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Description:
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This study proposes a new , easily applied method to quantify uncertainty in production forecasts for a volumetric gas reservoir based on a material balance model (p /z vs . Gp ) . The new method uses only observed data and mismatches between regression values and observed values to identify the most probable value of gas reserves . The method also provides the range of probability of values of reserves from the minimum to the maximum likely value . The method is applicable even when only limited information is available from a field . Previous methods suggested in the literature require more information than our new method . Quantifying uncertainty in reserves estimation is becoming increasingly important in the petroleum industry . Many current investment opportunities in reservoir development require large investments , many in harsh exploration environments , with intensive technology requirements and possibly marginal investment indicators . Our method of quantifying uncertainty uses a priori information , which could come from different sources , typically from geological data , used to build a static or prior reservoir model . Additionally , we propose a method to determine the uncertainty in our reserves estimate at any stage in the life of the reservoir for which pressure -production data are available . We applied our method to San Juan reservoir at Santa Rosa Field , Venezuela . This field was ideal for this study because it is a volumetric reservoir for which the material balance method , the p /z vs . Gp plot , appears to be appropriate . |