Reliable instrumentation is fundamental to safe and stable compressor operation. A faulty pressure transmitter can make a healthy
process appear abnormal, generating misleading alarms and potentially triggering unnecessary equipment trips.
In this case, the compressor's enclosure pressure transmitter began sending incorrect pressure readings. The challenge was to
determine whether the falling pressure represented a real process condition or a sensor fault before it disrupted compressor
operation.
VROC was monitoring the compressor train using 256 live AI models across critical operating parameters. The enclosure pressure
model detected a significant deviation between the measured pressure and the predicted normal operating envelope four days before
the trip.
It was found that the enclosure pressure reading was inconsistent with the wider compressor process.
Investigation confirmed that the enclosure pressure transmitter was malfunctioning and transmitting incorrect pressure data. The
faulty signal subsequently generated a false alarm and contributed to the compressor trip.
The enclosure pressure signal deviated significantly from its expected behavior while related suction and discharge pressure models
remained normal. This inconsistency helped indicate that the issue was with the pressure transmitter rather than a genuine system
wide pressure change.
Earlier fault detection
VROC identified abnormal sensor behavior 4 days before the compressor trip, providing time for the
operations team to investigate the signal.
Improved diagnostic confidence
Comparing the abnormal enclosure pressure behavior with other normally operating pressure
models helped distinguish a sensor fault from a genuine process condition.
Estimated cost avoidance
The insights enabled the client to swap compressors in time, helping avoid an estimated USD $36K in
production loss, equivalent to approximately 600 bbl, as well as reducing the risk of associated well shut-in and flaring.
VROC compares actual behavior with AI-predicted operating conditions to help identify abnormal instrumentation and distinguish sensor faults from genuine process changes.
Explore Deviation Management | Talk to Our Team
Related Case Study
Detecting Low Suction Pressure 3 Days Before a Gas Compressor Trip
See how multidimensional Deviation monitoring identified a genuine process-control issue by analyzing relationships across multiple compressor parameters.
Industry: Oil and Gas
Solution: Predictive Maintenance & Reliability
Use Case: Deviation Management
Facility: Offshore Platform
Asset: Gas Compressor
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