An Open, Object‐Based Framework for Generating Anisotropy in Sedimentary Subsurface Models. Issue 3 (19th June 2018) - Bennett, Jeremy P.; Haslauer, Claus P.; Ross, Martin; Cirpka, Olaf A.
Abstract: The spatial distribution of hydraulic properties in the subsurface controls groundwater flow and solute transport. However, many approaches to modeling these distributions do not produce geologically realistic results and/or do not model the anisotropy of hydraulic conductivity caused by bedding structures in sedimentary deposits. We have developed a flexible object‐based package for simulating hydraulic properties in the subsurface—the Hydrogeological Virtual Realities (HyVR) simulation package. This implements a hierarchical modeling framework that takes into account geological rules about stratigraphic bounding surfaces and the geometry of specific sedimentary structures to generate realistic aquifer models, including full hydraulic‐conductivity tensors. The HyVR simulation package can create outputs suitable for standard groundwater modeling tools (e.g., MODFLOW), is written in Python, an open‐source programming language, and is openly available at an online repository. This paper presents an overview of the underlying modeling principles and computational methods, as well as an example simulation based on the Macrodispersion Experiment site in Columbus, Mississippi. Our simulation package can currently simulate porous media that mimic geological conceptual models in fluvial depositional environments, and that include fine‐scale heterogeneity in distributed hydraulic parameter fields. The simulation results allow qualitative geological conceptual models to be converted into digital subsurface models that can be used in quantitative numerical flow‐and‐transport simulations, with the aim of improving our understanding of the influence of geological realism on groundwater flow and solute transport. Abstract : Article impact statement : Generate hydrogeological virtual realities and analyze three‐dimensional conceptual models using a flexible open‐source Python package.