Model Selection for Well Test and Production Data Analysis

The estimation of reservoir properties from production or pressure data measured during production or well tests is an important process for reservoir characterization and performance prediction. A key step in that process is the selection of a reservoir model for use in the interpretation of the data. The authors develop a procedure for selecting the most appropriate model from a pool of candidates. A parameter estimation algorithm is used to evaluate parameters within candidate models. Statistical measures are then used to select the most appropriate model. The authors demonstrate their procedure for model selection with actual well test data and production data from the Devonian shale. The authors show how their methodology can be used to evaluate whether certain reservoir features can be identified from measured production or pressure data. They also present a test for evaluating whether independent estimates of reservoir properties are consistent with measured pressure and production data.