This study accommodates subsurface uncertainties analysis and quantify the effects on surface production volume as to
propose the optimal future field development. The problem of well productivity is sometimes only viewed from the
surface components themselves, where in fact the subsurface component often has a significant effect on these
production figures. In order to track the relationship between surface and subsurface, a model that integrates both must
be created. The methods covered integrated asset modeling, probabilistic forecasting, uncertainty quantification, and
sensitivity analysis. Subsurface uncertainties examined were: reservoir closure, regional segmentation, fluid contact,
and SCAL properties. As the Integrated Asset Modeling is successfully conducted and several cases of production
probability forecasting are obtained, up to Âħ75% of reservoir uncertainty range variable value conducted yields various
of production forecasting with the best probabilistic case obtained for âKâ Field is 176.6 - 254.4 BSCF gas production
and 273.7 â 329.5 MSTB oil production. The main five reservoir uncertainty that affects gas and oil production of the
field are: Corey curvature (Ng), relative permeability of gas (Krg), oil-to-water critical saturation (Sowcr), gas-to-oil critical
saturation (Sogcr), and pseudo-fault. As condensate production is highly possible to occur and gives the NPV a significant
effect, EOS and rock compressibility modeling must be evaluated in detail. A production scenario for future
development with up to 151.58 BSCF gas and 414.4 MSTB oil that yields a NPV of 102.6 MMUSD is proposed. The
approach and methods implemented has been proven to acquire the more accurate production forecast and reduce the
project cost as the effect of uncertainty reduction.