SOLV ® is renowned for its expertise in applying Monte Carlo Simulation (MCS) to uncertainty analysis in flow measurement and allocation.
Monte Carlo Simulation is a robust statistical tool that utilizes stochastic random number sampling to model system variability. By aggregating results from numerous random trials, MCS helps determine the distribution and uncertainty of key variables, such as measured or allocated quantities. Originally developed during the Manhattan Project to model nuclear fission for the atomic bomb, MCS has since found applications in various fields, including financial risk modelling.
Our director, Martin Basil, CEng, was a pioneer in applying MCS to flow measurement and allocation in the late 1990s. He observed that conventional uncertainty analysis methods were increasingly inadequate for the complex allocation systems being deployed in the North Sea at that time.
For a more detailed exploration of our work and Martin’s contributions in this field, please refer to some of his original papers https://solv.net/documents/
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