Use of data mining in the corrosion classification of pipelines in Naphtha Hydro-Threating Unit (NHT)

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Published Aug 31, 2019
Amir Samimi Pathmanathan Rajeev Ali Bagheri Ali Nazari Jay Sanjayan Ahmadreza Amosoltani Mohammad Sadegh Tarkesh Esfahani Soroush Zarinabadi

Abstract

Nowadays, computational tools for analyzing and collecting data in the operation of petroleum units are essential. One of the methods is the classification or regression to step in the overall process of knowledge extraction. In this paper, a specific type of decision tree algorithm, called the conditional contract arrangement, is Naphtha hydro-threating (NHT) units for 4 factors: Density, pH, total iron ions in vessels (S.FE) and H2S. All of these factors are related to corrosion in NHT units and this paper aims to optimize some conditions to eliminate it. In this regard, using ammonium water with a specific range and pH can be helpful. According to the obtained results the best range of density (in Feed) is less than 0.712 kg/m3, pH (water in vessels) is more than 6.5, S.FE is less than 1.4 ppm and H2S (in recycle gas) is less than 581 ppm. The outcomes also show how this approach can be used to gain insight into some refineries and how to deliver results in a comprehensible and user-friendly way.

How to Cite

1.
Samimi A, Rajeev P, Bagheri A, Nazari A, Sanjayan J, Amosoltani A, Tarkesh Esfahani MS, Zarinabadi S. Use of data mining in the corrosion classification of pipelines in Naphtha Hydro-Threating Unit (NHT). PST [Internet]. 2019Aug.31 [cited 2019Nov.12];3(1):14-1. Available from: https://pipeline-science.com/index.php/PST/article/view/98

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Keywords

Ammonium Water, Corrosion, Tree Decision Algorithm, Naphtha Hydro-Treating Unit, Computational Tools

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Original Work