Abstract: Disclosed are computer implemented techniques for conducting a fluid simulation of a porous medium. These techniques involve retrieving a representation of a three dimensional porous medium, the representation including pore space corresponding to the porous medium, with the representation including at least one portion of under-resolved pore structure in the porous medium, defining a representative flow model that includes the under-resolved pore structure in the representation, and constructing by the computer system fluid force curves that correspond to fluid forces in the under-resolved pore structure in the representation.

Abstract: Disclosed are computer implemented techniques for conducting a simulation of physical properties of a porous medium. The features include receiving a micro-CT 3D image that captures a representative elemental volume of the porous medium, the porous medium defined as having mineral types and fluid types with individual grains and grain to grain contacts, labeling the micro-CT 3D image as individual voxels according to mineral and fluid types and labeling the mineral type voxels as belonging to separated and fixed individual grains. The features also include transforming the labeled voxels into an unstructured conformal mesh representation for all grains and applying the unstructured conformal mesh representation to a parametric cohesive contact engine, with the parametric cohesive contact engine executing a parametric cohesive contact model that has an adjustable parameter, a critical separation ?0 conditioned according to consolidation level.

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: Disclosed are computer implemented techniques for conducting a fluid simulation of a porous medium. These techniques involve retrieving a representation of a three dimensional porous medium, the representation including pore space corresponding to the porous medium, with the representation including at least one portion of under-resolved pore structure in the porous medium, defining a representative flow model that includes the under-resolved pore structure in the representation, and constructing by the computer system fluid force curves that correspond to fluid forces in the under-resolved pore structure in the representation.

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: A system and method for multi-phase segmentation of noisy 3D x-ray tomography images representative of porous material minimizing data smoothing which processes 3D x-ray tomography images to obtain a standardized intensity image, segments the standardized intensity image into at least 3 phases, calculates volumetric fractions and spatial distributions of the segmented phases and compares them with target values, and if the calculated fractions are not close enough to the target values, repeats the necessary segmentation steps until the calculated volumetric fractions are within a given tolerance to the target values. The segmentation steps include computing a median/mean-filtered-gradient image of the standardized intensity image, creating an intensity vs. gradient graph from the median/mean-filtered-gradient image and the standardized intensity image, partitioning the intensity vs.

Abstract: The present invention enables the use of a global optimization method for performing joint-inversion of multiple petrophysical data sets, using forward models based on first principle of physics, to generate a 3D rock representation of a subsurface rock structure. The resulting 3D rock representation captures the internal structure, and honors the measured petrophysical properties, of the subsurface rock structure. The 3D rock representation can then be used to predict additional properties not considered in the inversion, to further characterize the subsurface rock structure.

Abstract: A system and method for multi-phase segmentation of noisy 3D x-ray tomography images representative of porous material minimizing data smoothing which processes 3D x-ray tomography images to obtain a standardized intensity image, segments the standardized intensity image into at least 3 phases, calculates volumetric fractions and spatial distributions of the segmented phases and compares them with target values, and if the calculated fractions are not close enough to the target values, repeats the necessary segmentation steps until the calculated volumetric fractions are within a given tolerance to the target values. The segmentation steps include computing a median/mean-filtered-gradient image of the standardized intensity image, creating an intensity vs. gradient graph from the median/mean-filtered-gradient image and the standardized intensity image, partitioning the intensity vs.

Abstract: The present invention enables the use of a global optimization method for performing joint-inversion of multiple petrophysical data sets, using forward models based on first principle of physics, to generate a 3D rock representation of a subsurface rock structure. The resulting 3D rock representation captures the internal structure, and honors the measured petrophysical properties, of the subsurface rock structure. The 3D rock representation can then be used to predict additional properties not considered in the inversion, to further characterize the subsurface rock structure.

Abstract: A computer-implemented method enables a proton density distribution to be obtained. In one embodiment, the method comprises acquiring nuclear magnetic resonance data from porous media; inverting the nuclear magnetic resonance data via a global optimization algorithm to determine a proton density distribution within the porous media; and outputting the determined proton density distribution.