System and method of pore type classification for petrophysical rock typing

A system comprising:

• an interface for receiving a dataset for a plurality of core plugs from a reservoir, wherein the dataset comprises mercury injection capillary pressure (MICP) data, porosity, permeability, and grain density data for each core plug of the plurality of core plugs, and wherein a MICP data is acquired using a MICP device that houses each core plug of the plurality of core plugs in order to acquire the MICP data for the core plug;
• a memory resource;
• input and output functions for presenting and receiving communication signals to and from a human user;
• one or more central processing units for executing program instructions;
• and program memory, coupled to the one or more central processing units, for storing a computer program including program instructions that, when executed by the one or more central processing units, cause the computer system to perform a plurality of operations for pore type classification, the operations comprising:
• a) parametrizing the dataset using a Gaussian error function and the MICP data to derive a plurality of curve fit parameters, wherein the Gaussian error function comprises a formula comprising:
• V
• P
• c
• =
• V
• P
• ∞
• 2
• ⁢
• (
• 1
• +
• 2
• π
• ⁢
• ∫
• 0
• x
• ⁢
• e
• -
• t
• 2
• ·
• ⁢
• dt
• )
• where VPc is pore volume at a given capillary pressure and
• x
• =
• 1
• S
• ⁢
• log
• ⁡
• (
• P
• c
• P
• m
• )
• ,
• where S is a pore system shape factor, Pm is a modal pressure of the pore system, and Vp∞ is a bulk volume of the pore system;
• b) clustering the plurality of curve fit parameters to create one or more pore type groups for the plurality of core plugs with the MICP data;
• c) extrapolating the one or more pore type groups to a different plurality of core plugs without any MICP data;
• and
• d) extrapolating the one or more pore type groups of the plurality of core plugs with the MICP data and the different plurality of core plugs without any MICP data to a well log domain to classify a rock type from the reservoir, wherein the rock type is used to model the reservoir.

A non-transitory, computer readable medium having stored thereon instructions for pore type classification comprising machine executable code which when executed by at least one processor, causes the at least one processor to perform steps comprising:

• a) parametrizing a dataset for a plurality of core plugs from a reservoir using a Gaussian error function and mercury injection capillary pressure (MICP) data to derive a plurality of curve fit parameters, wherein the dataset comprises the MICP data, porosity, permeability, and grain density data for each core plug of the plurality of core plugs, wherein the MICP data is acquired using a MICP device that houses each core plug of the plurality of core plugs in order to acquire the MICP data for the core plug, wherein the Gaussian error function comprises a formula comprising:
• V
• P
• c
• =
• V
• P
• ∞
• 2
• ⁢
• (
• 1
• +
• 2
• π
• ⁢
• ∫
• 0
• x
• ⁢
• e
• -
• t
• 2
• ·
• ⁢
• dt
• )
• where VPc is pore volume at a given capillary pressure and
• x
• =
• 1
• S
• ⁢
• log
• ⁡
• (
• P
• c
• P
• m
• )
• ,
• where S is a pore system shape factor, Pm is a modal pressure of the pore system, and VP∞ is a bulk volume of the pore system;
• b) clustering the plurality of curve fit parameters to create one or more pore type groups for the plurality of core plugs with the MICP data;
• c) extrapolating the one or more pore type groups to a different plurality of core plugs without any MICP data;
• and
• d) extrapolating the one or more pore type groups of the plurality of core plugs with the MICP data and the different plurality of core plugs without any MICP data to a well log domain to classify a rock type from the subsurface reservoir, wherein the rock type is used to model the subsurface reservoir.