Articles | Volume 7, issue 2
https://doi.org/10.5194/se-7-481-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/se-7-481-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
30 Mar 2016
Research article |
| 30 Mar 2016
Multi-phase classification by a least-squares support vector machine approach in tomography images of geological samples
Faisal Khan
Geoscience Institute, Johannes Gutenberg University, Mainz 55099, Germany
Geoscience Institute, Johannes Gutenberg University, Mainz 55099, Germany
Michael Kersten
Geoscience Institute, Johannes Gutenberg University, Mainz 55099, Germany
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- Phase segmentation of X-ray computer tomography rock images using machine learning techniques: an accuracy and performance study S. Chauhan et al. 10.5194/se-7-1125-2016
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- Machine-Learning-Assisted Segmentation of Focused Ion Beam-Scanning Electron Microscopy Images with Artifacts for Improved Void-Space Characterization of Tight Reservoir Rocks A. Kazak et al. 10.2118/205347-PA
- Review of Data Science Trends and Issues in Porous Media Research With a Focus on Image‐Based Techniques A. Rabbani et al. 10.1029/2020WR029472
- Modern approaches to pore space scale digital modeling of core structure and multiphase flow K. Gerke et al. 10.18599/grs.2021.2.20
- An efficient reliability method combining adaptive Support Vector Machine and Monte Carlo Simulation Q. Pan & D. Dias 10.1016/j.strusafe.2017.04.006
- Generation of ground truth images to validate micro-CT image-processing pipelines S. Berg et al. 10.1190/tle37060412.1
- Benchmark study using a multi-scale, multi-methodological approach for the petrophysical characterization of reservoir sandstones P. Haruzi et al. 10.5194/se-12-665-2021
- Petrophysical Properties of Opalinus Clay Drill Cores Determined from Med-XCT Images L. Keller & S. Giger 10.1007/s10706-019-00815-2
- Digital Rock Physics: A Geological Driven Workflow for the Segmentation of Anisotropic Ruhr Sandstone M. Balcewicz et al. 10.3389/feart.2021.673753
- Simulating permeability reduction by clay mineral nanopores in a tight sandstone by combining computer X-ray microtomography and focussed ion beam scanning electron microscopy imaging A. Jacob et al. 10.5194/se-12-1-2021
- Pore-scale tomography and imaging: applications, techniques and recommended practice M. Halisch et al. 10.5194/se-7-1141-2016
8 citations as recorded by crossref.
- In Situ Local Contact Angle Measurement in a CO2–Brine–Sand System Using Microfocused X-ray CT P. Lv et al. 10.1021/acs.langmuir.6b04533
- Optimization of pixel size and propagation distance in X-ray phase-contrast virtual histology S. Donato et al. 10.1088/1748-0221/17/05/C05021
- Morphological and Euler characteristics of nonwetting phases in porous media P. Lv et al. 10.1063/5.0132936
- Reducing User Bias in X-ray Computed Tomography-Derived Rock Parameters through Image Filtering E. Thompson et al. 10.1007/s11242-021-01690-3
- Pore‐Scale Imaging and Analysis of Phase Topologies and Displacement Mechanisms for CO2‐Brine Two‐Phase Flow in Unconsolidated Sand Packs P. Lv et al. 10.1002/2016WR020270
- Integrating X-ray phase-contrast imaging and histology for comparative evaluation of breast tissue malignancies in virtual histology analysis S. Donato et al. 10.1038/s41598-024-56341-6
- Pore‐scale investigation of effects of heterogeneity on CO2 geological storage using stratified sand packs P. Lv et al. 10.1002/ghg.1702
- Experimental and numerical investigations on the effect of fracture geometry and fracture aperture distribution on flow and solute transport in natural fractures M. Stoll et al. 10.1016/j.jconhyd.2018.11.008
Latest update: 21 Nov 2024
Short summary
X-ray microtomography image processing involves artefact reduction and image segmentation. The beam-hardening artefact is removed, applying a new algorithm, which minimizes the offsets of the attenuation data points. For the segmentation, we propose using a non-linear classifier algorithm. Statistical analysis was performed to quantify the improvement in multi-phase classification of rock cores using and without using our advanced beam-hardening correction algorithm.
X-ray microtomography image processing involves artefact reduction and image segmentation. The...
