Critical decision making with limited information and associated uncertainties is a challenge at every level of the hydrocarbon value chain. This is even more so at early stages of field development projects when geosciences and engineering data are sparse and the understanding of the geological complexities is still limited. Thus, the need for building multiple realizations of representative reservoir models that captures the full range of subsurface uncertainties is crucial to ensure a robust decision-making process.From previous studies, the Reservoir Complex, X is highlighted as a stack of two gas-bearing reservoirs that merge to form a doublet as observed on seismic and share a common contact towards the flank of the structure. This interpretation informed the modelling of both reservoirs as a single mega unit. An Integrated Reservoir Modeling approach rather than a discipline-focused one was adopted to evaluate the range of uncertainties in the reservoirs. For this study, a multidisciplinary subsurface team built a scenario-based model and performed Sensitivity analysis to identify key uncertainties on input parameters that are most impactful on in-place volumes and recoverables.This paper discusses techniques employed in building the static/dynamic models, generating estimates for the various uncertainties and how these were analyzed to identify the 'heavy hitters'. Results from this study identified Structure, Net-to-Gross and Porosity as the top three uncertainties with most impact on static volumes while Structure, PVT and Aquifer size have most impact on recoveries.Deterministic low, base and high case In-place volumes computed are 509, 627 and 769 BScf while recoveries were 182, 339 and 643BScf respectively. Probabilistically, the in-place volumes were 336, 480 and 634 Bscf while the recoverables were 205, 348 and 550 Bscf respectively.