Learning

Customized Training

Training

Customized Engineering Training Courses

Software Tutorials

PFC 7 Balls in a Box

This tutorial will guide you through the main steps required to build a simple PFC model with 30 interacting balls in a box using the linear contact model.

Plotting Borehole Core Data using Geometry and FISH

In this example, you will see how to create your own custom plot of drill core data containing location, orientation, depth, and geotechnical data (lithography. fracture count, rock strength, weathering, and RMR).

Homogeneous Embankment Dam Analysis (Part 2 of 3)

This FLAC 8.1 tutorial demonstrates how to conduct a steady-state seepage analysis to calculate the pore water pressures in the embankment due to the reservoir.

Technical Papers

Flowback Test Analyses at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) Site

Injection testing conducted in 2017 and 2019 at the Frontier Observatory for Research in Geothermal Energy site in Utah evaluated flowback as an alternative to prolonged shut-in periods to infer closure stress, formation compressibility, and formation permeability. Flowback analyses yielded lower inferred closure stresses than traditional shut-in methods and indicated high formation compressibility, suggesting an extensive fractured system. Numerical simulations showed rebound pressure is not necessarily the lower bound of minimum principal stress. Stiffness changes can be identified as depletion transitions from hydraulic to natural fractures. The advantage if flowback is reduced time to closure.

Graph-based flow modeling approach adapted to multiscale discrete-fracture-network models

In this study, we address the issue of using graphs to predict flow as a fast and relevant substitute to classical DFNs. We consider two types of graphs, whether the nodes represent the fractures or the intersections between fractures.

A Discrete Fracture Network Model With Stress-Driven Nucleation: Impact on Clustering, Connectivity, and Topology

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.