In recent years, improving the accuracy of production forecast in unconventional reservoirs has been of growing interest to oil and gas industries. Decline curve analysis (DCA) models have been recognized as the most efficient and easiest approaches to estimate gas rate. However, fluid flow regime and well rate decline curves are highly affected by the geological properties of formations. Therefore, the selection of DCA models based on completion designs and geological properties of formations is important for production rate prediction.

Traditional DCA methods, particularly Arps' decline model, was originally developed for predicting boundary dominated hydrocarbon well rate decline, which differs from the dominant long-duration transient flow regime in shale reservoirs. The Stretched Exponential model, the Duong model, the Arps model with a minimum terminal decline rate and the scaling method by Patzek were developed to match and forecast wells with transient flow followed by boundary dominated flow (BDF). In this paper, firstly we developed a new model to estimate production in shale gas reserviors by considering both Knudsen diffusion of bulk gas and surface diffusion of adsorbed gas based on the traditional equation of rate versus square-root-of-time. This proposed model can provide better fits to data in transient linear flow regimes. In addition, a systematic analysis of numerical simulation cases in CMG were performed to compare with the traditional model.

The results demonstrated that, in most cases, our model which is demonstrated in this paper, provide more accurate estimation of reserves for numerically simulated cases compared with the traditional decline methods. Therefore, the work offers critical insights into evaluating production in shale gas reserviors in a more efficient way.

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