Prediction of pore pressure and porosity in an unconventional resource assessment area of Abu Dhabi was performed by using petroleum systems modeling techniques, combining seismic and well data and geological knowledge to model sedimentary basin evolution. The study objective was ultimately to reconstruct basin history and key geological structures as a basis for further geomechanical and fracture prediction studies. Twelve surfaces were interpreted from seismic data and derived from isopach maps. These maps were used to construct the basin model. The model was built from the top of the surface sediment down to the Shuaiba formation. Sediment decompaction was modeled, which enabled the reconstruction of the formation structures through time. Athy's law, formulated with effective stress, was used in the forward modeling simulator for the calculation of pore pressure. Information such as formation ages, erosional events, and hiatus periods were taken into account during simulation. The evolution of porosity, pore pressure, temperature, and thermal maturity through time were simulated and calibrated to measured data. Model porosity is dependent on burial depth, weight of the overburden sediment columns, and lithology properties. Porosity calibration was achieved by adjusting the compaction curve to effective stress. Pore pressure was calibrated by adjusting lithology porosity-permeability relationships. Lowpermeability lithologies result in high pore pressure. A regional Paleocene pore pressure reduction was observed, caused by substantial erosion of the Simsima formation. Generally, formation overpressure is observed at greater depth. Additionally, modeled overpressures depend on the evolution of connate water vectors over geological time; these vectors depend on multiple lithology parameters as well as the capillary entry pressure of adjacent model layers. In the Shilaif fm, overpressure zones were identified at the anticlinal structures. Interestingly, higher overpressure was observed in the shallower anticlinal structure. The simulation results provide the estimated porosity and pore pressure in the unconventional play, as well as the reconstruction of the overall basin geometry through time. The resulting models were subsequently used as the basis for further fracture prediction studies; results were ultimately consistent with faults derived from existing seismic interpretation. Model porosity, pore pressure, and predicted fractures will be used for the development of static geological and dynamic reservoir models.

The Brage field was discovered in 1980 and started production from its Fensfjord reservoir in 1993. The Fensfjord Fm. is a highly heterogeneous reservoir with low STOIIP density. Lack of zonal control and several drainage strategies throughout the years make production allocation and drainage history very complex. Thus, achieving a full field history match in the Fensfjord reservoir through deterministic modeling has always been a challenge. Current STOIIP estimates indicate that there is room for several more producers. However, identification of target areas for future wells are associated with high uncertainties. Using advanced stochastic modeling and ensemble-based methods has reduced the uncertainties and thereby improved the history match quality and understanding of the reservoir. Bayesian statistical methods have been applied to combine the structural and well path TVD uncertainties, and generate multiple realizations of the top reservoir surface, isochores and well trajectories, serving as additional history matching parameters. Based on this input, an ensemble of static models was iteratively conditioned to the dynamic data resulting in a significant improvement of the history match quality. Sensitivity analysis have been performed to identify and breakdown the impact of the uncertain parameters on the in-place volumes. This paper shows how the new integrated approach has increased the predictive power of the model, resulting in identification of several infill targets for future drilling campaigns.