Timely detection of subsea leaks prevents production shutdown, saving £647,500 a day *
* Estimate based on customer engineering reports
Monitoring hydraulic fluid usage gives early warning of leak
Hydraulic leaks in subsea equipment are difficult to detect but can have big consequences for both the environment and production.
Using the Eigen Data Transformation engine to calculate the amount of hydraulic fluid used in a rolling 24 hour period, Eigen were able to alert operators to a leak early enough to prevent any production losses.
The Eigen Analytics Platform has a built in Data Transformation Engine that lets you create virtual timeseries by applying mathematical or logical transformations to the source data.
This can be anything from a simple units conversion (For example, if you are measuring a pressure in ‘barg’ but want to plot it in ‘psig’ then you need to multiply it by 14.5) to If..Then statements and Totalisers over irregular calendar periods. These virtual timeseries can be treated just the same as any other real timeseries (for example you can set limits & alerts or use as the basis for another virtual timeseries) but they are evaluated at runtime and do not need the values to be written back to a database.
To monitor the number of pump starts in a rolling 24hr window, a data transformation had to be applied to the source data from the Master Control System (MCS) which only measured the total number of pump starts. The Sliding Aggregates function in Eigen’s Data Transformation Engine and a user alert was configured against this new Virtual Timeseries.
Users can create event checks and configure email and mobile alerts on any timeseries datasource, including virtual timeseries in the Eigen Data Transformation Engine.
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Over the past fifteen years, we have worked with many of the major oil and gas operators. We are trusted as engineering experts who deploy digital technologies to create value.
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