Diagenesis makes complex carbonate complex.
Classifying the rock types in any complex carbonate reservoirs is very hard.
Rock typing is a clustering of rocks that have the similar geological and petrophysical properties at core and log scale.
It's like trying to group your rock favorite rock bands into a specific rock genre categories. Some are easy to classify, but some are not that clear.
For instance, Metallica is a metal band. What about Queen? What about System of A Down? Dave Matthews Band? Avril Lavigne? Oasis? K.I.S.S.? ACDC? Puddle of Mud? Arctic Monkeys? Maroon Six?
You get the point.
The more complex the music, the harder for us to put them into clear rock categories.
So, when people have complex carbonate, which one do you choose?
Most people would take either one of these three methods of rock typing.
- Geological rock typing – mostly using depositional facies
- Petrophysical rock typing – mostly using conventional measurements like porosity, permeability, grain density or SCAL data
- Production driven rock typing – mostly using large scaly dynamic data
Each of the method works well individually. But they suffer one inherent problem: They represent different reservoir scales. When you want to propagate and upscale the rock typing, then the headache comes in.
So, what's the best method?
You integrate them all.
Geological rock typing
Petrophysical rock typing
Phi-K Based Clustering
- Flow Zone Indicator (FZI) and Reservoir Quality Index (RQI)
- Cutoff Based Clustering
Capillary Pressure (Pc) Clustering
- Windland/Pittman R35
- Leverett J Function
- Thomeer Function
- Wooddy-Wright-Johnson (WWJ) method
Logs Clustering Method
Dynamic clustering method
Dynamic Rock Types
An Integrated Approach
Static Rock Types