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Decline curve analysis (DCA) is a method for analyzing production decline and predicting the amount of hydrocarbon that can be produced comercially in a well/field. This prediction is important for further field development. Decline curve analysis by Arps (1945) is method that widely use in this industry. In the unconventional reservoir, the transient flow regime takes longer time compared to the conventional reservoir due to the very low permeability. Therefore, the Arp’s method would not be as accurate for estimating production decline as well as Estimated Ultimate Recovery (EUR). Valkó dan Lee (2010) proposed Stretched Exponential Production Decline (SEPD) to better represent the production and decline behavior on unconventional reservoir. Telisa Sandstone in Srikandi Field was proven to be a hydrocarbon bearing zone. The evidence of the hydrocarbon can be seen from the drilling result in the form of gas chromatograph and oil show in the cutting description. Telisa Sandstone faced challenges in its development as it has a very small permeability of around 1 mD. This formation cannot be produced without stimulation. The most suitable stimulation for this formation is hydraulic fracturing. Determining reserves using DCA has uncertainties. This uncertainties increase with reservoirs that have low permeabilities values, this is because reservoirs with low permeability have relatively longer transient period. To solve this problem, a probabilistic approach is needed to quantify the uncertainties. Quantile regression as a probabilistic approach used to determine distribution of SEPD parameters and estimating reserves by considering uncertainty. This thesis compares the performance of conventional DCA with the Stretched Exponential Production Decline to estimate the production decline and EUR using probabilistic approach in Telisa Sandstone in Srikandi Field. SEPD method may represent the production behaviour of this tight reservoir.