Intelligent Subsea Condition Monitoring by Digitization and Mining of Big Data

摘要

Inspection Maintenance and Repair activities can typically be reactive in nature, often relying on adequate inspection intervals in addition to Risk Based techniques to minimise production down times. To compliment current IMR technologies, a suite of Digital Applications is currently being developed to provide operators with additional 'real time' remote condition monitoring information. The aim is to provide a focused up-to-date status of subsea equipment and insights on equipment remining life, in the form of both predictive and prescriptive analytics. Combining this information with more traditional inspection techniques will provide a powerful tool in defining support strategies including planning activities to support operations through planned ROV/intervention campaigns, use of remaining life metrics to drive spares holding, location and SIT of spares or use of deep understanding of equipment performance to drive campaign based ROV maintenance activities. The condition monitoring services and digital suite currently in development will enable, optimisation of operational performance, early identification of system degradation, prediction of equipment failures before they occur (prognostics) and immediate notification of equipment failure. Although the condition monitoring services and digital suite currently focuses on Subsea Production System Performance, development of an ongoing 'vulnerability matrix' with participating operators is providing impetus to broaden the breadth of scope to include process measurands. The goal being to provide a useful suite of focused applications and services which have the potential to significantly improve overall production efficiency tailored to the specific needs of the oil and gas production industry.