An integrated understanding of static and dynamic issues is essential to generate an appropriate life cycle FDP. This abstract will highlight the power of such integration. First pass dynamic modeling gave very poor history match results. The model significantly under produced the historical gross volumes. Sensitivity analysis on the permeability multiplier, Kv/Kh, viscosity and relative permeability curves were utilized to improve the history match, however, the improvement was limited. Careful investigation showed that the main reason for the poor history match was the underestimation of permeability in apparently low porosity intervals. These previously unrecognized flow units also contributed to a high vertical heterogeneity. Further integration and analysis of various petrophysical data, combined with reservoir performance behavior, suggested that these additional flow units were conglomeratic intervals of different gravel sizes. These intervals are characterized by reduced bulk porosity because of the presence of low porosity pebbles in the otherwise highly permeable sandy matrix. Following this re-interpretation, a new realization of the conceptual depositional model, that incorporates the new litho-facies, was constructed. The static inputs were re-visited; however, due to the lack of core data, identification of the permeability range of the new litho-facies was complicated. This forced maximum utilization of the basic static/dynamic data and analogues. Analysis of borehole rugosity, oil saturation, reservoir performance and pressure data strengthened the adopted subsurface concept model. A recent core, taken from this reservoir, revealed the presence of conglomerates comprising hard clasts cemented by unconsolidated sands and thereby finally confirmed the interpretation. The updated models, with minor fine-tuning in dynamic parameters, showed a step change in the history match. This outcome confirmed the presence of high permeable facies despite the low porosity reading at these intervals. It can be concluded that the vertical heterogeneity, which is often overlooked, can cause complex issues in history match process. However, the better understanding of these features, through multidisciplinary approach, is the key to drive the right solution. Moreover, maximum utilization of the basic data can paint a picture beyond its anticipated frame. Despite the lack of core data, compiling the subsurface data through multidisciplinary integration provides a powerful tool to mitigate subsurface uncertainties.