Abstract: Systems and methods for generating permeability scaling function for different features of interest are disclosed. Exemplary implementations may: obtain subsurface data sets; generate permeability scaling functions for individual features of interest; store the permeability scaling functions; and generate upscaled subsurface distributions using the permeability scaling functions.

Abstract: Systems and methods for generating permeability scaling function for different features of interest are disclosed. Exemplary implementations may: obtain subsurface data sets; generate permeability scaling functions for individual features of interest; store the permeability scaling functions; and generate upscaled subsurface distributions using the permeability scaling functions.

Abstract: Embodiments of a method of pore type classification for petrophysical rock typing are disclosed herein. In general, embodiments of the method utilize parameterization of MICP data and/or other petrophysical data for pore type classification. Furthermore, embodiments of the method involve extrapolating, predicting, or propagating the pore type classification to the well log domain. The methods described here are unique in that: they describe the process from sample selection through log-scale prediction; PTGs are defined independently of the original depositional geology; parameters which describe the whole MICP curve shape can be utilized; and objective clustering can be used to remove subjective decisions. In addition, the method exploits the link between MICP data and the petrophysical characteristics of rock samples to derive self-consistent predictions of PTG, porosity, permeability and water saturation.

Abstract: Embodiments of a method of pore type classification for petrophysical rock typing are disclosed herein. In general, embodiments of the method utilize parameterization of MICP data and/or other petrophysical data for pore type classification. Furthermore, embodiments of the method involve extrapolating, predicting, or propagating the pore type classification to the well log domain. The methods described here are unique in that: they describe the process from sample selection through log-scale prediction; PTGs are defined independently of the original depositional geology; parameters which describe the whole MICP curve shape can be utilized; and objective clustering can be used to remove subjective decisions. In addition, the method exploits the link between MICP data and the petrophysical characteristics of rock samples to derive self-consistent predictions of PTG, porosity, permeability and water saturation.

Abstract: Disclosed are various embodiments of a workflow or method for petrophysical rock typing of carbonates in an oil or gas reservoir or field comprising determining a Data Scenario (DS) for the reservoir or field, determining a plurality of Depositional Rock Types (DRTs) for the reservoir or field, determining a Digenetic Modification (DM) from a plurality of diagenetic modifiers or primary textures associated with the plurality of DRTs, selecting a Reservoir Type (RT) corresponding to the plurality of DRTs, determining at least one pore type, and determining, on the basis of the plurality of DRTs, the Diagenetic Modification (DM), and the at least one pore type, a plurality of Petrophysical Rock Types (PRTs) associated with the RT.

Abstract: Disclosed are various embodiments of a workflow or method for petrophysical rock typing of carbonates in an oil or gas reservoir or field comprising determining a Data Scenario (DS) for the reservoir or field, determining a plurality of Depositional Rock Types (DRTs) for the reservoir or field, determining a Digenetic Modification (DM) from a plurality of diagenetic modifiers or primary textures associated with the plurality of DRTs, selecting a Reservoir Type (RT) corresponding to the plurality of DRTs,determining at least one pore type, and determining, on the basis of the plurality of DRTs, the Diagenetic Modification (DM), and the at least one pore type, a plurality of Petrophysical Rock Types (PRTs) associated with the RT.