Linear uncertainty analysis is also known as “first order second moment” (or “FOSM”) analysis. It provides approximate mathematical characterisation of prior predictive probability distributions, and of posterior parameter and predictive probability distributions. It has other uses as well. It can be used to demonstrate how the history-matching process bestows worth on data. It can also be deployed to track the flow of information from field measurements of system state to parameters, and ultimately from parameters to model predictions.
The present document is a tutorial on how to perform common linear analysis tasks using utilities from the PEST suite to a model which has been setup and calibrated in a previous GMDSI tutorial. This tutorial is part of a series of tutorials which demonstrate workflows for parameter estimation and uncertainty analysis with the PEST/PEST++ suites. These are not the only (or necessarily the best) workflows; their purpose is to take the reader through the fundamentals of how to accomplish common tasks whilst also providing insights in how to apply the outcomes.