Curve-fitting models for fossil fuel production forecasting: Key influence factors

摘要: Abstract Curve-fitting models are an approach that is frequently used in long-term production projections of fossil fuels. However, this has been criticized for inconsistent and diverging results. This study identifies four key factors influence the results such (i.e., ultimate recoverable resources (URR), curve shape, number cycles maximum depletion rate) theoretically analyzes influences these on model Additionally, case studies Chinese fuel modelled to empirically investigate The empirical analysis indicates use curve-fitting produce endogenous URR estimate should be avoided. even with well-founded exogenous estimates, applied shape can greatly Multi-cyclic a good fit historical data but often create high peak levels post-peak decline rates caution. Limiting rate could prevent attainment mathematically optimal practically unreasonable Because importance factors, type expected present more consistent conclusions if they reflect comprehensive consideration all factors.