Cid H E, Carrasco-Núñez G, Manea V C
X-ray Microtomography Laboratory (LUMIR), Centro de Geociencias, Universidad Nacional Autonoma de Mexico, Campus Juriquilla, Queretaro, 76230, Mexico; Energy Futures Lab, Imperial College London, London, SW7 2AZ, UK.
X-ray Microtomography Laboratory (LUMIR), Centro de Geociencias, Universidad Nacional Autonoma de Mexico, Campus Juriquilla, Queretaro, 76230, Mexico.
Micron. 2017 Jun;97:11-21. doi: 10.1016/j.micron.2017.01.003. Epub 2017 Jan 22.
Petrophysical analysis using X-ray microtomography provides key textural and compositional information, useful to investigate porous media characteristics of hydrocarbon and geothermal reservoirs. Several approaches, used for rock porosity estimation from tomography data, rely mainly on visual or mathematical segmentation algorithms that attempt to obtain thresholding values to segment a phase solved by pixel analysis resolution. Therefore, porosity is evaluated using only pores above pixel resolution (macroporosity), and dismiss pores sized less than the pixel resolution (microporosity) that can be essential to characterize permeability conditions of geothermal reservoirs. Here we propose an improved method to calculate the total effective porosity and simulate the absolute permeability of rock samples. This method combines the analysis of X-ray computed microtomography (μCT) with the interpretation of data using a powerful thresholding method that is based on the greyscale interclass variance. The 3D volume is segmented into three domains: solid, pores above resolution and, an intermediate region where each pore below resolution is linearly combined with solid matrix resulting in a grey scaled pixel equal to this combination. For the intermediate region, the microporosity was calculated employing a Matlab code that provides a new thresholding value containing pores, both above and below resolution (total porosity). Finally, by using this new calculated thresholding value the total effective porosity was obtained and an absolute permeability simulation was implemented only to the connected pores. Our results show that micropores contribute for nearly 50 percent of the total porosity and that microporosity plays a key role in estimating effective porosity, and assessing the geothermal potential of a rock reservoir.
使用X射线显微断层扫描进行岩石物理分析可提供关键的结构和成分信息，有助于研究油气藏和地热储层的多孔介质特征。几种用于从断层扫描数据估算岩石孔隙率的方法，主要依赖于视觉或数学分割算法，这些算法试图获得阈值来分割通过像素分析分辨率求解的相。因此，孔隙率仅使用高于像素分辨率的孔隙（大孔隙率）进行评估，而忽略了尺寸小于像素分辨率的孔隙（微孔隙率），而这些微孔隙对于表征地热储层的渗透率条件可能至关重要。在此，我们提出一种改进方法来计算岩石样品的总有效孔隙率并模拟其绝对渗透率。该方法将X射线计算机显微断层扫描（μCT）分析与基于灰度类间方差的强大阈值方法对数据的解释相结合。三维体积被分割为三个区域：固体、高于分辨率的孔隙以及一个中间区域，其中每个低于分辨率的孔隙与固体基质线性组合，得到一个等于该组合的灰度像素。对于中间区域，使用Matlab代码计算微孔隙率，该代码提供一个包含高于和低于分辨率的孔隙的新阈值（总孔隙率）。最后，通过使用这个新计算的阈值获得总有效孔隙率，并仅对连通孔隙进行绝对渗透率模拟。我们的结果表明，微孔对总孔隙率的贡献近50%，并且微孔隙率在估算有效孔隙率和评估岩石储层的地热潜力方面起着关键作用。
