Abstract

This paper focuses on reviewing and offering a solution to manage the complex atmospheric corrosion process and its protection within industrial plants such as Oil & Gas, Petrochemicals, Pulp and Paper, and Mining. A review of the main protective coating failure mechanisms, as well as corrosion evaluation methods, are presented. Our objective is to gather the main parameters for a maintenance/inspection management tool, by developing a field data collection processing that feeds a digital model to predict coating failure and to enhance time, costs, and performance of asset integrity management activities. The development of a software is discussed, bringing a view on how to merge the Industry 4.0 technologies such as Digital Twins, Artificial Intelligence, Cloud services, and Mobile concepts to deploy predictive models. Advances in the platform showed ways to outline optimized inspection and maintenance plans, using condition data. It was possible to develop tools to predict costs, workforce and other variables to be considered for protective coating management. Finally, after carrying out all the necessary calculations for the activities mentioned above, the authors present how the technology can deliver other management information such as budget, productivity, the number of paintings done and/or future paintings followed for decision-makers to evaluate optimized scenarios.

Introduction

The Brazilian cost of corrosion was estimated at 3% of the GPD in 2018, that percentage is equivalent to approximately $US 49 billion, according to an ABRACO(1) journal released in 2020.1 It is estimated that from this cost $US 19 billion could have been saved through anticorrosive actions. In another research conducted by the EPRI(2) the results showed that at least 22% of corrosion costs could be avoided through adequate mitigating actions.2

In terms of the integrity of process plant assets, one of the biggest causes of damage is corrosion, which, according to NACE, represents a global annual cost of $US 2.5 trillion, or 3.4% of global GDP.3 A large part of this cost relates to the industrial sector and a significant part relates to atmospheric corrosion and the costs of protecting assets. It is estimated that up to 50% of the cost of corrosion is related to protection against atmospheric corrosion, Schweitzer.4

Keywords:
corrosion inhibition, materials and corrosion, machine learning, oilfield chemistry, neural network, upstream oil & gas, inspection, retrieval system, riser corrosion, corrosion management
Subjects:
Production Chemistry, Metallurgy and Biology, Pipelines, Flowlines and Risers, Information Management and Systems, Materials and corrosion, Artificial intelligence, Neural networks, Well Integrity, Subsurface corrosion (tubing, casing, completion equipment, conductor), Corrosion inhibition and management (including H2S and CO2)
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