Effect of Nitrate on Carbon Steel Corrosion

Vargas, Silvia; Woollam, Richard; Durnie, William; Hodges, Michael; Betancourt, Daniel

doi:10.2118/184512-ms

Cited by 3 publications

References 12 publications

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Assessing the feasibility of using a data-driven corrosion rate model for optimizing dosages of corrosion inhibitors

Jayaweera,

Fernandes del Pozo,

Hitsov

et al. 2024

npj Mater Degrad

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Optimizing dosages of corrosion inhibitors requires experimental data gathered from time-consuming methods. The current study examines the feasibility of optimizing inhibitor dosages using a model trained for predicting corrosion rates more easily measured using linear polarization resistance in a full-scale cooling water system. A comprehensive study on variable selection showed that linearly correlated variables are necessary to predict corrosion trends. The Sobol sensitivity of inhibitors is trivialized by variables linearly correlated to the corrosion rate. The study highlights the importance of achieving high model prediction accuracy and high Sobol sensitivity of inhibitors to the corrosion rate, for using the model for inhibitor dosage optimization.

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Assessing the feasibility of using a data-driven corrosion rate model for optimizing dosages of corrosion inhibitors

Jayaweera,

Fernandes del Pozo,

Hitsov

et al. 2024

npj Mater Degrad

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Carbon Dioxide Induced Corrosion of Carbon Steel X65 Exposed to Nitrite Aqueous Solutions

Vargas¹,

Woollam²,

Durnie³

et al. 2018

SPE Journal

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Summary Nitrate used to control reservoir souring in oil fields contains nitrite impurities. Nitrite is a strong oxidizer, and when used in souring–treatment fluids, the flow path often includes carbon–steel piping. Vanadium, also an oxidizer, is at times found in oilfield–production streams that commingle with souring–treatment fluids. The interactions between nitrite and vanadium and their effects on carbon steel X65 corrosion were investigated. The effect of nitrite on corrosion was investigated using synthetic brine to simulate produced water [rich in carbon dioxide (CO2), pH value of approximately 5] and seawater (negligible CO2, pH value of approximately 7). Tests were conducted with carbon steel X65 exposed to synthetic brine at 25, 60, and 80°C using a rotating cylinder electrode (RCE). The test results demonstrate the following: The corrosivity of nitrite strongly depends on the pH level. Nitrite increases corrosion at pH of approximately 5 and is relatively benign at pH of approximately 7. Nitrite reduces to ammonium (thermodynamically stable in acid solutions), whereas vanadium(III) delays the formation of ammonium. Inhibited corrosion tests indicate that nitrite reduces the performance of the studied commercial corrosion inhibitors (CIs).

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The Use of Artificial Intelligence (AI) to Give Insight to a Complex Well Tubing Issue to Ensure Suitable Corrosion Mitigation Approaches

Mohamed-Said,

Cowe,

Bertoncello

et al. 2023

Day 3 Wed, October 04, 2023

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In one of TotalEnergies North Sea fields, nitrate is continuously injected as the main mitigation of reservoir souring. The nitrate treatment is employed to limit the biogenic generation of H2S, due to reservoir souring. Reservoir souring is caused by the proliferation of SulfateReducing microbes (bacteria and/or archaea). In parallel, severe corrosion was observed in oil producing well tubing conveying fluids from a reservoir subjected to nitrate treatment. It is known that nitrates can catalyze the corrosion of carbon steels through different mechanisms, in particular electrochemical or microbiological. The challenge was therefore to accurately evaluate the impact of nitrate injection, and its presence in the produced fluids, on the corrosion of the producing well tubing. The influence of nitrate treatment towards corrosion of carbon steel well tubing has been singled out using an artificial intelligence algorithm. The algorithm employs a method called "Propensity Score Matching" (PSM). PSM is a statistical method commonly used in the medicine field to assess the efficiency of treatment in biased data. This method has been used to compare two reservoirs, one being subjected to nitrate treatment and another that has never been subjected to nitrate treatment. In this paper a first known use of causal inference in industrial settings is presented. It helped removing biases by comparing only comparable data and to find causal relationship in the data. Outcomes of the multi-faceted study have led to optimized corrosion mitigation approaches and increased well tubing service life.

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Effect of Nitrate on Carbon Steel Corrosion

Cited by 3 publications

References 12 publications

Assessing the feasibility of using a data-driven corrosion rate model for optimizing dosages of corrosion inhibitors

Assessing the feasibility of using a data-driven corrosion rate model for optimizing dosages of corrosion inhibitors

Carbon Dioxide Induced Corrosion of Carbon Steel X65 Exposed to Nitrite Aqueous Solutions

The Use of Artificial Intelligence (AI) to Give Insight to a Complex Well Tubing Issue to Ensure Suitable Corrosion Mitigation Approaches

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