Proper evaluation of any hydrocarbon reservoir requires knowledge of information such as hydrocarbon in place, recoverable reserve and average reservoir pressure. Production data analysis techniques are regarded as one of the best engineering tools for estimating reservoir parameters. These methods, which may be either empirical, semi analytical or analytical, are normally applied in a systematic manner to analyze well data. All methods (Empirical, semi analytical and analytical) use well production rate as the input data. The well pressure-rate data of specific wells are analyzed to determine reliable estimates of reservoir parameters and also to predict well production performance. This thesis categorizes existing methods and study strengths and drawbacks of each method. At first, the analysis was performed by using empirical methods. By applying different scenarios, the impact of different factors on data analysis was evaluated by empirical methods. The empirical methods donot extract all reservoir parameters. Next, analytical methods specific for single-phase reservoirs were used for gas condensate reservoirs. Because these types of model contain provisions of single phase, theirs use are limited. For this reason, a variety of different condensate fluid at different production scenarios were analyzed and same as empirical methods; by applying different scenarios, the impact of different factors on production data analysis were evaluated by using analytical techniques. Synthetic production data of this investigation is generated by Eclipse 300 software and production data analysis have been doing by RTA software. The method was extended to data of an Iranian offshore gas condensate reservoir.