The Power of Image Analytics in Mitigating Corrosion

Introduction

If not properly identified and managed, corrosion can have a catastrophic impact on a facility. According to the NACE International Impact report, the cost of corrosion and corrosion management for the global oil and gas industry amounts to USD $375 to $875 billion per year [1]. To mitigate the cost of asset failure and downtime that can result from corrosion, facilities must adopt a robust, proactive approach to corrosion assessment and mitigation. However, proactive corrosion management requires a sizable amount of data collection, processing, and interpretation, and many facilities struggle to allocate the budget and resources needed for this approach.

Among the emerging technology and methodologies that are being developed by the industry to address the challenges of adopting a more proactive approach to corrosion management, recent advancements in visual data capture and image analytics have proven to be an effective tool for facilities gathering and processing large amounts of visual data. With these advancements, facilities can systematically identify external corrosion and visual defects, trend corrosion over time, and optimize and automate follow-up maintenance, resulting in more reliable operations and a reduction in inspection and maintenance costs.

In this article, we’ll discuss two use cases of how advanced visual data capture and image analytics can be used across multiple industries to drive better reliability decisions:

1. Coating Optimization for the Upstream Industry: Advanced visual data capture and image analytics used to optimize the coating program while reducing the cost of conventional laser scanning by 90%.
2. Systematic Identification of External Corrosion in Midstream and Downstream Industries: Advanced visual data capture and analytics used to systematically identify external corrosion in midstream and downstream facilities, enabling reliability leaders to drive better and faster decisions and reducing inspection time by 50%.