Thermo Scientific PerGeos Software version 2019.1 (released on March 2019) rolls out exciting new tools and enhancements. Read on for a quick introduction to these features and links to resources offering more information.

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Ridge enhancement filter

With PerGeos Software 2019.1, you can detect, highlight and enhance dark-to-bright and bright-to-dark transitions in an image. This filter can be used to obtain the pore and grain edges as separate phases.

Berea sandstone data with grain edges (purple) & pore edges (green) overlaid
Grain edges
Pore edges

Compute ambient occlusion

The ambient occlusion scalar field can be used for detection of cavities. Many natural objects contain pores and cavities that are filled with the same material that also surrounds the object. When such objects are imaged using computed tomography, the pores and cavities cannot be distinguished from the surrounding material by considering gray values and textural properties of the image. The ambient occlusion tool for the segmentation of pores and cavities is that it generates smooth scalar fields. Due to this smoothness property, a segmentation based on those fields will result in smooth boundaries at the pore and cavity openings.

PerGeos-Software_2019-1_ambient-occlusion_3_700x132.pngGrayscale CT image of a core (top). Ambient occlusion image of the core computed on the CT image (bottom).
PerGeos-Software_2019-1_ambient-occlusion_4Cavities and fractures segmented using the ambient occlusion image of the core.

Selective morphology operators

The selective morphology tools take into account the local binary values while performing opening, closing, dilation & erosion. Due to the local binary constraints, selective morphology can be robust to different datasets and hence these modules can make for excellent candidates to be part of recipes. Selective morphology can also be used to decide on pore-grain boundary pixels to recede or proceed while retaining the underlying shape of the pore or grain.

(from L-R) : Auto thresholded result for bright phase on the Barnett dataset. Regular dilation applied recursively 5 times with a kernel size of 5. Selective dilation applied 5 times recursively, 3 iterations each, with a threshold of 5.
(from L-R) : Auto thresholded result for bright phase on the Barnett dataset. Regular erosion applied recursively 5 times with a kernel size of 5. Selective erosion applied 5 times recursively, 3 iterations each, with a threshold of 5.

Intensity auto classification

The Intensity Auto Classification module is a non-supervised classification tool that performs an automatic segmentation of gray-scale and multi-channel images into a given number of classes. It is based on a k-means clustering algorithm.


Thin-section color image is automatically segmented into four phases using Intensity Auto Classification.
(Image courtesy of Weatherford Labs).

Recipe from multiple outputs

The functionality to create a recipe from multiple outputs is now available. A create recipe tool is introduced that enables you to provide multiple data files for generating a single recipe. You can now make a workflow with multiple output files, which may be generated through independent paths, into a single recipe, thus eliminating the need to run multiple recipes.


Recipes inside recipe

Complex digital rock analysis workflows consist of many steps that can be bundled into multiple categories. Some of these subsets of the workflow are often repeated and can be re-used in other workflows. A recipe inside a recipe functionality is introduced that enables you to include a recipe as a step of a new recipe.

Nuclear Magnetic Resonance (NMR)

The NMR tool simulates the decay of the magnetic resonance of the nuclei of hydrogen-1 atoms of the fluids in the pore-space of the rock. It uses the random walk technique. A multi-phase segmented image of the rock is used as input.

You can use this tool to compare the results of magnetic relaxation against the NMR logs acquired in the lab or downhole in the field. The NMR tool also provides an alternative method for characterizing the behavior of the pore-size distribution of your rock without performing pore-separation and individual label measurements.

Heterogeneity Logs

The Heterogeneity Logs tool is introduced in this release. This tool generates a number of logs based on the intensity histogram of the input grayscale image. You can specify the number of logs to be generated.

The generated logs are loaded as a single data file and displayed in the Core Profile workspace. The variations in the logs provide an insight into the amount of heterogeneity in the core.

Heterogeneity logs are generated based on variation in CT number
SPE paper SPE-183145-MS Integration and data analysis of conventional core data with NMR and CT data to characterize an evaporitic carbonate reservoir - Fitzsimons&Al, Wintershall
Heterogeneity logs are displayed alongside the CT image of the core in Core Profile.

The Python scripting API in PerGeos Software has been upgraded to Python 3.5.2. Python 2.7 support has been discontinued. Some compatibility issues exist between Python 2 and Python 3. The official Python documentation regarding porting to Python 3 can be found here

The following are some of the advantages of moving to this new version of Python:

  • Compatibility with Matplotlib and PyQt
  • OpenCV available in default packages list
  • New Deployment Manager (EDM) that allows fast creation of multiple self-contained Python environments

2019 introduces a new product life cycle

All customers with active maintenance will benefit of our quarterly release. This new product life cycle allows you to benefit of the best level of features and performance for increased productivity.

Customers with active maintenance at the time of the release will be automatically notified about the availability of the newest version.

Read the full release notes

What was new

PerGeos Software 1.8
Released on October 2018