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Tutoriels Logiciels

Working with Building Blocks in FLAC3D 6 (Part 1)

This video demonstrates using a library set of Building Blocks as a starting point for creating a new model. In this example, cylindrical blocks are snapped together to represent a tunnel and intersected with other blocks representing a nearby wall.

FLAC3D Quick Start Tutorial

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.

Using Python in FLAC3D 6

The Python programming language is embedded inside FLAC3D 6 and extended to allow FLAC3D models to be manipulated from Python programs. This webinar recording provides a brief introduction to Python scripting and includes many examples of using Python with FLAC3D.

Articles scientifiques

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.

Connectivity, permeability, and channeling in randomly distributed and kinematically defined discrete fracture network models

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.

Deep Sublevel Cave Mining and Surface Influence

With increasing depth, higher stress and more difficult mining. With increasing depth is there more ground surface effects or less?