Closing the metering skills gap in oil & gas

Flow meters could be likened to cash registers for the oil and gas sector as they track the transfer of oil and gas through different stages of production. They are used, among other things, for stringent fiscal taxation measurement to report the quantities of produced hydrocarbons which means they must be accurate, properly maintained and operated by competent and well-trained staff. 

The latter is particularly important, when considering the complexity and sensitivity of many metering technologies and the high level of user intervention and interpretation they often command. 

To put the role of the flowmeter into perspective, a 1% measurement error on a single meter could cost an oil and gas company over $3.6m a year (this is based on 20,000 barrels of oil per day production).  

Despite these high levels of financial exposure, over recent years the flow metering skills gap has got evidently wider. This has particularly been the case since the collapse of the oil price around five years ago. In a bid to reduce costs during difficult times many companies were seen to freeze training, disband in-house metering departments, and slash the number of experienced metering engineers. To make matters worse, with many of the more experienced metering engineers reaching retirement, little is being done to replace them. 

Meter management has been known to be notoriously difficult, time-consuming, and fraught with inefficiencies. This has not in any way helped operators in their plight to reduce costs. However, on the positive side, advances in technology have brought about systems of greater intelligence; simpler to use; with faster processing. Some are also fitted with built in diagnostics and analysis tools. These advances have, without doubt, helped to address the flow metering skills issue for the oil and gas sector.  With new technologies continuously coming on stream, the engineer now has an increasing array of tools to help keep metering assets working effectively and efficiently. Some high-impact arrivals over recent years have included automated systems, meter diagnostics, Computational Fluid Dynamics (CFD), risk-based calibration, network management and big data.

The world of flow measurement is changing. Traditional technologies such as orifice plates and turbine meters are being replaced by more sophisticated technologies such as ultrasonic and Coriolis meters which have faster processing times, onboard signal processing and improved communication platforms. 

 Meter network management is another method that can help streamline flow measurement operations. Despite often being managed in isolation, meters generally work as part of a group. The most efficient way to manage them is to manage the full network. Managing flow meters as a group allows you to cross-check them against one another.  Generally inter-relationships exist between meters. This can be exploited when tracking odd behaviour across pipeline groups.  Cross-checking meters against one another makes it easier to identify changes in patterns and trends which could signify faulty measurement devices or real operational issues.  

The best way of identifying an anomalous measurement is to use data validation and reconciliation (DVR), a network monitoring technique used to check the quality and reliability of flow measurement data. It checks for changes in relationships between meters and metering groups to single out inconsistencies.
  

Big data has provided a step change in flow and production measurement. By providing the ability to capture huge amounts of data, in real time, from a variety of sensors, allows much greater optimisation and control over production. The advanced data mining and analysis tools afforded by big data provides more powerful and intelligent data. They can be used to support self-learning machines to assist in predictive maintenance and early warning control systems. So not only can intelligent metering systems reduce costs and financial exposure, but they can also allow higher recovery rates of oil and gas through production optimisation.