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<span style="font-family:"Arial",sans-serif"><img width="600" height="174" id="x__x0000_i1026" alt="Dissertation Defense Announcement at the Cullen College of Engineering" style="width:6.25in; height:1.8125in" src="https://www.egr.uh.edu/sites/www.egr.uh.edu/files/enews/2022/images/thesis1.png"></span></p>
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<b><span style="font-size:18.0pt; color:#C8102E">Permeability, Pore Body, and Pore Throat Size Distribution from 2D Image Analysis: Comparison with results from 3D Imaging and Laboratory Measurements</span></b><b><span style="font-size:18.0pt"></span></b></p>
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<b><span style="font-size:13.5pt; color:black">Jomana Tarik Nabil Abdel Razik</span></b></p>
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<span style="font-size:10.5pt; font-family:"Arial",sans-serif; color:black">July 29, 2022; 2:00 PM - 4:00 PM (CST)<br>
Location: UH Technology Bridge, Bldg. 9, Room 124 <br>
Zoom link:<br>
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<span style="font-size:10.5pt; font-family:"Arial",sans-serif; color:black">Passcode: --</span></p>
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<b><span style="font-size:10.5pt; font-family:"Arial",sans-serif; color:black">Committee Chair:</span></b><span style="font-size:10.5pt; font-family:"Arial",sans-serif; color:black"><br>
Michael T. Myers, Ph.D.</span></p>
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<b><span style="font-size:10.5pt; font-family:"Arial",sans-serif; color:black">Committee Members:</span></b><span style="font-size:10.5pt; font-family:"Arial",sans-serif; color:black"><br>
Lori A. Hathon, Ph.D. | George K. Wong, Ph.D. </span></p>
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<p style="margin-bottom:11.25pt; line-height:16.5pt"><b><span style="font-size:12.0pt; font-family:"Arial",sans-serif; color:#C8102E">Abstract</span></b></p>
<p style="margin-bottom:11.25pt; line-height:16.5pt"><span style="font-size:10.5pt; font-family:"Arial",sans-serif; color:black">A </span><span style="font-size:12.0pt; font-family:"Times New Roman",serif; color:black">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, NMR, and 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 NMR T</span><sub><span style="font-family:"Times New Roman",serif; color:black">2</span></sub><span style="font-size:12.0pt; font-family:"Times New Roman",serif; color:black">
distributions and high-resolution micro-Ct scans.</span></p>
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<span style="font-size:12.0pt; line-height:115%; font-family:"Times New Roman",serif; color:black">Standard clean and shaly sandstone surface relaxivity values were applied to NMR T<sub>2</sub> 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 T<sub>2</sub> distribution-inverted pore body size
and the 3D image analysis pore body sizes using a tolerance of 1 as the input parameter to the 2D image analysis. Applying the watershed algorithm with a tolerance of 1 in UH’s Quantitative Petrographic Interpretation (QPI) software also provides accurate
estimates of pore body and pore throat sizes when compared to NMR T2 distributions and MICP pore throat size measurements. Characteristics of the pore system quantified utilizing 2D image segmentation, including mean pore body 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, NMR T<sub>2</sub> distribution, and pore throat diameter distribution of subsurface formations.</span><span style="font-family:"Times New Roman",serif"></span></p>
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<span style="font-family:"Arial",sans-serif"><img width="600" height="82" id="x__x0000_i1025" alt="Engineered For What's Next" style="width:6.25in; height:.8541in" src="https://www.egr.uh.edu/sites/www.egr.uh.edu/files/enews/2022/images/dissertation2.png"></span></p>
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