Uncertainty Calculations & Monte Carlo Simulations

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Uncertainty Calculations & Monte Carlo Simulations

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All sessions of this unique course online

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Course description

This course covers the propagation of measurement uncertainty using the methods outlined in the JCGM Guide to the Expression of Uncertainty in Measurement from a statistical perspective. This course will provide participants with a working knowledge of the methods needed to compute measurement uncertainties, hands-on experience in the application of these methods, and scientific and statistical insight into the interpretation of the results. The theory of uncertainty analysis will be applied on two practical examples, which are related to the oil and gas industry, i.e. the calculation of the uncertainty of calibration of a gas flow meter and the calculation of uncertainty in energy and volume measurement in a (fiscal) gas metering station.

In many cases, the effects of uncertainties are hard, if not impossible, to calculate analytically, especially with non-linear systems and when uncertainties of different contributors interfere with each other. A way to solve such problems is using ‘Monte Carlo’ simulation, in which each individual step in the uncertainty process is simulated in the computer. A large number of runs can easily be achieved, so reliable statistics are obtained and effects of the different contributors can be separated. In this part, the basics of Monte Carlo simulations will be described and the possibilities illustrated with several examples from the oil and gas industry and complex data-processing.

meet the training leaders
Hans van Maanen | Fleming
Hans van Maanen
Senior Consultant Multi-Phase Measurement
Hint Europe B.V.
Arend Herwijn
Senior Metrology Consultant
Hint Europe B.V.
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Uncertainty Calculations and Monte Carlo Simulations online live training by Fleming Agenda Cover
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Topics

Uncertainty Analysis according to the ISO ‘Guide to the Expression of Uncertainty in Measurement’

Type A uncertainty evaluation based on statistical methods

Type B uncertainty evaluation based on non-statistical methods

Setting-up an Uncertainty Budget

Implementation of Uncertainty Analysis for metering systems in the Oil&Gas Industry

Uncertainty Evaluation of the calibration of a gas flow meter

Basics of Monte Carlo simulations and how to set these up

Achievements possible with Monte Carlo simulations

Analysis of the interaction of the different uncertainty and noise sources in complex systems

Practical examples which show the potential of the Monte Carlo simulations

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Ada Tobias | Marketing Manager | Fleming
Ada Tobias
Sr. Manager for Energy & HSE

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