Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (6/6 displayed)

  • 2018Digital core laboratorycitations
  • 2012Qualitative and quantitative analysis of three-phase distributions of oil, water and gas in Bentheimer sandstone using micro-CT imagingcitations
  • 2010Tomographic image analysis and processing to simulate micro-petrophysical experiments5citations
  • 2008A comparison of pore structure analysis by NMR and Xray-CT techniquescitations
  • 2005Mechanical and transport properties of polymeric foams derived from 3D images40citations
  • 2004Polymeric foam properties derived from 3D images15citations

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Chart of shared publication
Pinczewski, W. V.
2 / 2 shared
Sok, R. M.
3 / 3 shared
Knackstedt, M. A.
5 / 6 shared
Sheppard, Adrian
4 / 13 shared
Averdunk, H.
1 / 1 shared
Sakellariou, A.
3 / 3 shared
Bauget, F.
1 / 1 shared
Knackstedt, M.
1 / 1 shared
Cinar, Y.
1 / 2 shared
Feali, M.
1 / 1 shared
Francois, N.
1 / 1 shared
Arns, Ji Youn
1 / 2 shared
Turner, M.
1 / 4 shared
Varslot, T. K.
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Meleán, Y.
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Saadatfar, Mohammad
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Schrof, W.
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Steininger, H.
1 / 2 shared
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Co-Authors (by relevance)

  • Pinczewski, W. V.
  • Sok, R. M.
  • Knackstedt, M. A.
  • Sheppard, Adrian
  • Averdunk, H.
  • Sakellariou, A.
  • Bauget, F.
  • Knackstedt, M.
  • Cinar, Y.
  • Feali, M.
  • Francois, N.
  • Arns, Ji Youn
  • Turner, M.
  • Varslot, T. K.
  • Meleán, Y.
  • Saadatfar, Mohammad
  • Schrof, W.
  • Steininger, H.
OrganizationsLocationPeople

document

Tomographic image analysis and processing to simulate micro-petrophysical experiments

  • Sok, R. M.
  • Knackstedt, M. A.
  • Sheppard, Adrian
  • Varslot, T. K.
  • Arns, C. H.
  • Sakellariou, A.
Abstract

<p>We present a description of our departments work flow that utilises X-ray micro-tomography in the observation and prediction of physical properties of porous rock. These properties include fluid flow, dissolution/deposition, fracture mapping, and mechanical processes, as well as measurement of three-dimensional (3D) morphological attributes such as pore/grain size and shape distributions, and pore/grain connectivity. To support all these areas there is a need for well integrated and parallel research programs in hardware development, structural description and physical property modelling. Since we have the ability to validate simulation with physical measurement, (and vice versa), an important part of the integration of all these techniques is calibration at every stage of the work flow. For example, we can use high-resolution scanning electron microscopy (SEM) images to verify or improve our sophisticated segmentation algorithm based on image grey-levels and gradients. The SEM can also be used to obtain sub-resolution porosity information estimated from tomographic grey-levels and texture. Comparing experimental and simulated mercury intrusion porosimetry can quantify the effective resolution of tomograms and the accuracy of segmentation. The foundation of our calibration techniques is a robust and highly optimised 3D to 3D image-based registration method. This enables us to compare the tomograms of successively disturbed (e.g., dissolved, fractured, cleaned,...) specimens with an original undisturbed state. A two-dimensional (2D) to 3D version of this algorithm allows us to register microscope images (both SEM and quantitative electron microscopy) of prepared 2D sections of each specimen. This can assist in giving a multimodal assessment of the specimen.</p>

Topics
  • Deposition
  • porous
  • impedance spectroscopy
  • pore
  • grain
  • grain size
  • scanning electron microscopy
  • experiment
  • simulation
  • tomography
  • texture
  • two-dimensional
  • porosity
  • porosimetry
  • Mercury