Infinite Rock Typing: A Paradigm Shift in Clastic Reservoir Modelling

This paper presents a paradigm shift in clastic reservoir modelling through the Infinite Rock Typing (IRT) framework. Traditional rock typing methods—such as Vshale cutoffs and machine learning clustering—often result in oversimplification, subjective interpretation, and statistical bias, introducing significant uncertainty into petrophysical models.

The IRT approach eliminates the need for discrete rock classes by enabling direct application of Choo’s predictive permeability and saturation height function (SHF) equations across the reservoir model. These equations, validated using core and log data at the well level, are then used to dynamically compute permeability and water saturation throughout the 3D model using petrophysical inputs like porosity and Vshale.

Field applications across diverse clastic settings demonstrate improved consistency, reduced cycle time, and enhanced uncertainty quantification. IRT has been integrated into commercial modelling software as a guided workflow, supporting faster, more robust, and auditable reservoir characterization.

IRT offers a scalable, industry-ready solution for high-fidelity, uncertainty-aware petrophysical modelling.