Modelling and forecasting the trends of life cycle curves in the production of non-renewable resources

In this study, we review mathematical models of trends in the production of non-renewable resources. We propose new models that allow specifying curve asymmetry and use genetic algorithms as curve-fitting methods. We estimate the quality of fit of our proposed models and use them to predict oil production in the OECD (Organisation for Economic Co-operation and Development) countries, the EU, the U.S., Norway, Syria, the UK, and some fields in Russia; gas production in the EU, the UK and Italy; shale gas production in the U.S.; coal production in the U.S. and Germany; as well as global gold production. The models fit the data accurately in all these cases. •We review well-known life cycle models for non-renewable resources production.•We propose combining these models with asymmetry managing functions.•Genetic algorithms are applied for parameter identification.•We study oil production in the OECD (Organisation for Economic Co-operation and Development), EU, US, Norway, Syria, and Russian wells.•We study gas, shale gas, coal, and gold production at national and global levels.