One of Southeast Asia's major oil and gas producers was operating an aging offshore platform highly dependent on continuous gas lift and injection to maintain production.
The gas lift compressor was experiencing recurring trips and was unable to operate continuously, affecting production reliability and making it difficult for the field to consistently meet production targets.
The technical team had also struggled to isolate the underlying causes through conventional troubleshooting. The operator needed greater visibility into compressor health, earlier warning of developing problems and a faster way to understand the factors contributing to repeated interruptions.
VROC worked with the reliability team to analyze the operator's existing operational data, including approximately 35,500 sensor tags.
AI models were applied to support three complementary reliability activities:
Forecast equipment health to identify developing deterioration in the gas compressors.
Predict Time to Failure to provide earlier warning of undesirable operating conditions and create more time for intervention.
Identify contributing factors and root causes associated with equipment and surface-line integrity issues.
Rather than requiring a separate monitoring approach for each problem, VROC enabled the team to use existing operational data to continuously assess compressor behavior, investigate abnormal conditions and focus engineering attention on the issues most likely to affect production.
The deployment moved the reliability team from primarily responding to compressor trips toward continuous monitoring and earlier intervention.
Compressor health became more visible.
AI models provided ongoing insight into equipment behavior, helping the team identify developing reliability issues before they resulted in repeated operational disruption.
Failure risk could be managed earlier.
Time to Failure predictions gave the team greater visibility of approaching undesirable conditions and more time to plan an operational or maintenance response.
Troubleshooting became more focused.
Analysis of contributing parameters helped engineers move beyond symptoms and investigate the factors driving compressor and surface-line integrity problems.
Operational performance improved.
Greater reliability contributed to higher compressor availability and utilization, improved trip avoidance and more consistent production performance.
Gas compressor availability increased from 60% to 100%
Improved visibility into developing equipment issues and earlier intervention supported a substantial increase in compressor availability.
Gas compressor utilization increased from 94.5% to 99.4%
More reliable operation enabled the compressor to remain productive for a greater proportion of available operating time.
Flaring target compliance improved from 50% to 100%
More stable compressor operation contributed to improved compliance with the facility’s flaring performance target.
RM15.6M value realized in three months
The operator reported RM15.6M in value realization, attributed to production-trip avoidance, cost avoidance, fewer equipment failures and reduced process interruptions.
“Let everyone use it… it will open the eyes of the importance of Artificial Intelligence in Oil and Gas.” – Manager, Head Strategy & Performance, HSSE, Gas and New Energy
VROC combines continuous asset monitoring, Time to Failure prediction and contributor analysis to help reliability teams identify developing problems earlier, focus intervention and improve operational performance.
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Industry: Oil & Gas
Solution: Predictive Maintenance & Reliability
Use Case: Multi-Asset Reliability / Time to Failure & Root Cause Analysis
Facility: Offshore Oilfield
Asset: Gas Compressor / Gas Lift System
Gain real-time visibility, predict failure earlier, optimize performance, and take control of your operations with VROC’s integrated solutions.