Abstract
Abstract Objectives / Scope Continuous Fabric Maintenance (FM) is crucial for uninterrupted operations on offshore oil and gas platforms. A primary FM goal is managing equipment degradation onset across the production facilities. General Vision Inspection (GVI) programs target timely detection and grading of defects such as corrosion severity, coating condition, and likelihood-of-failure. These processes are costly, time-consuming, labor-intensive, and must be conducted on-site. Moreover, inspection findings are subjective and provide incomplete asset coverage, leading to increased risk of unplanned shutdowns. Insights from inspection programs feed into the prioritization of equipment maintenance and defect remediation. The impacts of an Automated Condition Assessment system on FM efficiency, risk reduction, maintenance cost reduction, and required manpower are demonstrated in practice across four offshore deep water production facilities. Methods, Procedures, Process Inspection Data is collected across the entirety of the facilities using a terrestrial scanner. Corrosion onset, coating degradation, and equipment is detected, classified, and identified across the facility using the Automated Condition Assessment System, empowered by machine learning and computer vision algorithms. Equipment is tagged with unique piping line numbers per design, fixed equipment tags, or a unique asset identification number. Detected defects and equipment tags are registered together, which results in a comprehensive equipment condition database. Each of these individual tags will be used to group together all relevant images and point out potential defects. By amalgamizing the different perspectives, the coverage on each asset will be increased. This includes imagery-based examples as well as holistic point cloud coverage which are used to better prioritize asset management and maintenance processes. Results, Observations, Conclusions Recommendations and their impacts from the Automated Condition Assessment System are compared against recommendations and impacts from the standard GVI process (i.e., physical walkdowns) conducted one year earlier. The GVI process gives gross estimations either by block/ or paint region. The Automated Condition Assessment System uses volumetric data given by scans to report results in various segmentations. These include: per block, line, area, and height groupings. Reported results are averaged across the four deep water production facilities. The Automated Condition Assessment System achieved increased inspection coverage, at a reduced cost, with decreased PoB (Person on Board) requirements. Facility inspection coverage rose from 15% to >95%, with a 6% of the usual PoB requirement, and at a 50% inspection cost reduction. Work packs are created based on the Automated Condition Assessment System recommendations. Better prioritization of maintenance resulted in an estimated 86% reduction in maintenance costs, over a two year period. Novel/Additive Information The Automated Condition Assessment system contributes directly to greater risk awareness, targeted remediation strategies, improving the overall efficiency of the asset management process, reducing maintenance costs, and the down-time of offshore facilities. Fabric Maintenance campaigns vary across many operators in the offshore oil and gas space and can largely depend on cost of PoB. Since painting, remediation, and coating can be such a high-volume task, a large number of people are required to paint a portion of the platform in a short period of time. Many operators cannot afford to have large PoB requirements for their offshore Fabric Maintenance campaigns, so they employ strategies to reduce the time and personnel allocation. For example, an operator may choose to have a parallel strategy where two separate teams address Fabric Maintenance related problems offshore. One team will be dedicated to pursuing issues which are in more critical condition and in risk of becoming nominated for a complete replacement. When an item is replaced instead of remediated, painted, or re-coated the implications of cost increase ten-fold. One paint job’s associated cost could be as low as a few thousand dollars while a full replacement job offshore could be requiring a significant engineering, construction and planning effort amassing to several hundred thousand dollars. Another team could be dedicated to painting by block or designated region. The focus of this team is to address all non-critical issues while also repainting any defects found during their campaign. However, the critical issues cannot be addressed by this team due to the delicate nature of the asset condition. Varying approaches to Fabric Maintenance can also include a dedicated on-site team for painting and remediation or a rotational program that addresses the entire facility. It should also be clear that remediation, coating and painting is not limited to process equipment but can also include structural and safety equipment.
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