Design and Implementation of a Digital Twin for Live Petroleum Production Optimization
Several key decisions were made in terms of choosing the architecture for the system , integration with a platform that supports event labeling , factors to consider for templating the simulation setup , and facilitating the simulation output to be compared with field data . The importance and examples of these decisions were presented in the paper to help in adopting and replicating this work .
The methodology and experience shared in this paper is expected to help the community get one step closer to scalable and generalized automated set-point optimization , and also help engineers free-up their time for important decision making , rather than spending it on templatizable and repetitive tasks such as setting up simulations manually .
This infrastructure live massive scale simulation coupled with field IIOT sensor data paves the way towards the next steps required for closed loop dynamic set-point optimization . These include : Inverse modeling using a combination of machine learning and probabilistic models , setpoint recommendation and evaluation system . These topics need separate individual papers and will be presented in future publications .
ACKNOWLEDGEMENTS
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