This paper describes the technology and processes used to identify in a timely matter the source of an Instantaneous Over Current (IOC) trip during an ESP re-start at Shell Perdido SPAR. Monitoring health condition of subsea ESPs is challenging. ESPs operate in harsh and remote environments which makes it difficult to implement and maintain any in-situ monitoring system. Shell operates five subsea ESPs and implemented a topside conditioning monitoring system using electrical waveform analysis. The Perdido SPAR had a scheduled maintenance shutdown in April 2019. While ramping the facility down on April 19, 2019 the variable frequency drive (VFD) for ESP-E tripped on a cell overvoltage fault. The cell was changed, but the VFD continued to trip on instantaneous overcurrent. During ramp up beginning April 29, 2019 most equipment came back online smoothly, but the VFD of the particular ESP labeled ESP-E continued to experience the problem that was causing overcurrent trips, preventing restart. Initial investigations could not pinpoint the source of the issue. On May 1, 2019 Shell sought to investigate this issue using high-frequency electrical waveform data recorded topside as an attempt to better pinpoint the source of this trip. Analysis of electrical waveform before, during and after the IOC trip found an intermittent shorting/arcing at the VFD and ruled out any issues with the 7,000-foot-long umbilical cable or ESP motor. Upon further inspection, a VFD technician was able to visually identify the source of the problem. Relying in part on electrical waveform findings, VFD technician found failed outer jackets in the MV shielded cables at the output filter section creating a ground path from the VFD output bus via the cable shield. The cables were replaced, and the problem was alleviated allowing the system to return to normal operation. Shell credits quick and accurate analysis of electrical waveform with accelerating troubleshooting activities on the VFD, saving approximately 1-2 days of troubleshooting time and associated downtime savings, that translate to approximately 50,000 BOE deferment reduction. Analysis of high-frequency electrical waveform using physics-based and machine learning algorithms enables one to extract long-term changes in ESP health, while filtering out the shorter-term changes caused by operating condition variations. This novel approach to analysis provides operators with a reliable source of information for troubleshooting and diagnosing failure events to reduce work-over costs and limit production losses.

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