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Use case

Predicting Heat Exchanger Fouling Before Throughput Becomes Constrained

Pablo Sanchez
,
Industry Principal
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3
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The Challenge

Fouling in the hydrotreater heat exchangers gradually restricts unit throughput. To compensate, operators open a control valve to maintain production. However, once the valve approaches 95% open, engineers lose operational flexibility and are forced into reactive cleaning.

The key challenge was identifying the moment when fouling begins to meaningfully impact production, before reaching the constraint limit.

  • Progressive fouling reducing heat transfer efficiency
  • Valve opening used as compensation mechanism
  • Loss of visibility once valve exceeds 95%
  • Reactive rather than proactive cleaning strategy

The Approach

The team translated pressure differential behavior into a predictive fouling indicator.

  • Differential pressure formula: A calculated tag was created to represent exchanger pressure drop
  • Correlation validation: Analysis confirmed pressure difference as a reliable fouling indicator, correlating it to the manual valve increase
  • Constraint window identification: Time-series analysis focused on periods when valve opening exceeded 90%
  • Predictive threshold creation: The moment when fouling began constraining production was identified, defining the ΔP when valve opening > 90%
  • Monitor configuration: An alert was created to notify engineers before throughput was impacted

Key Insight

Pressure differential trends provide early warning signals, allowing fouling to be addressed before production losses occur.

Results

KPIResult
Fouling indicatorPressure differential validated
Constraint thresholdIdentified before 95% valve opening
Monitoring capabilityEarly alert system implemented
Maintenance timingShift from reactive to predictive
Production protectionCleaning scheduled before throughput loss

The Takeaway

By identifying the precise moment fouling becomes a production constraint, the team moved from reactive cleaning to predictive maintenance, protecting throughput and reducing operational disruptions.

Oil & gas
Energy & natural resources
Asset Performance Management
Operational Performance Management
Predictive Maintenance
Process Health Monitoring
Process Engineer
Reliability Engineer
Maintenance Engineer
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The Challenge

Fouling in the hydrotreater heat exchangers gradually restricts unit throughput. To compensate, operators open a control valve to maintain production. However, once the valve approaches 95% open, engineers lose operational flexibility and are forced into reactive cleaning.

The key challenge was identifying the moment when fouling begins to meaningfully impact production, before reaching the constraint limit.

  • Progressive fouling reducing heat transfer efficiency
  • Valve opening used as compensation mechanism
  • Loss of visibility once valve exceeds 95%
  • Reactive rather than proactive cleaning strategy

The Approach

The team translated pressure differential behavior into a predictive fouling indicator.

  • Differential pressure formula: A calculated tag was created to represent exchanger pressure drop
  • Correlation validation: Analysis confirmed pressure difference as a reliable fouling indicator, correlating it to the manual valve increase
  • Constraint window identification: Time-series analysis focused on periods when valve opening exceeded 90%
  • Predictive threshold creation: The moment when fouling began constraining production was identified, defining the ΔP when valve opening > 90%
  • Monitor configuration: An alert was created to notify engineers before throughput was impacted

Key Insight

Pressure differential trends provide early warning signals, allowing fouling to be addressed before production losses occur.

Results

KPIResult
Fouling indicatorPressure differential validated
Constraint thresholdIdentified before 95% valve opening
Monitoring capabilityEarly alert system implemented
Maintenance timingShift from reactive to predictive
Production protectionCleaning scheduled before throughput loss

The Takeaway

By identifying the precise moment fouling becomes a production constraint, the team moved from reactive cleaning to predictive maintenance, protecting throughput and reducing operational disruptions.

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Share with a co-worker

The Challenge

Fouling in the hydrotreater heat exchangers gradually restricts unit throughput. To compensate, operators open a control valve to maintain production. However, once the valve approaches 95% open, engineers lose operational flexibility and are forced into reactive cleaning.

The key challenge was identifying the moment when fouling begins to meaningfully impact production, before reaching the constraint limit.

  • Progressive fouling reducing heat transfer efficiency
  • Valve opening used as compensation mechanism
  • Loss of visibility once valve exceeds 95%
  • Reactive rather than proactive cleaning strategy

The Approach

The team translated pressure differential behavior into a predictive fouling indicator.

  • Differential pressure formula: A calculated tag was created to represent exchanger pressure drop
  • Correlation validation: Analysis confirmed pressure difference as a reliable fouling indicator, correlating it to the manual valve increase
  • Constraint window identification: Time-series analysis focused on periods when valve opening exceeded 90%
  • Predictive threshold creation: The moment when fouling began constraining production was identified, defining the ΔP when valve opening > 90%
  • Monitor configuration: An alert was created to notify engineers before throughput was impacted

Key Insight

Pressure differential trends provide early warning signals, allowing fouling to be addressed before production losses occur.

Results

KPIResult
Fouling indicatorPressure differential validated
Constraint thresholdIdentified before 95% valve opening
Monitoring capabilityEarly alert system implemented
Maintenance timingShift from reactive to predictive
Production protectionCleaning scheduled before throughput loss

The Takeaway

By identifying the precise moment fouling becomes a production constraint, the team moved from reactive cleaning to predictive maintenance, protecting throughput and reducing operational disruptions.

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