Securing Offshore Reliability
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Company Background
PTT Exploration and Production Public Company Limited (PTTEP) is Thailand’s national upstream oil and gas operator, managing offshore production assets critical to domestic energy supply. Booster Compressors (BCs) deployed on remote wellhead platforms are essential for maintaining gas flow and stabilizing production across the offshore network.
These assets operate in harsh environments, far from onshore engineering support, making reliability and remote visibility non-negotiable.
These assets operate in harsh environments, far from onshore engineering support, making reliability and remote visibility non-negotiable.
Challenges
Booster compressor trips were causing substantial production losses. Key issues included:
- Limited early warning before compressor shutdown
- Difficulty differentiating process-driven trips from engine-related faults
- Long recovery times due to offshore accessibility constraints
- Data siloed across multiple process historians
- Manual, post-event root cause investigations
Solution
PTTEP implemented a predictive reliability framework by integrating data from
multiple offshore process historians into Seeq for centralized, contextualized analytics.
1. Historian Integration Data streams including:
2. Self-Service Predictive Analytics Using Seeq Workbench, PTTEP engineers developed predictive models independently without reliance on external data science teams. Analytics included:
1. Historian Integration Data streams including:
- Lube oil temperature and pressure
- Vibration signals
- Inlet gas temperature and pressure
- Engine performance parameters
2. Self-Service Predictive Analytics Using Seeq Workbench, PTTEP engineers developed predictive models independently without reliance on external data science teams. Analytics included:
- Event aggregation and trip pattern comparison
- Correlation modelling between ambient conditions and lube oil pressure
- Leading indicator identification
- Dynamic threshold optimization to reduce false positives
3. Early Warning Deployment
Predictive indicators were operationalized into dashboards and alerts, providing:
Predictive indicators were operationalized into dashboards and alerts, providing:
- 30–60 minutes of advanced warning before trip conditions
- Clear differentiation between process-related instability and engine faults
- Actionable intervention windows for operators
Benefits
Operational Efficiency
- Reduced unplanned compressor trips
- Shorter recovery times
- Improved production continuity
- High-accuracy trip prediction
- Improved root cause clarity
- Reduced mechanical stress from repeated shutdown cycles
- Reduced flaring associated with unstable compression
- Lower operational disruption and emergency mobilization
Organizational Impact
- Shift from reactive troubleshooting to predictive asset management
- Unified cross-domain data visibility across operations
- Engineers empowered with self-service advanced analytics
Cost Saving
Avoided production losses and reduced emergency interventions represent significant annual financial impact.
To review the quantified opportunity-loss avoidance model and financial benefit analysis for offshore compression assets, connect with us directly for a detailed cost-saving assessment.
To review the quantified opportunity-loss avoidance model and financial benefit analysis for offshore compression assets, connect with us directly for a detailed cost-saving assessment.
