Film former corrosion inhibitors for oil and gas pipelines - A technical review

Askari, Mehdi; Aliofkhazraei, M.; Ghaffari, Sanaz; Hajizadeh, Amirhossein

doi:10.1016/j.jngse.2018.07.025

Cited by 151 publications

(49 citation statements)

References 60 publications

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“…They proposed a non-deterministic artificial intelligence method that estimated the corrosion at different sections of the pipeline. Many other investigations on the use of artificial intelligence in the estimation of the corrosion defect growth of carbon steel materials used for pipelines also abound in the literature [14][15][16][17][18][19][20][21][22][23]. Notable among these studied is the work on the fatigue crack growth where ANN was employed to investigate the corrosion-fatigue crack of a dual phase steel at different stress intensities inconsideration of the martensite content of 32-76% [23].…”

Section: Introductionmentioning

confidence: 99%

“…Notable among these studied is the work on the fatigue crack growth where ANN was employed to investigate the corrosion-fatigue crack of a dual phase steel at different stress intensities inconsideration of the martensite content of 32-76% [23]. Other researchers [17] also estimated the corrosion-fatigue growth with ANN. However, these authors concentrated on the length of crack and cyclic loading time of the pipeline during operation.…”

Section: Introductionmentioning

confidence: 99%

“…However, these authors concentrated on the length of crack and cyclic loading time of the pipeline during operation. Other research papers [14][15][16][17][18] also used machine learning strategies for establishing the corrosion defect growth of pipelines in varying conditions of operations.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Data-Driven Machine Learning Approach for Corrosion Risk Assessment—A Comparative Study

Ossai

2019

BDCC

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Understanding the corrosion risk of a pipeline is vital for maintaining health, safety and the environment. This study implemented a data-driven machine learning approach that relied on Principal Component Analysis (PCA), Particle Swarm Optimization (PSO), Feed-Forward Artificial Neural Network (FFANN), Gradient Boosting Machine (GBM), Random Forest (RF) and Deep Neural Network (DNN) to estimate the corrosion defect depth growth of aged pipelines. By modifying the hyperparameters of the FFANN algorithm with PSO and using PCA to transform the operating variables of the pipelines, different Machine Learning (ML) models were developed and tested for the X52 grade of pipeline. A comparative analysis of the computational accuracy of the corrosion defect growth was estimated for the PCA transformed and non-transformed parametric values of the training data to know the influence of the PCA transformation on the accuracy of the models. The result of the analysis showed that the ML modelling with PCA transformed data has an accuracy that is 3.52 to 5.32 times better than those carried out without PCA transformation. Again, the PCA transformed GBM model was found to have the best modeling accuracy amongst the tested algorithms; hence, it was used for computing the future corrosion defect depth growth of the pipelines. This helped to compute the corrosion risks using the failure probabilities at different lifecycle phases of the asset. The excerpts from the results of this study indicate that my technique is vital for the prognostic health monitoring of pipelines because it will provide information for maintenance and inspection planning.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Data-Driven Machine Learning Approach for Corrosion Risk Assessment—A Comparative Study

Ossai

2019

BDCC

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“…Inhibitors used in oil fields are mainly composed of compounds containing quartenized nitrogen atoms, amides, amines, imidazolines, long-chain carboxylic acids, ethoxylates, multifunctional low molecular weight polymers, sulfonates, phosphates and their esters, pyridine salts [5]. Phosphates of metals [6], various polymeric ethers of phosphates [7], as well as ethers of phenols, ethoxylated, propoxylated, butoxylated alcohols [8][9][10], phosphonic acids and their salts [11], thio-and dithiophosphonates [12] are the most common among organophosphate corrosion inhibitors.…”

Section: Introductionmentioning

confidence: 99%

New Sintanyl Phosphonates for Protection of Oil and Gas Pipelines from Steel Corrosion

Nikitin¹,

Shumatbaev²,

Terenzhev³

et al. 2019

Civ Eng J

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Many corrosion inhibitors are economically disadvantageous or toxic to the environment. Additionally, there are certain requirements for corrosion inhibitors. Therefore, the development of new corrosion inhibitors is one of the important problems in the oil-producing and oil-refining industry. The purpose of this work is the synthesis of new corrosion inhibitors with high inhibitory activity, the establishment of the structure of the compounds obtained and the determination of the anti-corrosion effect with respect to aggressive media. This paper presents the results of research on the development of new iron corrosion inhibitors. New α-aminophosphonates were synthesized based on the Kabachnik-Fields reaction. Formalin, morpholine, phosphite containing residues of industrial non-ionic surfactants - syntanols as radicals were used as a raw material. The compounds obtained were isolated in high yield. The structure of the compounds obtained is established by modern methods of physico-chemical analysis. The protective effect of the compounds obtained was studied by a gravimetric method for 6, 24, 72 hour exposure and an inhibitor concentration of 10, 25, 50, 100 ppm. As an aggressive medium, a highly mineralized medium containing СО2 and Н2S was used in simulated formation water. The dynamics of changes in the protective effect of the resulting aminophosphonate from time to time, at dosages of 2.5-100 ppm, were studied using electrochemical analysis methods. The protective effect of syntanyl-O-ethyl- (N-morpholinyl) methylphosphonate obtained at 25 ppm and a shutter speed of 6 hours is 73-82%. The article shows that with increasing concentration, an increase in the protective effect is observed. The greatest protective (89,6) effect showed O-2- [2- [2- [2- [2- [2- [2- [2- [2- [2- (dodecyloxy) ethoxy] ethoxy] ethoxy] ethoxy ] ethoxy] ethoxy] ethoxy] ethoxy] ethoxy] ethyl-O-ethyl- (N-morpholinyl) methylphosphone at a dosage of 100 ppm.

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“…The use of inhibitor protection for the purpose of preventing corrosion of oil & gas steel pipelines is a universal way of extending their service life [1][2][3][4][5]. The relevance of research in this area consists in the design for multi-purpose effective inhibitor compounds which have the universality of their protective action.…”

Section: Introductionmentioning

confidence: 99%

Gravimetric and electrochemical testing of multipurpose corrosion inhibitors with biocidal action

2019

Int. J. Corros. Scale Inhib.

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The article presents the results of studies of industrial additives as universal compositions that can simultaneously absorb hydrogen sulfide and inhibit the corrosion of carbon steel in lowmineralized H 2 S containing media with different acidity. Gravimetric tests were carried out and the current-voltage characteristics of the steel immersed in a 0.5% solution of NaCl without and in the presence of bactericides and hydrogen sulfide were measured. The effectiveness of the absorbing effect of the studied additives was estimated by correlating the kinetics of C(H 2 S) reduction in background and inhibited media. On the basis of a complex of corrosion and electrochemical studies, the influence of the acidity of the medium was discussed, as well as the inherent insignificant concentrations of hydrogen sulfide on the protective ability of the studied substances. According to the results of the tests, we have shown that industrial bactericides have actually the ability to absorb hydrogen sulfide. These compounds are inhibitors of anodic action and their effective inhibitory concentration is at least 50 mg/L. he protective ability of additives increases with decreasing acidity of the medium, as well as with an increase in the exposure time of the steel sample in a corrosive environment. In all our experiments, we compared the effectiveness of industrial additives with a known inhibitor and a bactericidehexamine.

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Film former corrosion inhibitors for oil and gas pipelines - A technical review

Cited by 151 publications

References 60 publications

A Data-Driven Machine Learning Approach for Corrosion Risk Assessment—A Comparative Study

A Data-Driven Machine Learning Approach for Corrosion Risk Assessment—A Comparative Study

New Sintanyl Phosphonates for Protection of Oil and Gas Pipelines from Steel Corrosion

Gravimetric and electrochemical testing of multipurpose corrosion inhibitors with biocidal action

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