Remote Monitoring of Mud Pumps on Offshore Drilling Platforms: A Case Study from the North Sea
The Importance of Continuous Machine Monitoring
In the era of industrial digitalization, continuous machine monitoring is crucial for maintaining the health of industrial equipment. Asystom, a leader in AI-assisted machine condition monitoring, has developed the world’s most data-rich wireless sensor capable of analyzing and diagnosing machine health remotely. This technology provides real-time insights into the condition of machines, eliminating the need for physical inspections. By identifying potential issues early, it reduces the costs associated with unplanned downtime and allows for timely interventions, preventing major failures.
The Challenge: Optimizing Maintenance and Reducing Downtime
Service companies and oil companies must maintain their production tools despite the harsh conditions and remoteness of offshore platforms. They face challenges related to the high cost of accessing offshore platforms for emergency interventions and the need to conduct in-depth analyses of potential breakdowns or deviations remotely. This necessitates providing of information remotely and the ability to request additional information without human intervention. A leading offshore drilling company struggled with unplanned downtimes and high operational costs due to insufficiently proactive inspection methods.
The Solution: Advanced Vibrational and Acoustic Monitoring
By combining acoustic (ultrasound), oscillation (vibration) and thermal (temperature) data, the multi-sensor enables complex machinery to be monitored autonomously. The battery-powered system transmits the measurement data via LoRaWAN, which greatly reduces the installation effort and costs compared to a wired installation. Sensors were deployed to continuously monitor equipment health, providing early detection of potential issues.
Quick and Simple Sensor Setup
The sensors were installed on a mud pump in the North Sea within a few minutes. After a short training period of just a few days, the AI-based evaluation of the sensor data could begin. The system detected an anomaly on the Topdrive main shaft based on a change in the ultrasound signal. Offshore personnel visually inspected the Topdrive without finding anything, while the onshore team began their analysis. Thanks to the ultrasound data, the analysis team identified loose metal fragments alongside the main shaft. The Topdrive was stripped during a planned drilling stop.
Findings
The findings revealed broken Belleville springs in the torque arrestor frame, leading to metal-to-metal contact between the link hanger and split collar. This caused ultrasound emissions alongside the main shaft, which the sensors detected, potentially preventing a breakdown during later drilling operations.
Ultrasound Early Detection
Sensors detected rising ultrasound levels on the Topdrive main shaft, prompting detailed analysis and early intervention.
The Result: Achieving Operational Efficiency and Cost Savings
- Proactive Maintenance: Early detection enabled scheduled maintenance, avoiding unexpected downtimes.
- Cost Savings: Reduced emergency repair costs and improved efficiency.
- Enhanced Equipment Longevity: Continuous monitoring extended equipment lifespan.
Summary: Effective Predictive Maintenance
The technology enabled early detection of issues, allowing thorough analysis and preventive maintenance, resulting in improved drilling performance and reduced costs. The sensor detected metal-to-metal friction on the equipment, and the alarm was given at the proper time, allowing the analysis team to evaluate the trend curves. This paved the way for planning maintenance during a dedicated drilling stop, saving both time and cost.
