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.