Initial water saturation (Swi) in a gas reservoir is an important parameter for inplace resource (GIIP) and ultimate reserve estimation, which in turn impacts the economic decision. Swi estimation in a low resistivity deep-water clastic reservoir is more challenging because limited well data in less number of (costly) appraisal wells in a large area. Conventionally, Swi is computed from open hole logs and validated with core plug data to reduce the range of uncertainty in estimation. But this standard methodology fails when resistivity log derived Swi shows a variance with the saturation measured from the core plugs and increases the range of uncertainty. Sometimes, log derived Swi shows high water saturation in the gas bearing interval due to low anomalous resistivity which is beyond correction.
Saturation height modelling is an age old solution for this sort of problem and the same was attempted first to estimate Swi. But single saturation height function does not represent all the rock types of the reservoir and replicate log derived Swe curve. Petrophysical rock typing was carried out using porosity and permeability from the core plug in the first step and then by using the concept of flow zone index (FZI) and rock quality index (RQI). FZI-RQI based rock types were able to characterize the reservoir in a better way in 3D-Geologic model and also able to separate the different behaviours of Capillary pressure curves.
Two saturation height functions were made after characterizing good rock and poor rock type, which were tested in the dynamic model for flow simulation and recovery factor estimation successfully. This innovative concept of FZI-RQI based petrophysical rock typing (PRT) and saturation height modelling finally added value to recreate the Swi curve against the low resistivity pay interval and to reduce the range of uncertainty in Sw estimation.