Learning

Software Tutorials

Using Python in Itasca Software

Python scripting is built into current versions of FLAC3D, 3DEC, and PFC. This video introduces users of Itasca software to working with Python and FLAC3D, 3DEC, and PFC types (zones, blocks, ball, structural elements, and so on). The Itasca Module, a comparison with FISH scripting, and object-oriented and array-oriented interfaces are reviewed and demonstrated.

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).

Python and Pore Pressure Initialization

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.

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.

The Economic Challenges of Dewatering at the Victor Diamond Mine in Northern Ontario, Canada

The challenges of mining economically have never been greater than under current global financial conditions.

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.

Latest News
  • 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...
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  • WEBINAR: Solving Geothermal Challenges with XSite Numerical Modeling ITASCA Software and Baker Hughes are hosting a collaborative webinar to demonstrate how combining advanced...
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  • Itasca has announced the release of FLAC2D v9 Itasca has announced the release of FLAC2D v9, revolutionizing the way we analyze and predict...
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Upcoming Events
11 Aug
ITASCA Joins Caving 2026 as a Main Sponsor
We are pleased to announce that ITASCA will be participating as a Main Sponsor in Caving 2026, the leading international conference ded... Read More
15 Sept
ITASCA at EUROCK 2026: Advancing Innovation in Rock Engineering
ITASCA is pleased to announce its participation in EUROCK 2026 – ISRM Regional Symposium, taking place from 15–19 September 2026 in Sko... Read More
20 Sept
ITASCA to Participate in CouFrac 2026
ITASCA will be participating in CouFrac 2026, taking place from 20–23 September 2026 in Uppsala, Sweden. The conference brings together... Read More