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Preface
(2018)
Predicting macroscopic elastic rock properties requires detailed information on microstructure
(2017)
Predicting variations in macroscopic mechanical rock behaviour due to microstructural changes, driven by mineral precipitation and dissolution is necessary to couple chemo-mechanical processes in geological subsurface simulations. We apply 3D numerical homogenization models to estimate Young’s moduli for five synthetic microstructures, and successfully validate our results for comparable geometries with the analytical Mori-Tanaka approach. Further, we demonstrate that considering specific rock microstructures is of paramount importance, since calculated elastic properties may deviate by up to 230 % for the same mineral composition. Moreover, agreement between simulated and experimentally determined Young’s moduli is significantly improved, when detailed spatial information are employed.
Our Conclusions
(2018)
Point clouds provide high-resolution topographic data which is often classified into bare-earth, vegetation, and building points and then filtered and aggregated to gridded Digital Elevation Models (DEMs) or Digital Terrain Models (DTMs). Based on these equally-spaced grids flow-accumulation algorithms are applied to describe the hydrologic and geomorphologic mass transport on the surface. In this contribution, we propose a stochastic point-cloud filtering that, together with a spatial bootstrap sampling, allows for a flow accumulation directly on point clouds using Facet-Flow Networks (FFN). Additionally, this provides a framework for the quantification of uncertainties in point-cloud derived metrics such as Specific Catchment Area (SCA) even though the flow accumulation itself is deterministic.
Water management tools are necessary to guarantee the preservation of natural resources while ensuring optimum utilization. Linear regression models are a simple and quick solution for creating prognostic capabilities. Multivariate models show higher precision than univariate models. In the case of Waiwera, implementation of individual production rates is more accurate than applying just the total production rate. A maximum of approximately 1,075 m3/day can be pumped to ensure a water level of at least 0.5 m a.s.l. in the monitoring well. The model should be renewed annually to implement new data and current water level trends to keep the quality.