Flow assurance
Apply historical and operational data to wax and scale prediction.
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Industrial Prediction & Risk Analytics
Striix Predictive Intelligence
Detect risk before it becomes downtime.
THE PROBLEM
Process risks can develop before they become obvious.
Combine historical and real-time operational data, engineering knowledge and AI to detect anomalies, predict process and asset risks, and support earlier operational decisions.
Historical trends and changing operating conditions contain useful signals. Engineering knowledge helps put those signals in context so predictions and anomalies can support operational review.
DATA → INTELLIGENCE → ACTION
How it works.
- 01Historical + Real-time Operational Data
- 02Engineering + AI Models
- 03Prediction / Anomaly Detection
- 04Alerts & Decision Support
PRACTICAL APPLICATIONS
Where the technology helps.
Sand prediction
Use production information to support sand-related assessment and intervention planning.
Corrosion and anomalies
Apply engineering analytics and AI to identify patterns for technical review.
- Solid deposition / flow assurance
- Sand prediction
- Corrosion analytics
- Anomaly detection
- Predictive monitoring
IMPLEMENTATION CONTEXT
Built around
your workflow.
Define the process or asset risk, assess data quality and establish the engineering basis. Model outputs and alert thresholds need to be evaluated in the operating context before they are incorporated into decision-making.
Discuss your application →Have a problem worth solving?
Let’s turn it into a working solution.