The Application of 3D Supervised Attributes in Facies Distribution as Input for Reservoir Modeling

Creating a facies model will help to guide the facies population in a 3D model, which in turn will impact the Hydrocarbon Initially In Place (HUP) calculation and the history match (HM) of the production from the existing producers. A properly calibrated facies model will also provide assurance on the well placement in an infill drilling campaign. Part of the main input in creating a facies model is to have good trend came from seismic attributes. This paper discusses on utilizing the seismic pre stack and well data as training set, creating a supervised volume attribute that quantitatively reproduce petrophysical properties or geological facies variations within the reservoir.