systems.

Prediction model for corrosion rate of low-alloy steels under atmospheric conditions using machine learning algorithms

Prediction model for corrosion rate of low-alloy steels under atmospheric conditions using machine learning algorithms

Reliability analysis of gas pipelines under global bending and thermal loadings considering a high chloride ion environment

The long-distance gas pipelines inevitably experience global bending deformation due to the ground movements. Meanwhile, a harsh environment where both the temperature may change drastically and the high chloride ion soil condition possibly causes more severe corrosion on the pipelines, could pose a significant challenge to pipeline safety. It is very crucial to ensure gas pipeline safety and durability in the energy transportation industry. Therefore, this study aims to systematically investigate the failure pressure of corroded gas pipelines under the combined effects of global bending and temperature difference. Considering gas pipelines potentially exposed to soil conditions with different contents of sodium chloride (NaCl), five corrosion rate models were for the first time employed to carry out reliability-based lifetime prediction analysis. The results show that compared to the case without global bending and temperature difference, the service life of gas pipelines can be reduced by 14 % in the case of global bending strain of 0.25 % and temperature difference of −40 °C. As for the corrosion rate model, the Model 4 plays a strongly adverse role in the service life of gas pipelines. Furthermore, parametric sensitivity analysis indicates that apart from the working pressure, initial corrosion depth and the radial corrosion rate are the two more influential factors in affecting the service life of gas pipelines.

Corrosion Rate Analysis and Prediction of the Remaining Life of the Research Vessel to Improve Ship Safety Aspects

<p>Corrosion is a major concern in the marine industry, compromising the safety and integrity of ships. This paper presents a corrosion rate analysis and prediction of the remaining life of the Baruna Jaya IV research vessel using non-destructive testing (NDT) ultrasonic testing to improve ship safety aspects. The NDT ultrasonic testing was conducted on the ship's hull to evaluate the thickness and detect any hidden corrosion. The results were used to develop a corrosion rate model and predict the remaining life of the ship using a probabilistic model. The study found that the corrosion rate of the ship was high, and the remaining life of the ship was estimated to be less than five years. The study’s findings can be used to develop a maintenance and repair strategy to reduce corrosion and improve the safety of the Baruna Jaya IV research vessel.</p>

Empirical Model for Predicting Corrosion Under Insulation Considering the Effects of Temperature, Salinity, and Water Content

Corrosion under insulation (CUI) is one of the increasing issues in industries such as oil refineries and petrochemical plants. For preventing accident and reducing the inspection load caused by CUI, the prediction model for CUI has attracted increasing attention. In this study, to construct a prediction model for the corrosion rate of CUI (CUI rate), the effects of water content in the insulation material, salinity, and temperature on the CUI rate were evaluated with a corrosion test simulating a CUI environment. Analysis of the atmospheric corrosion monitoring sensor current showed that the CUI rate increased as the water content increased, promoting the formation of the water-thin film at the interface of insulation and carbon steel. Maxima of the CUI rate were observed for salinity and temperature. Salinity increased the electrical conductivity of the water-thin film and promoted the corrosion reaction, and over a certain salinity, the water-thin film became thicker and the CUI rate decreased due to the rate-determining step in oxygen diffusion. Over a certain temperature, the CUI rate decreased due to the evaporation of the water-thin film and a decrease in dissolved oxygen. We constructed the prediction model for the CUI rate with a coefficient of determination of 0.87 by multiple regression analysis using the obtained test data.

Investigation into main controlling factors and prediction model of L245NS steel corrosion rate in CO2–O2–SO2–H2S–H2O environment

Multi-component thermal fluid flooding is an increasingly mature technology for heavy oil recovery. However, the production of associated gas containing highly corrosive CO2/O2/SO2/H2S/H2O impurities can lead to corrosion and perforation failure in gathering pipelines. This study systematically investigated the effects of temperature/CO2/O2/SO2/H2S on L245NS steel corrosion in a CO2–O2–SO2–H2S–H2O environment and analyzed the correlation between these factors and corrosion rate. The corrosion behavior of L245NS steel in a CO2–O2–SO2–H2S–H2O environment was investigated through weight-loss experiments and surface characterization techniques. An empirical model for predicting the corrosion rate in this environment was established based on the obtained results. The results indicated that the sequence of importance for corrosion rate was as follows: O2 (0.8181) > H2S (0.7511) > Temperature (0.7491) > CO2 (0.7312) > SO2 (0.7017). Surface characterization revealed that the predominant corrosion products were FeCO3, FeS2, FeS, Fe(OH)3, FeOOH, Fe3O4, Fe2O3, elemental sulfur and FeSO4·4H2O. The corrosion reaction involved CO2/O2/SO2/H2S while synergistic reactions between SO2–O2 and SO2–H2S further promoted corrosion. Finally, an empirical model for the corrosion rate of L245NS steel in a CO2–O2–SO2–H2S–H2O environment was established. The fitting error ranged from 0.03% to 8.99%, and the verification error ranged from 2.62% to 14.83%. This model can provide a valuable reference for preventing and controlling pipeline corrosion.

Probabilistic Analysis of Corrosion Rates and Degradation of Weathering Steel Bridges

AbstractCorrosion of weathering steels in outdoor conditions has been observed since their pioneering applications in construction in the 1960s. Changing environmental conditions such as decreasing SO2 concentration and changes in temperature and relative air humidity affect the formation and development of a protective layer of corrosion products on the surface of these steels. The study compares the long‐term corrosion rates of weathering steels according to EN ISO 9224 with the measured rates for various environments in the Czech Republic and abroad, with a focus on sites with high concentrations of chlorides from de‐icing salts. When considering related uncertainties, the corrosion rate models provide estimates in a wide range, and in‐situ measurements can significantly improve corrosion loss predictions. The reliability of bridges made of weathering steels with a well‐developed protective layer is insignificantly affected by corrosion. However, low reliability levels may be experienced in critical details where for example leakage may damage the protective layer of patina.

Modeling of Corrosion Rate Under Two Phase Flow in Horizontal Pipe Using Neural Network

The present study develops an artificial neural network (ANN) to model an analysis and a simulation of the correlation between the average corrosion rate carbon steel and the effective parameter Reynolds number (Re), water concentration (Wc) % temperature (T o) with constant of PH 7 . The water, produced fom oil in Kirkuk oil field in Iraq from well no. k184-Depth2200ft., has been used as a corrosive media and specimen area (400 mm2) for the materials that were used as low carbon steel pipe. The pipes are supplied by Doura Refinery . The used flow system is all made of Q.V.F glass, and the circulation of the two –phase (liquid – liquid ) is affected using a Q.V.F pump .The input parameters of the model consists of Reynolds number , water concentration and temperature. The output is average corrosion rate .The performance of the two training algorithms, gradient descent with momentum and Levenberg-Marquardt, are compared to select the most suitable training algorithm for corrosion rate model. The model can be used to calculate the average corrosion rate properties of carbon steel alloy as functions of Reynolds number, water concentration and temperature. Accordingly, the combined influence of these effective parameters and the average corrosion rate is simulated. The results show that the corrosion rate increases with the increase of temperature, Reynolds number and the increase of water concentration.

A study on static properties of high-performance steel after corrosion damage

This paper experimentally investigates the mechanical properties of high-performance steel (690 MPa) under different corrosion degrees. The tensile specimens are examined by indoor salt spray accelerated corrosion tests with varying durations. Tensile tests are performed on the corroded specimens to obtain the corrosion kinetics (corrosion rate) model and residual mechanical properties under different degrees of corrosion, and the correlations between residual mechanical properties and corrosion weight loss rate are discussed. In addition, the paper will adopt Q235 steel as the control to compare the difference in corrosion characteristics between conventional-strength steel and the new high-performance steel under the same corrosion conditions and to compare their corrosion kinetics curves. The paper will establish a new constitutive model for high-performance steel and calibrate the relevant parameters. A new constitutive model was proposed based on the modification of Ramberg-Osgood model. On this basis, the paper will obtain a prediction expression of constitutive parameters considering the degree of corrosion damage. It is found that that the proposed corrosion model is suitable for the new high-performance steel under atmospheric corrosion.

Research on Corrosion Rate Model of Reinforcement in Concrete under Chloride Ion Environments

In a chloride environment, taking reinforced concrete structures as the research object, the corrosion rate of reinforcement determines its corrosion expansion because multiple coupling parameters will affect the corrosion rate of reinforcement, which is extremely difficult to effectively predict. In this paper, 144 sets of experimental data were collected and sorted out by reading the relevant literature, and six empirical models for predicting the corrosion rate of steel bars were compared and analyzed based on these experimental data. Based on the investigations, a new empirical model is proposed for predicting the corrosion rate of reinforcement, and the relevant influencing factors are considered in the new model. By comparing the 144 sets of experimental data and 90 experimental data for this paper, the new prediction model can well predict the corrosion rate of reinforcement. Furthermore, the time variability of the new prediction model is verified. The probability distribution characteristics of seven prediction models are obtained through model error analysis, which provides a theoretical basis for the next step of concrete cover cracking and reliability analysis.

ФУНКЦИЯ НАДЕЖНОСТИ ПРЕДВАРИТЕЛЬНО НАПРЯЖЕННОЙ КОРРОДИРОВАННОЙ ЖЕЛЕЗОБЕТОННОЙ БАЛКИ ПРИ НЕЛИНЕЙНОМ РАСПРОСТРАНЕНИИ КОРРОЗИИ

The paper considers the limit state function in the context of reliability analysis of corroded beams. Methods for determining the ultimate load limit for corroded beams are discussed. Various approaches to the determination of the limit state function are considered, including those based on statistical data on corrosion and modelling of stresses in a reinforced concrete beam. A general reliability assessment model for reinforced concrete structures should include corrosion propagation. Most previous studies have focused on one-dimensional diffusion problems with an assumed constant corrosion rate. A nonlinear corrosion rate model, unlike linear models, considers the corrosion current density not constant over the service life of a reinforced concrete structure. An approach to reliability analysis together with a nonlinear corrosion growth model is developed. In this paper, the main problems related to reliability under a nonlinear model of prestressed reinforcement rope corrosion of reinforced concrete beams are discussed. A function for the reduction of reinforcing bar diameter from time is presented. Sensitivity analysis is performed to determine the effect of corrosion growth parameters on the reliability index of reinforced concrete T-beam. The nonlinear corrosion growth model, together with other relevant probabilistic models used to describe random variables, was applied to analyze the reliability of a reinforced concrete crane girder. The expression of corrosion current density shows that the corrosion rate increases exponentially as the value of the design parameter of the model increases. To further evaluate the effect of the proposed time corrosion growth model on the reliability of reinforced concrete beam, two specific cases are considered. The first one is with fixed corrosion current density, and the second one is with fixed corrosion growth at a given time.

Study on wind-induced response of corroded transmission tower

Transmission towers in heavily polluted areas and coastal areas are prone to corrosion, resulting in the decline of wind resistance capacity of the structure. In order to study the wind-induced effect of transmission towers under strong corrosive environment, the finite element model of transmission towers with different service life is established by using the corrosion rate model of galvanized coating and the corrosion depth model of steel provided by the specification. The attenuation characteristics of structural natural vibration characteristics are studied, and the variation of displacement, acceleration and stress of tower body under strong wind are analysed. The results show that with the increase of service life, the structural vibration mode changes and the torsional frequency decays fastest, the stress of main members increases gradually. When the service life reaches 50 years, the extreme displacement at tower top and normal stress of member at 95.5 m exceeds limit, making the tower being destroyed.

A time-dependent corrosion wastage model for the partial structure of mobile offshore platforms

ABSTRACT Offshore mobile platforms are important facilities for the development of deep-water offshore oil and gas resources. In life-cycle safety assessment of offshore mobile platforms, there remains a lack of effective structural corrosion models to guide design evaluation. From a large amount of corrosion data provided by the China Classification Society regarding the operation of offshore mobile platforms, relevant data were statistically analysed, and available corrosion data were selected for analysis and comparison. By analysing the experimental data of offshore mobile platforms, it was verified that the corrosion rate of local components of offshore mobile platforms follows the Weibull distribution, which is consistent with Paik's verification that the corrosion rate of local components of marine mobile platforms follows Weibull distribution. Therefore, the corrosion evolution model of local components of offshore mobile platforms was established by referring to the ship corrosion rate model.

Machine learning approach to AC corrosion assessment under cathodic protection

AbstractData mining was introduced and 178 sets of alternating current (AC) corrosion data were collected from published data and our research group. The AC current density (JAC), direct current (DC), current density (JDC), the ratio of AC/DC current density (JAC/JDC), and cathodic protection potential (IR‐free potential, EIR‐free) were defined as the input feature and the priority of feature subset was ranked as (JAC, JDC) > (JDC, JAC/JDC) > (JAC, EIR‐free) >JAC > (JAC/JDC, EIR‐free) > JAC/JDC. Then, based on the different feature subsets, the AC corrosion rate model was established by the random forest algorithm, and the generalization ability of the model was verified on the test data respectively. Finally, the mapping relationship between AC, DC parameters, and corrosion rates was presented and the limiting values of (JAC, JDC) and (JDC, JAC/JDC) were given.

Integrated Design and Analysis of Corrosion Rate Model on Tubular Pipe of Oil and Gas Production Well

Corrosion occurrence in the oil and gas production system is an example of an unavoidable problem. This problem is caused by the presence of water and corrosive material fraction along with the produced hydrocarbon. On the way from the reservoir to the surface, the mixture between water fraction and the corrosive substance might adhere to the wall of conduit steel pipe (e.g. tubing, casing, and flowline) and can lead to corrosion on the wall. The corrosion problem can have a major impact on the economics of the production because the cost of production equipment is relatively expensive and workover operation is very costly. Therefore, planning and mitigation for a better production system need to be performed, so that the rate of corrosion can be controlled, and its economic impacts can be minimized. The purpose of this study was to create an integrated model of the corrosion rate calculation on the tubing by the Petroleum Engineering Study Program of Bandung Institute of Technology (ITB). Several terms related to the production process were considered in this model: the characteristics of the produced fluid, flow regimes, pressure and temperature conditions along the tubing, the trajectory of the well, the type of tubing material used, and the use of inhibitors. The model was developed from the model developed by C. de Waard, Liane Smith, and Mike Billingham. The corrosion rate calculation model was then validated using field data and the results were compared with the result from industrial commercial software, Electronic Corrosion Engineer (ECE®). The corrosion rate calculation model were able to predict the rate of corrosion in oil and gas wells accurately. A software-based system was created based on this integrated and accurate proven model. By using this software, the production system can be simulated and tested for various conditions, and then the result can be compared with each other to obtain the optimum fluid production rate with minimum corrosion rate. In addition, this software is capable to determine the most suitable tubing material which will be used in a given production environment and condition.

Simulation of CO2 Corrosion of Carbon Steel in High Pressure and High Temperature Environment (HPHT)

In HPHT environments, the mechanism of CO2 corrosion faces a challenge as an effect of chemical-physical reactions on the metal surface. The presence of other elements in the CO2 system complicates corrosion behavior. To provide a realistic mechanism for corrosion process, some corrosion prediction models have developed software using fundamental theories such as electrochemical reactions and thermodynamics theories. Existing methods to predict corrosion rate models in HPHT environments have shown reasonable results. This paper reviews software of corrosion predictions which calculate corrosion rate based on mechanistic theories that study effects of H2S, acetic acid (HAc) concentrations, shear stress, pH in temperature from 25oC – 100oC and pressure from 1–10 bar. From the simulation, corrosion rate increased significantly in the high pressure CO2 environment. Corrosion rate at pH 4 increased to 30 mm/y at a temperature from 15oC to 90oC. While at pH 8 corrosion rate reached 4 mm/y. This lower corrosion rate indicated a tendency for deposits formation at higher pH. Corrosion rate behaves in a different mechanism at high temperatures. The corrosion rate decreased to 4 mm/y when the temperature increased to more than 90oC. Effects H2S gas and HAc were identified to increase corrosion rate. Both elements provide extra cathodic reaction and create limiting current density in the cathodic reaction process based on polarization sweep models. However, the polarization graph calculated using corrosion models could not display passive behavior in the anodic polarization process. Thus, further, improvement should be considered. From the data calculation, it can be shown that corrosion prediction software can predict corrosion rate in HPHT conditions.

Optimal Maintenance Policy for Corroded Oil and Gas Pipelines using Markov Decision Processes

This paper presents a novel approach to determine optimal maintenance policies for degraded oil and gas pipelines due to internal pitting corrosion. This approach builds a bridge between Markov process-based corrosion rate models and Markov decision processes (MDP). This bridging allows for the consideration of both short-term and long-term costs for optimal pipeline maintenance operations. To implement MDP, probability transition matrices are estimated to move from one degradation state to the next in the pipeline degradation Markov processes. A case study is also implemented with four pipeline failure modes (i.e., safe, small leak, large leak, and rupture). And four maintenance actions (i.e. do nothing, adding corrosion inhibitors, pigging, and replacement) are considered by assuming perfect pipeline inspections. Monte Carlo simulation is performed on 10,000 initial pits using the selected corrosion models and assumed maintenance and failure costs to determine an optimal maintenance policy.

Corrosion Prediction Models in the Reinforcement of Concrete Structures of Offshore Wind Farms

The growth of offshore wind farms (OWF’s) is expected to be significant. Reducing operation and maintenance (O&M) costs will be important to ensure its development. The foundation is the most important structural element, with concrete as its main constituent. With concrete structures, particular attention must be paid to corrosion of embedded steel especially in marine environments, as poor maintenance management can have significant economic and structural safety consequences. This article presents a systematic analysis of prevalent corrosion prediction models and the subsequent development of a tool for estimating the diameter loss in the reinforcement of concrete structures in OWFs. For validation, the tool methodology is applied to 32 real cases to evaluate the difference between the calculated and the real diameter loss. The results indicate that the combination between the chloride diffusion model of the Spanish code on structural concrete (EHE-08) and the corrosion rate model of Li (2004) guarantees favourable diameter loss prediction results. The ability to rapidly calculate the diameter loss of reinforcement in concrete structural elements as a function of time, provides OWF operators with a valuable tool for the planning of maintenance strategies and cost optimisation.

Macrocell Corrosion of Steel in Concrete under Carbonation, Internal Chloride Admixing and Accelerated Chloride Penetration Conditions.

Steel corrosion has become the main reason for the deterioration of reinforced concrete structures. Due to the heterogeneity of concrete and the spatial variation of environmental conditions, macrocell corrosion is often formed by localized corrosion, which is more detrimental if the anode is supported by large numbers of cathodes. The macrocell corrosion caused by concrete carbonation has been seldom studied. Furthermore, the influence of geometrical conditions on cathode-controlled corrosion in the chloride environment needs to be further clarified. In this work, the macrocell corrosion of steel embedded in concrete specimens exposed to accelerated carbonation, chloride contamination, and chloride penetration is studied using a modified ASTM G109 method. Concrete specimens with various binder types, geometrical parameters (i.e., concrete cover thickness and the diameter of embedded steel), and boundary conditions were tested. A simplified mathematical model for the prediction of the steel corrosion rate was developed considering two-dimensional oxygen diffusion. The results showed that, at the same level of anodic potential drops, the corrosion current rate in chloride-induced corrosion is higher than that of carbonation-induced corrosion. Chloride contamination is less detrimental to concrete incorporated with slag and pulverized fly ash than it is to pure ordinary Portland cement (OPC), likely due to enhanced chloride binding capacity. The results also indicated that the model considering two-dimensional diffusion can accurately predict the cathodic reaction process on corroded steel bars, which provides a theoretical basis for considering the correction coefficient of steel bar position in the establishment of a steel bar corrosion rate model.