Predicting Fracture Network Development in Crystalline Rocks

The geometric properties of fractures influence whether they propagate, arrest, or coalesce with other fractures. Thus, quantifying the relationship between fracture network characteristics may help predict fracture network development, and perhaps precursors to catastrophic failure. To constrain the relationship and predictability of fracture characteristics, we deform eight one centimeter tall rock cores under triaxial compression while acquiring in situ X-ray tomograms. The tomograms reveal precise measurements of the fracture network characteristics above the spatial resolution of 6.5 µm. We develop machine learning models to predict the value of each characteristic using the other characteristics, and excluding the macroscopic stress or strain imposed on the rock. The models predict fracture development more accurately in the experiments performed on granite and monzonite, than the experiments on marble. Fracture network development may be more predictable in these igneous rocks because their microstructure is more mechanically homogeneous than the marble, producing more systematic fracture development that is not strongly impeded by grain contacts and cleavage planes. The varying performance of the models suggest that fracture volume, length, and aperture are the most predictable of the characteristics, while fracture orientation is the least predictable. Orientation does not correlate with length, as suggested by the idea that the orientation evolves with increasing differential stress and thus fracture length. This difference between the observed and expected relationship between orientation and length highlights the influence of mechanical heterogeneities and local stress perturbations on fracture growth as fractures propagate, link, and coalesce.

Correlation between the mineral composition and strength properties of sulfate rocks

The literature review confirms that the effect of mineral composition on the strength properties of rocks has rarely been studied. One of the most problematic sedimentary rocks is sulfate rocks, which cause engineering problems in the infrastructure sites such as reservoir dams. In this paper, for the first time, the effect of mineral composition on the strength properties of sulfate rocks was investigated. The rock blocks were collected from the Gachsaran Formation outcrops at the four under construction reservoir dam sits in Iran. After preparing, drying and saturation the rock cores samples (329 samples), uniaxial compressive strength tests were performed in accordance with ASTM and ISRM standards. The results of this study confirmed that firstly, there is a correlation between the mineral composition and the strength properties of the sulfate rocks, but the obtained relationships do not have the necessary certainty to be used as predictive equations. Secondly, by increasing the amount of anhydrite or microcrystalline carbonates in a gypsum rock, its strength properties are increased. Thirdly, in a dry condition the dominant failure mode in gypsum and anhydrite rocks is a shear and dilatation mode, respectively, but after saturation, the failure mode tends to shear mode.

Potential microbial contamination from drilling lubricants into subseafloor rock cores

International Ocean Discovery Program (IODP) Expedition 357: “Serpentinization and Life” drilled shallow cores into the Atlantis Massif near the Mid-Atlantic Ridge in October 2015 using seabed drills. Serpentinization and other geochemical processes occurring within the Atlantis Massif release hydrogen, methane, and other chemicals that can potentially fuel microorganisms through chemosynthesis. The subseafloor rock cores collected during IODP Exp. 357 are the first of their kind, meaning the analysis and interpretation of these samples required new methodologies, including a specialized approach for distinguishing endemic subsurface inhabitants from potential contaminants from various sources. Background samples of various potential contamination sources were collected during sampling: 109 samples of seawater collected before, during, and after drilling; 20 samples of greases and oils associated with the drilling equipment; and samples of the laboratory's ambient air. Despite the widespread usage of drilling lubricants and the importance of controlling contamination in drill-core samples for microbiological analyses, no studies to date have looked at DNA in drilling greases and oils. In this study, drilling lubricants were analyzed as possible sources of microbial contamination of subseafloor rock core samples by environmental sequencing of 16S rRNA genes. We find that microbial signatures from drilling lubricants are only found in low abundance in seafloor samples (at most a few percent of total sequence counts), with laboratory contaminants being a greater source of contamination.

Predicting fracture network development in crystalline rocks

<p>The geometric properties of fractures influence whether they propagate, arrest and coalesce with other fractures. Thus, quantifying the relationship between fracture network characteristics may help predict fracture network development, and hence precursors to catastrophic failure. To constrain the relationship and predictability of fracture characteristics, we deform eight rock cores under triaxial compression while acquiring in situ X-ray tomograms. The tomograms reveal precise measurements of the fracture network characteristics above 6.5 microns. We develop machine learning models to predict the value of each characteristic using the other characteristics, and excluding the macroscopic stress or strain imposed on the rock. The models predict fracture development more accurately in the experiments performed on granite and monzonite, than the experiments on marble. Fracture network development may be more predictable in these igneous rocks because their microstructure is more mechanically homogeneous than the marble, producing more systematic fracture development that is not strongly impeded by grain contacts and cleavage planes. The varying performance of the models suggest that fracture volume, length, and aperture are the most predictable of the characteristics, while fracture orientation is the least predictable. Orientation does not correlate with length, as suggested by the idea that the orientation evolves with increasing differential stress and thus fracture length. This difference between the observed and expected predictability of orientation highlights the significant influence of local stress perturbations on fracture growth within brittle material in laboratory-scale systems with many propagating and interacting fractures.</p>