3D Pore Geometry Of Rock In Relation To Deformation Mechanism And Tranport Properties

Rock is a typical inhomogeneous material. The inhomogeneities of rock may becaused by its complex microstructure, including grains, pores, and cements. Porespace is one of the most important part of microstructure and will influence thebehaviors of rock on a macroscale. The mechanical and transport behaviors of a rockare sensitively dependent on its pore geometry. Hence it is of fundamentalimportance in rock physics to characterize the pore space and its geometricattributes, including pore size, shape, tortuosity and connectivity.Therefore, quantitative characterization of pore geometry of rocks is of greatsignificance to both rock mechanics and rock physics; and being able to interpret themacro behaviors of rocks from a microstructure perspective can advance rock studyto a higher level.Recent advances in3-dimensional imaging techniques such as X-raymicrocomputed tomography (microCT) have provided enhanced perspective on poregeometry complexity, which has contributed to useful insights into the preexistingpore space and how it influences rock physical properties, as well as damageevolution and its relation to the micromechanics of failure. With a combination ofconventional rock mechanics experiments and an advanced technology such asmicroCT, a few approaches have been made.First of all, this thesis studied the pore structure in intact and inelasticallycompacted Indiana limestone using microCT imaging. Guided by detailedmicrostructural observations and using the Otsu’s global thresholding method, the3D images acquired at voxel resolution of4m were segmented into three domains:solid grains, macropores and an intermediate zone dominated by microporosity. Themacropores were individually identified by morphological processing and their shapequantified by their sphericity and equivalent diameter. The new data revealed asignificant reduction of the number of macropores in hydrostatically and triaxiallycompressed samples with respect to the intact material, in agreement with previousmicrostructural analysis. The intermediate (microporosity) domains remained interconnected in compacted samples. The data suggest that the inelasticcompaction in Indiana limestone is manifested by not only a decrease in the volumefraction of the microporosity backbone, but also a corresponding decrease in itsthickness.Secondly, this thesis analyzed the pore structure of the intact sample of Majellalimestone following the same routine, and the quantitative characterization of themacro pore and micro pore was presented. Besides, CT scan was applied to eachsample before and after deformation, and then the TOMOWARP code was used toperform3D volumetric DIC on the two images to derive the permanent displacementfield and the full3D strain tensor field of each sample. Furthermore, a detailedanalysis of the3D strain field has been made with the help of image processing andmorphological methods.Thirdly, this study tried to gain some insight of how the localized discretecompaction band would develop. The discrete compaction band is an intermediatefailure mode between the two end-members of brittle faulting and compactivecataclastic flow. So far, there are only three sandstones that have been observed todevelop discrete compaction bands in the lab, which are Bleuswiller sandstone,Bentheim sandstone and Diemelstadt sandstone. The mechanism of the compactionband is still under debate. This work applied CT scan on each Bentheim sandstonesample before and after deformation. Based on the CT images, the porosity patchwas defined and the strain localization band was recognized. Both porosity patch andstrain localization were plotted together in3D space, which led to a conclusion thatthe locations of these patches did not coincide with where the compaction bandsformed.Finally, a fast algorithm for multi-level thresholding is presented. Rock is atypical multi-phase medium on a microscale, with the participation of different grains,pores, micro cracks and so on. To quantitatively study the behavior of rock on amicroscale, a reliable way of segmenting the CT images of rock is required. The Otsus method of image segmentation selects an optimum threshold by maximizing the between-class variance in a gray image. However, this method becomes verytime-consuming and resource-consuming when applied to a multi-level thresholdproblem due to the fact that a huge number of iterations are required for computingthe cumulative probability and the mean of a class, and a great amount of RAM isrequired to restore the look-up table. To improve the efficiency of Otsu’s method, anew fast multi-level algorithm is proposed, which can greatly reduce computing timewith mush less RAM and produce the global optimum in the mean time.