Modeling of water saturation in carbonate reservoirs is a challenging task which becomes more difficult if the reservoir is highly affected by diagenesis processes. This paper addresses a robust water saturation modeling workflow that encompass multiple approaches followed to handle an onshore Abu Dhabi carbonate reservoir that have complex pore network. This covers a holistic reservoir petrophysical evaluation all the way to water saturation modeling for dynamic simulation studies. The studied reservoir was deposited in high energy shallow, water platform environment prevailing during Early Cretaceous time. It has a large areal extent with low average porosity and moderate to low average permeability. Considering the impact of porosity exponent (m) and water resistivity (Rw) on the water saturation evaluation, the workflow was adjusted to integrate all available log, core and well test data. By integrating the formation resistivity factor (FRF) at different net confining stress and petrography data, relationship for variable porosity exponent (m) versus porosity was developed. The salinity variation was observed across the field (east to west) from the well test and Pickett plot. In water saturation estimation, salinity taken from one side of the field (east/west) causes either under or overestimation of water saturation by 18% on the other side of the field which has a Considerable impact on the STOIIP. To address this problem, variable formation water resistivity (Rw) was generated from log data. This was validated using Porous Plate capillary pressure data measured using samples collected from different areas of the field. The destructive dolomitization at the bottom part of the reservoir resulted in the large transition zone and sporadic occurrence of poor lithofacies poses a great challenge in developing a saturation height function. The current case study also evaluates the best possible saturation height function which can explain the variability of water saturation across the field.

One of the reservoirs in a giant field in onshore Abu Dhabi has been producing for six decades. The reservoir was already saturated at the time of production commencement, with a large oil rim and a gas cap. Both water injection and lean gas injection have been relied upon to sustain production, and will play an even more prominent role for the future development of oil rim and gas cap. Due to the stakeholders’ different entitlements / equity interests in the hydrocarbons originally existed in oil rim area versus gas cap area, it is important to be able to allocate liquid hydrocarbon production and injection gas utilization among the stakeholders, based on a systematic framework. This paper presents a comprehensive comparison of two modeling-based approaches of fluid tracking for condensate allocation and gas utilization – a tracer modeling option in a commercial reservoir simulator, and a full component fluid tracking approach implemented for this reservoir. The component tracking approach is based on the idea that if individual components represented in a fully compositional reservoir model are tracked separately starting from model initialization, one can trace back the source of hydrocarbon production from both gas cap and oil rim. This approach is implemented through the doubling of the number of components in the equation of state fluid characterization – one set of components for the gas cap, and another set for the oil rim. In order to track the net utilization of the injected lean gas, additional components are needed – in this case one more component representing the lean gas, as the injected gas is a dry gas. The results of the comprehensive comparison demonstrate very clearly that these two approaches yield consistent condensate allocation and gas utilization results over the entire life of field (including history match and prediction). For condensate allocation, the hydrocarbon liquid production split depends on how the injected lean gas is tracked. For gas utilization, the injected lean gas must be tracked as a distinct component separate from both oil rim and gas cap components. The comparison also shows that although the tracer-based approach is numerically more efficient with less runtime, the full component tracking approach is simulator agnostic, and therefore can be implemented in any reservoir simulator. In addition, the full component tracking method can be used for cases where injection gas is a known mixture of oil rim and gas cap gas – something the tracer-based option cannot handle. In summary, this paper presents a first comprehensive comparison of the two (2) different fluid tracking modeling approaches, with practical recommendations on modeling-based hydrocarbon liquid production and injection gas utilization allocation in cases where the commercial framework makes such allocation necessary.