A new approach to production data analysis of non-volumetric naturally fractured gas condensate reservoirs

Abstract

A significant amount of hydrocarbon exists in naturally fractured formations. Due to the limitations of classical reservoir evaluation methods, the ongoing researches have focused on the analysis of production data to describe reservoir dynamic. Among the existing methods, the flowing material balance (FMB) technique brings a straightforward and accurate method of reserve estimation. Often, the same approach as the single porosity reservoirs are utilized for naturally fractured formations and fewer studies have been performed with the dual-porosity model. Regarding the importance of such reservoir types, the purpose of this study is to propose a new production data analysis approach by implication of a modified compressibility parameter to the conventional FMB equations to achieve an accurate estimation of initial gas in place and average reservoir pressure in non-volumetric naturally fractured gas condensate reservoir. In the current study, we applied the aquifer influence on reservoir performance in the FMB equation by a modified isothermal rock compressibility factor, without using complex multi-phase reservoir modeling. Due to inherent uncertainty associated with aquifer parameters, the production data analysis in this study proceeded in two phases. In the first phase with the assumption of known aquifer parameters, output data were obtained. In the second phase, based on the best-fitted aquifer parameters in advance, the impact of variation of aquifer input data on the validity of output results was studied using the Monte-Carlo simulation approach. To validate the proposed method, different simulation models with variable reservoir and fluid properties were defined and the results were compared against a commercial compositional simulator. The obtained results proved the accuracy of the proposed method. Therefore, applying the modified rock compressibility in the conventional FMB method would result in a simple yet accurate method that requires the least input data to estimate initial gas in place and average reservoir pressure.