MINEDW Tutorial (Part 1: Menu Options)

In this tutorial we will briefly cover the MINEDW user interface, its components, and the MINEDW Menu with the different options and tools it provides to build numerical models.

An Introduction to Python Scripting: Part 2

Introduction to Python scripting by reviewing key concepts and through demonstrations. Part 2 focuses on classes and objects plus lists and dictionaries.

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.

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.

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.

  • ITASCA Strengthens North American Delivery of Integrated Geomechanics and Hydrogeology Solutions Drawing on decades of geomechanical and hydrogeological expertise, ITASCA has announced the formation of ITASCA...
  • Itasca has announced the release of FLAC2D v9 Itasca has announced the release of FLAC2D v9, revolutionizing the way we analyze and predict...
  • 6th Itasca Symposium on Applied Numerical Modeling The next Itasca Symposium will take place June 3 - 6, 2024, in Toronto, Canada....