New forecasting method for liquid rich shale gas condensate reservoirs with data driven approach using principal component analysis

This work shows that multivariate statistics and data driven methods can be used as an important approach to complement existing tools like reservoir simulation and decline curve analysis to perform production data analysis. PCA can also be used and can generate accurate results relatively quickly. We recognize that even more rapid approximate methods will be required for routine analysis. Understanding the limitations of different approximate methods and application of methods to overcome these limitations in given circumstances should lead to optimal use of these methods.