Abstract:
An example method includes acquiring two-dimensional (2D) or three-dimensional (3D) digital images of a rock sample. The method also includes iteratively analyzing property measurements collected throughout the digital images using different subsample sizes to identify a property distribution convergence as a function of subsample size. The method also includes selecting a smallest subsample size associated with the property distribution convergence as a representative elementary area or volume for the rock sample.
Abstract:
An example method includes acquiring two-dimensional (2D) or three-dimensional (3D) digital images of a rock sample. The method also includes iteratively analyzing property measurements collected throughout the digital images using different subsample sizes to identify a property distribution convergence as a function of subsample size. The method also includes selecting a smallest subsample size associated with the property distribution convergence as a representative elementary area or volume for the rock sample.
Abstract:
Methods and systems for characterizing a wellbore depth interval from rock fragments, including a method that includes converting measurements of a bulk rock fragment sample and of individual rock fragment samples to a concentration percent, computing a normalization deviation for each of the individual rock fragment samples relative to the bulk rock fragment sample (said normalization deviation being derived from the concentration percent of the bulk and individual rock fragment samples) and ranking the individual rock fragment samples based on a corresponding normalization deviation. The method further includes selecting one or more individual rock fragment samples based on a corresponding ranking, characterizing the properties of the wellbore depth interval from which the bulk and individual rock fragment samples originated using measured properties of at least some of the selected individual rock fragment samples and presenting to a user the characterized wellbore depth interval.
Abstract:
Methods and systems for conditioning expanded porosity, including a method that includes creating a disconnected pore structure by reducing the pore sizes of a rock sample's scanned image, identifying expanded pores within the rock sample and generating an expanded pore image from the expanded pores. The method further includes combining the expanded pore image with the scanned image to create an expansion mask, generating a grain conditioning volume based on at least one unexpanded region of the rock sample, combining the grain conditioning volume with the expansion mask to generate a fill volume image, combining the fill volume image with the scanned image to create an unexpanded volume image, and generating and presenting to a user a formation log using a model generated based upon the unexpanded volume image.
Abstract:
A method for determining fabric and upscaled properties of a geological sample, such as a rock sample. A system for the method also is provided.
Abstract:
An example method includes acquiring two-dimensional (2D) or three-dimensional (3D) digital images of a rock sample. The method also includes selecting a subsample within the digital images. The method also includes deriving a trend or petrophysical property for the subsample. The method also includes applying the trend or petrophysical property to a larger-scale portion of the digital images.
Abstract:
An example method includes acquiring two-dimensional (2D) or three-dimensional (3D) digital images of a rock sample. The method also includes selecting a subsample within the digital images. The method also includes deriving a trend or petrophysical property for the subsample. The method also includes applying the trend or petrophysical property to a larger-scale portion of the digital images.
Abstract:
Methods and systems for characterizing a wellbore depth interval from rock fragments, including a method that includes converting measurements of a bulk rock fragment sample and of individual rock fragment samples to a concentration percent, computing a normalization deviation for each of the individual rock fragment samples relative to the bulk rock fragment sample (said normalization deviation being derived from the concentration percent of the bulk and individual rock fragment samples) and ranking the individual rock fragment samples based on a corresponding normalization deviation. The method further includes selecting one or more individual rock fragment samples based on a corresponding ranking, characterizing the properties of the wellbore depth interval from which the bulk and individual rock fragment samples originated using measured properties of at least some of the selected individual rock fragment samples and presenting to a user the characterized wellbore depth interval.
Abstract:
Methods and systems for conditioning expanded porosity, including a method that includes creating a disconnected pore structure by reducing the pore sizes of a rock sample's scanned image, identifying expanded pores within the rock sample and generating an expanded pore image from the expanded pores. The method further includes combining the expanded pore image with the scanned image to create an expansion mask, generating a grain conditioning volume based on at least one unexpanded region of the rock sample, combining the grain conditioning volume with the expansion mask to generate a fill volume image, combining the fill volume image with the scanned image to create an unexpanded volume image, and generating and presenting to a user a formation log using a model generated based upon the unexpanded volume image.