Conventional DCA methods, developed for boundary dominated flow (BDF), yield unrealistic values for expected ultimate recovery (EUR) when used for unconventional reservoirs with long-duration transient linear flow. Moreover, the developed model parameters are not functions of reservoir properties and flow mechanisms. Although new models have been developed over the years to predict the linear flow, there is still no good way to forecast long-term performance of gas condensate reservoirs.

In this study, we use decline curve analysis, reservoir simulation and statistical analysis to understand the flow of hydrocarbons in LRS reservoirs and to estimate the ultimate recovery in LRS gas condensate reservoirs accurately. Initially, a synthetic reservoir model was constructed to replicate a limited case history available for the Eagle Ford Shale. Various sensitivities on reservoir parameters and operating conditions were performed to understand their effect on oil and gas EUR's after 30 years of production using design of experiments (DOE) and response surface modelling (RSM). Various decline curve methods were applied to the synthetic data obtained by using pressure normalized diagnostic plots. Results from this study shows that pressure normalization could potentially be used to identify the flow regimes in LRS reservoirs, which is especially true for rate restricted fields. We also observed that the production characteristics of LRS gas condensate reservoirs are highly variable, possibly due to the change in composition via liquid dropout. The approach of using two or more models with different production parameters by isolating the parameters provides a good fit to the data and a realistic estimate of the EUR. Statistical analysis of the reservoir parameters and the EUR shows that there is some relationship among them. Our study shows that these statistically developed co-relations are accurate for the reservoir studied and EUR for other wells in the same field can be obtained with variation of parameters.

We present a methodology which uses empirical decline curve analysis, physics based reservoir simulation and statistical analysis to forecast EUR based on limited production data in LRS gas condensate reservoirs. This study provides considerable insight into the long-term production behavior in LRS gas condensate reservoirs.

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