Quickly determine the sensitivities in your model
Before history matching a model, it is often useful to find the sensitivity of the model to individual parameters.
MEPO gives you the tools to do this efficiently. Experimental Design Matrices (EDM) can easily be generated and used to understand the effect of the uncertainty parameters. Pareto plots and line plots help you quickly analyse the results to establish the importance of a parameter. This will allow you to effectively select the dominant uncertainty parameters and eliminate unresponsive parameters from the history matching process.
Such studies give you confidence that a history matching solution exists within the range of parameters you have defined. It is also a good method to find starting points for the history matching process; alternatively you can use an engineering best guess.
Reducing uncertainty: improving reserve estimates
EDM techniques are frequently used to obtain an understanding of the possible range of hydrocarbons in place and the range of recoverable hydrocarbons. This is a guide based on the range of possible input parameters. There is no link to production data. In an exploration scenario this is a very useful guide.
However, in a field with production data it is possible to reduce the level of uncertainty. The EDM range has many combinations which, while theoretically possible, must be rejected as they do not match the historical production data.
MEPO is able to generate multiple scenarios (history matched models). This collection of models provides a range of hydrocarbons in place and a range of recoverable reserves that agree with the production data and are therefore possible. This reduces the range and the subsequent uncertainty.
For published examples of workflows illustrated with case studies see MEPO articles and publications.