A method for determining porosity of a part is provided. The method includes: determining scan data of the part, the scan data including data of a plurality of sequential segments; determining a background model for the part, the scan data, or both; and determining a bulk porosity based on a difference between the scan data and the background model.

A method and system for approximating a predicted three-dimensional imbibition phase saturation profile from a measured three-dimensional drainage phase saturation profile, a derived one-dimensional drainage phase saturation profile, a measured one-dimensional imbibition phase saturation profile using a trained machine-learning algorithm are disclosed. A method for training of the machine learning algorithm is also disclosed.

The present invention provides a method for estimating hydrocarbon saturation of a hydrocarbon-bearing rock from a resistivity log and a rock image. The image is segmented to represent either a pore space or solid material in the rock. An image porosity is estimated from the segmented image, and a corrected porosity is determined to account for the sub-resolution porosity missing in the image of the rock. A corrected cementation exponent of the rock is determined from the image porosity and the corrected porosity and is used to estimate the hydrocarbon saturation. A backpropagation-enabled trained model can be used to segment the image. A backpropagation-enabled method can be used to estimate the hydrocarbon saturation using an image selected from a series of 2D projection images, 3D reconstructed images and combinations thereof.

A method for determining porosity of a part is provided. The method includes: determining scan data of the part, the scan data including data of a plurality of sequential segments; determining a background model for the part, the scan data, or both; and determining a bulk porosity based on a difference between the scan data and the background model.

A method and apparatus for identifying porosity in a structure made by an additive manufacturing process in which a laser is scanned across layers of material to form the structure. Pyrometry data comprising images of the layers acquired during additive manufacturing of the structure is received. The pyrometry data is used to generate temperature data comprising estimated temperatures of points in the layers in the images of the layers. The temperature data is used to identify shapes fit to high temperature areas in the images of the layers. Conditions of the shapes fit to the high temperature areas in the images of the layers are identified. Outlier shapes are identified in the shapes fit to the high temperature areas in the images of the layers using the conditions of the shapes.

The present invention provides a method for estimating fluid saturation of a hydrocarbon-bearing rock from a rock image. The image is segmented to represent either a pore space or solid material in the rock. An image pore volume is estimated from the segmented image, and a corrected pore volume is determined to account for the sub-resolution pore volume missing in the image of the rock. An image-derived wetting fluid saturation of the rock is estimated using a direct flow simulation on the rock image and corrected for the corrected pore volume. A backpropagation-enabled trained model can be used to segment the image. A backpropagation-enabled method can be used to estimate the fluid saturation using an image selected from a series of 2D projection images, 3D reconstructed images and combinations thereof.

A method and a system are provided to prepare a plurality of cuttings or other rock fragments or other porous media, such as cuttings from a drilling interval or multiple intervals, for computer tomographic scanning at the same time. A method and system also are provided to allow organization of mass quantities of cuttings or other rock fragments obtained from intervals of a well to more accurately categorize the cuttings to assist selections thereof for more detailed digital rock analysis, such as using SEM and FIB-SEM systems, are provided. A method and system also are provided to allow characterization of facies occurrence frequency of a depth interval using drill cuttings or other rock fragments. Computerized systems, computer readable media, and programs for performing the methods are also provided.

The effect of a treatment on a rock sample or sub-sample extracted from the rock sample can be analyzed through computed tomography (CT). To determine the effect of a treatment of a rock sample or the sub-sample, pre-treatment and post-treatment CT images of the rock sample or the sub-sample are captured. Further, the pre-treatment CT images and post-treatment CT images of the rock sample or the sub-sample are compared based on one or more alignment markers added to the rock sample or the sub-sample. In some embodiments, pre-treatment and post-treatment CT scans of an extracted sub-sample provide higher-resolution information regarding the effect of the treatment. Further, pre-treatment and post-treatment CT scans of a rock sample with a restored sub-sample may be considered and may provide additional information regarding the effect of the treatment on the rock sample or the sub-sample.

Provided is a method for non-destructively measuring an electrode density and an electrode porosity of an electrode active material coated on an electrode base material using X-ray diffraction. According to the methods of the present invention, a value of I.sub.peak in parallel direction/I.sub.peak in perpendicular direction of the electrode active material is obtained by X-ray diffraction and an electrode density and an electrode porosity are calculated according to previously obtained correlations between the electrode density and I.sub.peak in parallel direction/I.sub.peak in perpendicular direction and between the electrode porosity and I.sub.peak in parallel direction/I.sub.peak in perpendicular direction.

Provided are techniques for developing a hydrocarbon reservoir that include: determining a reservoir model of a hydrocarbon reservoir that includes columns of gridblocks that represent a vertical segment of the reservoir; acquiring nano-images of a rock sample of the reservoir; determining, based on the nano-images, properties of an inorganic pore network and an organic pore network of the rock sample; generating a divided reservoir model of the reservoir that represents the inorganic and organic pore networks of the reservoir, including: for each of the columns of gridblocks, dividing each of the gridblocks of the column into: a water-wet gridblock associated with the properties of the inorganic pore network determined based on the nano-images; and an oil-wet gridblock associated with the properties of the organic pore network determined based on the nano-images; and generating, using the divided reservoir model, a simulation of the hydrocarbon reservoir.