Oil and gas reserve appreciation, or growth, is a phenomenon important to petroleum exploratory and producing companies. If well understood, the companies will improve their reserves projection into the future. Each field presents a particular appreciation that depends on various factors that move resources from an initial classification into proved reserve-classification. This thesis proposes a methodology for determining oil and gas reserves appreciation based on historical time series data from similar fields, calculating year to year average appreciation, and associating to each average a confidence interval. Two models were selected for adjustment (logarithmic and hyperbolic) both presenting monotonic non- increasing year to year growth. The logarithmic model presented better adjustment to a limited data-set but hyperbolic should not be discarded both because it has desirable features and may produce better future projections. The difficulties in obtaining adequate real historical data, and other kinds of information on reserves time series impeded further statistical analysis.