By Jason McIntosh
Leapfrog has a new surface modelling tool available in the Geological modelling toolset! The offset surface tool will be available to users who have the latest version of Leapfrog Geo or Geothermal. It’s designed to enable a greater degree of flexibility when modelling complex stratified geology, particularly from heterogeneous data. The offset surface tool appropriates all the current dynamic functionality available in the existing geological modelling surface options.
So how can the new tool be used to model such deposits? Users of Geo 2.2.1 and earlier may already be familiar with the existing offset tool that was located in the meshes folder. The new tool incorporates much of the same functionality but supersedes the earlier version with improved algorithms and additional editing options. The new functionality is well suited for modelling faulted, stratified deposits.
By Jason McIntosh
Continued from part 1 – Making the most of Leapfrog for Flow Modelling.
Generate and evaluate a finite element grid
Finally to generate a FEFLOW model right click ‘Flow Models’ in the project tree and select ‘New 2D FEFLOW Model’. Set the element size and boundary from either a GIS line, polyline or a GM. Next expand the grid, right click ‘grid’ and select ‘New feature’. Within the dialogue add any ‘Point’, ‘Line’ or ‘Polygon’ features you wish to refine the grid with. Select ‘Simplify Feature’ to reduce or increase the number of points used for the boundary prisms. Next double click the grid, in the ‘Features’ tab and activate any features you wish to build detail around and the number of refinement steps. Within the ‘Boundary’ tab select either a rectangular boundary or a custom boundary by selecting ‘From another object’.
By Jason McIntosh
Simulating fluid flow, mass and heat transfer requires the synthesis of geological models with a multitude of parameters, the process is complex. So how can Leapfrogs modelling functionality be used to streamline it?
Interoperability with FEFLOW and MODFLOW allows Leapfrog Hydro, Geothermal and Hydrology module users to interpolate initial simulation parameters and apply them to geologically constrained finite element and finite difference grids. For the purpose of this blog I will demonstrate the capabilities by modelling an aquifer system in Leapfrog Geo, simulating it in FEFLOW and viewing the time series in Leapfrog.
Aquifer systems are comprised of permeable porous water bearing aquifers and impermeable aquitards. Both have variable permeability and porosity within the sedimentary units they are comprised of, the units themselves pinch-out and diverge within stratified layers of sediment. Stratified drift aquifers are among the most challenging of such systems, as a result of the complex depositional environments they derive from.
Many of the original development team still work for ARANZ Geo, all adding their substantial knowledge and experience to the mix. Many joined as students in the early days to advance the RBF mathematics and software that is Leapfrog’s engine, FastRBF™. ARANZ Geo founder, Rick Fright describes it as a ‘blend of expertise’ and a ‘combination of experts all at the top of their game’, many in between working at University College London or Cambridge University. Fundamentally the common theme was that they were Kiwi’s, many friends from the University of Canterbury in New Zealand.
In 1999 work began on new surfacing algorithms so that an RBF implicit model could be utilised by conventional computer graphics packages. This meant converting an implicit RBF model into meshes of triangles and piecewise continuous spline surfaces.
The main difference between traditional RBF’s and what became ARANZ’s FastRBF™ is the ability to deal with large datasets of well over 1,000,000 points on ordinary computing hardware incredibly quickly. The maths used to speed up the calculation was initially used in particle physics. Filtering and approximation methods make Fast RBF™ ideal for visualising and processing non-uniformly sampled noisy data. FastRBF™ has extraordinary extrapolation capabilities, even when large gaps occur in a data set.
By Jason McIntosh
Modelling multiple thin intersecting veins in 3D can be an arduous task, luckily the Leapfrog vein modelling tool is perfect for visualising thin intersecting vein systems. Complex vein systems are common in many geological settings, but for the purpose of this blog I’m going to focus on shear zone vein systems. So bear with me as I attempt to sum up the characteristics of metalliferous shear zone ore deposits and how they can be modelled using Leapfrog Geo in an easily digestible blog.
A shear zone is a discontinuity surface in the Earth’s crust and upper mantle. Depending on the characteristics of the shear zone genesis and later regional tectonics, shear zones can form economic gold, silver, copper, lead, zinc and molybdenum deposits. However, the formation of large mineral deposits is dependent on a number of factors.
Shear zones form in brittle/ductile transition zones as metamorphic facies are uplifted during orogenic collisions. They are mineralized throughout successive cycles consisting of increased and decreased fluid pressure phases. Metamorphic compression pressurizes the fluid and seismic activity reduces the pressure by allowing the fluid to invade the country rock along grain boundaries and fractures. The successive cycles allow fluid to disperse and regenerate, therefore allowing for incremental precipitation of incompatible elements such as gold within fractures and along grain boundaries.
It has been a big year for Leapfrog Geo with the release of version 2.0 and 2.1. Significantly advanced in 2014, taking your modeling to new heights.
Significantly advanced in 2014. Let’s look at the major new features.
2.0 for advanced vein modelling
2.0 did not disappoint when it was released in July. With the most superior vein modelling in the industry, feedback from users has confirmed we were right to get excited. After all, when Product Manager Tim Schurr, described the vein modelling as ‘simply beautiful,’ we knew it was something special. So if you haven’t already tried out 2.0 what exactly are you missing?
By Scott Briscoe
We are pleased to publish another guest blog this week! Scott Briscoe is a geologist who has worked in both exploration and mining roles in Nevada, California, Alaska and Western Australia. He is a professional geologist currently doing exploration in Nevada. His specialties include mapping, advanced geological modeling, leading teams, identifying and solving problems in the pursuit of finding ore. You can read more of his articles on his own blog Briscoe Geology. Below is the process Scott went through to visualize his earthquake data, using Leapfrog Geo.
By Gordon P.L.Scott
Newcastle University, School of Civil Engineering and Geosciences
We’re pleased to be able to publish out first guest blog this week! Gordon P.L.Scott, from Newcastle University, School of Civil Engineering and Geosciences, has kindly let us use his current research paper for our Leapfrog blog. Have a read of this fantastic article and learn how Leapfrog software helped Gordon with his research.
Summary: Evaluating tritium plume
The evaluation of a developing tritium plume using a new approach through the 3D characterisation of the hydrogeology in a complex glacial environment is presented through the use of new geological modelling software and spatially varying Kh and Kv within a lithofacies method.
The main tritium waste repository in the UK is at the Drigg Low Level Waste repository in West Cumbria (Figure 1), where the waste is stored in a series of vaults excavated into the shallow drift sediments. Over the years, it has been proven (Henderson and Smith 2011) that tritium has been leaking from the depository, and found its way into the groundwater system. The presence of ‘tritiated’ water in the groundwater system is undesirable as it is a radioactive compound that is easily absorbed into the body and poses a risk to our DNA.
The tritium concentration in groundwater can be used to check the degree of confinement of an aquifer and the rate of flow of groundwater and provide data with which to validate the hydraulic parameters of the numeric model used to monitor the tritium plume.