Using digital twins and data analytics to make informed operational decisions – a centrifugal compressor case study

Abstract

An Australian operator with an expansive portfolio of liquefied natural gas, pipeline gas and oil assets wanted to gain greater visibility of how their compressor fleet was operating. To help the operator gain a greater understanding of the performance of their assets, Worley Digital built digital twins of 17 of their compressors. This involved detailed first principle calculations supported by hundreds of thousands of offline simulations. This created the thermodynamic correlations necessary to accurately model the most important operating statistics surrounding each stage of those assets. We then used dimensional analysis and data analytics to benchmark the operation of these machines. This represents a hybrid approach; first principles engineering and simulation coupled with data science and analytics. A suite of tools was then delivered to the operator in their preferred real-time data analytics and visualisation platform, providing them with information about the efficiency of their compressors. They were then able to perform net present value calculations based on different operating and maintenance strategies. This gave them the detailed information they needed in order to be able to make more informed decisions. An example of this might be a decision to bring a scheduled maintenance activity forward based on the knowledge that there are net operational and financial incentives to do so. The resulting tool has proved extremely valuable, quantifying some business-critical metrics that have led to several financially impactful operational decisions.