Numerical Prediction of Erosion-Corrosion in Bends

Keating, Anthony; Nešić, Srdjan

doi:10.5006/1.3290389

Cited by 47 publications

(34 citation statements)

References 5 publications

(6 reference statements)

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“…Other factors that could have an impact on wellhead corrosion rate are organic and inorganic acids, bacteria, turbulence, erosion, erosion-corrosion, bubbles formation, and condensation resulting from the flow of the oil and gas [18,32,[34][35][36][37]. The predicted corrosion model was validated with field data, experimental results, and de Waard-Milliams corrosion models.…”

Section: Resultsmentioning

confidence: 99%

Predictive Modelling of Wellhead Corrosion due to Operating Conditions: A Field Data Approach

Ossai¹

2012

ISRN Corrosion

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The flow of crude oil, water, and gas from the reservoirs through the wellheads results in its deterioration. This deterioration which is due to the impact of turbulence, corrosion, and erosion significantly reduces the integrity of the wellheads. Effectively managing the wellheads, therefore, requires the knowledge of the extent to which these factors contribute to its degradation. In this paper, the contribution of some operating parameters (temperature, CO 2 partial pressure, flow rate, and pH) on the corrosion rate of oil and gas wellheads was studied. Field data from onshore oil and gas fields were analysed with multiple linear regression model to determine the dependency of the corrosion rate on the operating parameters. ANOVA, P value test, and multiple regression coefficients were used in the statistical analysis of the results, while in previous experimental results, de Waard-Milliams models and de Waard-Lotz model were used to validate the modelled wellhead corrosion rates. The study shows that the operating parameters contribute to about 26% of the wellhead corrosion rate. The predicted corrosion models also showed a good agreement with the field data and the de Waard-Lotz models but mixed results with the experimental results and the de Waard-Milliams models.

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Section: Resultsmentioning

confidence: 99%

Predictive Modelling of Wellhead Corrosion due to Operating Conditions: A Field Data Approach

Ossai¹

2012

ISRN Corrosion

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“…In order to perform the CFD calculations with good accuracy, fine near-wall grids with correct near-wall turbulence models can therefore provide mass transfer data for the corrosion species. In these cases corrosion is controlled by the mass transfer, relation between the wall mass transfer coefficient and corrosion rate can be derived as explained in details by Keating and Nesic [11]. Furthermore, in formulating the CFD codes, consideration is made to the hydrodynamic parameters affecting the mass transfer rate of the corrosion products to the bulk fluid and consequently the FAC rate.…”

Section: Conditions Required For Facmentioning

confidence: 99%

Flow Accelerated Corrosion in Nuclear Power Plants

Ahmed¹

2012

Nuclear Power- Practical Aspects

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“…(ii) In distributed flow condition, local near wall density of turbulence helps to remove the protective film. This disruption to the mass transfer boundary layer results in an enhanced corrosion rate [32,33]. (iii) Dissolution of film which is controlled by mass transfer.…”

Section: Mechanisms Of Corrosion In Oil and Gas Pipelinesmentioning

confidence: 99%

“…The possible mechanisms resulting in the removal of the protective film are a follows: (i) Dissolution or removal of protective layer by hydrodynamic shear stress occurs when the shear stress is greater than the bonding force between the film and the substrate. This is a function of a mechanical process of erosion caused by the multiphase flow regime in pipeline [19,32]. (ii) In distributed flow condition, local near wall density of turbulence helps to remove the protective film.…”

Section: Mechanisms Of Corrosion In Oil and Gas Pipelinesmentioning

confidence: 99%

Advances in Asset Management Techniques: An Overview of Corrosion Mechanisms and Mitigation Strategies for Oil and Gas Pipelines

Ossai

2012

ISRN Corrosion

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Effective management of assets in the oil and gas industry is vital in ensuring equipment availability, increased output, reduced maintenance cost, and minimal nonproductive time (NPT). Due to the high cost of assets used in oil and gas production, there is a need to enhance performance through good assets management techniques. This involves the minimization of NPT which accounts for about 20-30% of operation time needed from exploration to production. Corrosion contributes to about 25% of failures experienced in oil and gas production industry, while more than 50% of this failure is associated with sweet and sour corrosions in pipelines. This major risk in oil and gas production requires the understanding of the failure mechanism and procedures for assessment and control. For reduced pipeline failure and enhanced life cycle, corrosion experts should understand the mechanisms of corrosion, the risk assessment criteria, and mitigation strategies. This paper explores existing research in pipeline corrosion, in order to show the mechanisms, the risk assessment methodologies, and the framework for mitigation.

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Numerical Prediction of Erosion-Corrosion in Bends

Cited by 47 publications

References 5 publications

Predictive Modelling of Wellhead Corrosion due to Operating Conditions: A Field Data Approach

Predictive Modelling of Wellhead Corrosion due to Operating Conditions: A Field Data Approach

Flow Accelerated Corrosion in Nuclear Power Plants

Advances in Asset Management Techniques: An Overview of Corrosion Mechanisms and Mitigation Strategies for Oil and Gas Pipelines

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