Automatic Computing Model For Analyzing Production Data By Determining Different Flow Periods

In field development,production data analysis is crucial to formation evaluation and reservoir characterization.That provides assessment of important parameters such as reservoir permeability and formation damage skin for well deliverability forecasting,to improve the reservoir parameters and calculate these parameters of each flow periods.This thesis discusses "automatic computing model for analyzing production data by determining different flow periods" to interpret production data by identifying the flow periods automatically and calculate the parameters of each flow periods.This thesis also discusses the prediction of future well performance using RTA software.To evaluate the properties of reservoir are always tough job.It is very complex to use the conventional method to do that,especially for fully fractured well.Programming is a powerful tool in production data analysis for the flow periods division.The flow periods can be automatically identified and calculate the reservoir parameter(Permeability and skin factor)of each flow periods and accurately.Different type of curves used for prediction of future well performance,as well by numerical inversion algorithm,the flow periods and sensitive factors has analyzed.The source functions and solutions of fractured well have both theoretical and practical application in production data interpretation.Through the RTA Software,the Agarwal Gardner type curve and traditional decline curve analysis theory is compare with the model design through program.There are marginal differences between the results.Although the result of the programming model is more accurate as compare to other model.