This video is a recording of a one hour webinar reviewing the latest features in Version 5.2 of 3DEC. Presented by Dr. Jim Hazzard, 3DEC Product Manager and Lead Developer.
This tutorial steps through the actions necessary to quickly create and solve a FLAC3D model. The focus of this tutorial is to provide you with a basic familiarity with the user interface and recommended work flow.
In this tutorial we will demonstrate how to map a random point cloud with pore pressure values onto the grid points of a FLAC3D model using Python.
The realism of Discrete Fracture Network (DFN) models relies on the spatial organization of fractures, which is not issued by purely stochastic DFN models. In this study, we introduce correlations between fractures by enhancing the genetic model (UFM) of Davy et al. [1] based on simplified concepts of nucleation, growth and arrest with hierarchical rules.
A major use of DFN models for industrial applications is to evaluate permeability and flow structure in hardrock aquifers from geological observations of fracture networks. The relationship between the statistical fracture density distributions and permeability has been extensively studied, but there has been little interest in the spatial structure of DFN models, which is generally assumed to be spatially random (i.e., Poisson). In this paper, we compare the predictions of Poisson DFNs to new DFN models where fractures result from a growth process defined by simplified kinematic rules for nucleation, growth, and fracture arrest.