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Pore-scale modeling is essential in understanding and predicting flow and transport properties of rocks. Generally, pore-scale modeling is dependent on imaging technologies such as Micro Computed Tomography (micro-CT), which provides visual confirmation into the pore microstructures of rocks at a representative scale. However, this technique is limited in the ability to provide high resolution images showing the pore-throats connecting pore bodies. Pore scale simulations of flow and transport properties of rocks are generally done on a single 3D pore microstructure image. As such, the simulated properties are only representative of the simulated pore-scale rock volume. These are the technological and computational limitations which we address here by using a stochastic pore-scale simulation approach. This approach consists of constructing hundreds of 3D pore microstructures of the same pore size distribution and overall porosity but different pore connectivity. The construction of the 3D pore microstructures incorporates the use of Mercury Injection Capillary Pressure (MICP) data to account for pore throat size distribution, and micro-CT images to account for pore body size distribution. The approach requires a small micro-CT image volume (7–19 mm3) to reveal key pore microstructural features that control flow and transport properties of highly heterogeneous rocks at the core-scale. Four carbonate rock samples were used to test the proposed approach. Permeability calculations from the introduced approach were validated by comparing laboratory measured permeability of rock cores and permeability estimated using five well-known core-scale empirical model equations. The results show that accounting for the stochastic connectivity of pores results in a probabilistic distribution of flow properties which can be used to upscale pore-scale simulated flow properties to the core-scale. The use of the introduced stochastic pore-scale simulation approach is more beneficial when there is a higher degree of heterogeneity in pore size distribution. This is shown to be the case with permeability and hydraulic tortuosity which are key controls of flow and transport processes in rocks.
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Effect of X‐Ray Computed Tomography Imaging Parameters on Quantification of Petrophysical Properties
Abstract Three‐dimensional (3D) X‐ray computed tomography (X‐ray CT) imaging has emerged as a nondestructive means of microstructural characterization. However, obtaining and processing high‐quality and high‐resolution images is time‐consuming and often requires high‐performance computing, particularly with a high number of projections. This work evaluates the effect of 3D X‐ray CT imaging parameters on pore connectivity and surface area quantification in sandstone samples of varied composition. Samples from Bentheimer and Torrey Buff formations are imaged via 3D X‐ray CT imaging at resolutions ranging from 1.25 to 15 μm, bin sizes 1, 2, and 4, and number of projections from 400 to 4,500. Collected images are processed and analyzed using ImageJ and MATLAB to discern petrophysical properties and the results are compared with each other and Mercury Intrusion Capillary Pressure (MICP) results. Overall, little variation in bulk porosity with changing scanning parameters is observed. However, for low resolution and projection numbers, connected porosity is lower compared to bulk porosity due to a failure to capture microfeatures. Overall, mineral surface area is observed to decrease with increasing bin size, voxel size, and projection numbers, except an observed increase with projection numbers for Torrey Buff. The Torrey Buff samples contains comparatively more clays and even the highest resolution (1.25 μm) fails to separate the micrograins, which is reflected in the pore size distribution. Identifying these variations are helpful as discrepancies in imaged pore connectivity and surface area can largely impact assessments of fluid flow and transport in reactive transport simulations informed by this data.
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- Award ID(s):
- 1847243
- PAR ID:
- 10480756
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Earth and Space Science
- Volume:
- 10
- Issue:
- 10
- ISSN:
- 2333-5084
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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