Permeability, Pore Body, and Pore Throat Size Distributions from 2D Image Analysis: Comparison with Results from 3D Imaging and Laboratory Measurements

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Quantifying rock and fluid properties is essential for characterizing any petroleum bearing reservoir. Typically, this requires that core be acquired from the formation of interest. Core plug samples are then drilled for rock properties measurement. In order to cut costs, percussion sidewall core samples are often acquired. Because the percussion acquisition process damages large portions of the sample, direct measurements of rock properties cannot be reliably made. However, if undisturbed portions of the sample are identified in thin section, and models exist for estimating rock properties, then petrophysical properties may still be estimated. This was illustrated for absolute permeability by Hathon et al., (2003), and Tripathi, et al., (2017). That work required detailed petrographic interpretation of mineralogy, grain contacts, and authigenic phases. We extend that work based only on porosity segmentation. We estimate pore body and pore throat size distributions, and specific surface area from 2D-images. Then compare those estimates of pore body and pore throat size distributions from thin section to those obtained from 3D imaging, Nuclear Magnetic Resonance (NMR), and Mercury Injected Capillary Pressure (MICP) laboratory measurements. Watershed segmentation was used to divide the segmented pores into pore bodies and pore throats. However, pore body and pore throat sizes change as a function of input parameters to the watershed algorithm. To optimize the parameters 2D segmentation results have been compared to pore body sizes estimated from Nuclear Magnetic Resonance Relaxation Time (NMR T2) distributions and high-resolution Micro-Computed Tomography (Micro-CT) scans. Standard clean and shaly sandstone surface relaxivity values were applied to NMR T2 distributions for several industry standard and subsurface reservoir samples. The modal pore body sizes were used to define the best image analysis parameters for determining 3D equivalent pore body size distributions using 2D images. Good agreement is observed between NMR T2 distribution-inverted modal pore body sizes, and to 3D image analysis pore body sizes using a tolerance of 1 as the input parameter to the 2D watershed algorithm. Applying the watershed algorithm with a tolerance of 1 in UH’s Quantitative Petrographic Interpretation (QPI) software also provides accurate estimates of pore throat size distributions when compared to Mercury Injected Capillary Pressure (MICP) pore throat size measurements.
Characteristics of the pore system quantified utilizing 2D-image segmentation, including mean pore body area, mean area equivalent spherical diameter, mean pore throat diameter, and specific surface area are also strongly related to the measured brine permeability. These observations suggest that image analysis applied to thin section images can be used to rapidly and inexpensively estimate total porosity, absolute permeability, Nuclear Magnetic Resonance Relaxation Time (NMR T2) distribution, and pore throat diameter distribution of subsurface formations.

Reservoir Rock Characterization, Reservoir Rock Digitization, Petrophysics, Micro-CT, Transmitted Light Microscopy, Petroleum Reservoirs, Petroleum Formation Properties, Pore Body Size, Pore Throat Size, Nuclear Magnetic Resonance, Petrology