Abstract
Synchrotron-based fast micro-tomography is the method of choice to observe in situ multiphase flow and displacement dynamics on the pore scale. However, the image processing workflow is sensitive to a suite of manually selected parameters which can lead to ambiguous results. In this work, the relationship between porosity and permeability in response to systematically varied gray-scale threshold values was studied for different segmentation approaches on a dataset of Berea sandstone at a voxel length of 3 \(\upmu \)m. For validation of the image processing workflow, porosity, permeability, and capillary pressure were compared to laboratory measurements on a larger-sized core plug of the same material. It was found that for global thresholding, minor variations in the visually permissive range lead to large variations in porosity and even larger variations in permeability. The latter is caused by changes in the pore-scale flow paths. Pore throats were found to be open for flow at large thresholds but closed for smaller thresholds. Watershed-based segmentation was found to be significantly more robust to manually chosen input parameters. Permeability and capillary pressure closely match experimental values; for capillary pressure measurements, the plateau of calculated capillary pressure curves was similar to experimental curves. Modeling on structures segmented with hysteresis thresholding was found to overpredict experimental capillary pressure values, while calculated permeability showed reasonable agreement to experimental data. This demonstrates that a good representation of permeability or capillary pressure alone is not a sufficient quality criterion for appropriate segmentation, but the data should be validated with both parameters. However, porosity is the least reliable quality criterion. In the segmented images, always a lower porosity was found compared to experimental values due to micro-porosity below the imaging resolution. As a result, it is recommended to base the validation of image processing workflows on permeability and capillary pressure and not on porosity. Decane-brine distributions from a multiphase flow experiment were modeled in a thus validated \(\upmu \)-CT pore space using a morphological approach which captures only capillary forces. A good overall correspondence was found when comparing (capillary-controlled) equilibrium fluid distributions before and after pore-scale displacement events.
Highlights
X-ray micro-computed tomography (μ-CT) multiphase flow experiments are aimed at imaging the in situ fluid phase distributions in porous media (Wildenschild et al 2005; Silin et al 2010; Iglauer et al 2011; Setiavan et al 2012; Andrew et al 2014)
The influence of image segmentation on sequential pore space characterization and pore-scale modeling for multiphase flow must be thoroughly evaluated in further detail since the accuracy of the segmentation process determines how well the resulting binary image represents the “true” rock structure
The conclusion is that permeability and capillary pressure curves may still serve as a robust validation criterion, but it is important to look at multiple parameters at the same time
Summary
X-ray micro-computed tomography (μ-CT) multiphase flow experiments are aimed at imaging the in situ fluid phase distributions in porous media (Wildenschild et al 2005; Silin et al 2010; Iglauer et al 2011; Setiavan et al 2012; Andrew et al 2014). The mechanisms underlying multiphase flow through porous media can be studied and validated by combining pore-scale numerical modeling with μ-CT multiphase flow experiments. These approaches require μ-CT images that are segmented into binary images representing the “true” structure of the imaged rock and immiscible phases (Koroteev et al 2013). The influence of image segmentation on sequential pore space characterization and pore-scale modeling for multiphase flow (i.e., involving parameters important for flow, like permeability, and capillary dominated displacement like capillary pressure) must be thoroughly evaluated in further detail since the accuracy of the segmentation process determines how well the resulting binary image represents the “true” rock structure. Any pore space characterization, analysis of experimental results or flow modeling will be influenced by subtle differences in image segmentation (Iassonov et al 2009)
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