LNG Plant Operations and Surveillance
BKOAI delivered PI Vision–based operations surveillance for a large LNG facility, rebuilding PI AF into reusable templates and a standardized asset hierarchy to improve remote visibility, accelerate anomaly detection, and support scalable deployment across trains
Goals
- Deploy operations surveillance screens for a large LNG facility before first LNG introduction.
- Create a reusable, standardized data template hierarchy to streamline future train expansions.
- Provide a consistent PI AF data foundation for both PI Vision operations screens and Seeq analytics.
- Improve operational visibility across distributed facility areas, including the control room, administrative offices, and berths.
Challenges
- Inherited an incomplete PI AF database with missing PI tags and inadequate documentation.
- Faced a compressed 5–6 month timeline after previous contractors failed to deliver.
- Needed to support multiple operational areas and stakeholders while maintaining a unified asset hierarchy.
- Had to incorporate missing PI tags incrementally as they became available in the production PI server.
Solutions
- Developed PI AF templates based on P&IDs for gas inlets, turbines, and utilities.
- Implemented a 3-tier PI Vision screen hierarchy and added volumetric tank calculations.
- Configured element hierarchies to stream unified asset context to Seeq analytics.
- Added startup-event templates for propane unloading, gas turbine operations, and LNG tank loading and unloading activities.
Results
- Enabled remote operational visibility across control rooms, administrative offices, and berths.
- Reduced future engineering effort through reusable, scalable PI AF asset templates.
- Accelerated anomaly detection using rate-of-change calculations for abnormal conditions.
- Established a standardized PI Vision architecture that can be copied and adapted efficiently for future LNG trains.
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