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 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 2.0 in July, and 2.1 in November. Both versions offered significant improvements to take your modeling to new heights.
Lets 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.
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.
By Lisa Swinnard
There are several ways to edit and modify an “Intrusion” surface within a GM; of them, value clipping is often overlooked. This document is part one of two and will outline the procedure for modifying intrusion surfaces by value clipping, describe the importance and relevance of volume points, and explain how the two are connected.
1. Value Clipping
Step 1 – Create a new geological model and intrusion surface
- Within the GM, create a new intrusion surface.
- Edit the surface accordingly, add a trend if necessary.
Step 2 – Modify the value clipping
- To modify the value clipping, double click the intrusion surface in the project tree.
- In the dialogue box that appears, click on the surfacing tab and check the “Show additional surfacing options” box.
By Andrew Cantwell
One of the major costs of an exploration project is the drilling program. Planning drillholes in 3D based on existing knowledge is an easy way to maximise the value of any future drilling, and can be achieved quickly and easily in Leapfrog Geo. This blog post will take you through the steps required to plan a drilling campaign in Leapfrog Geo, then set up a scene file so the field team can see where each drillhole should be going, as well as what lithology and grade it is expected to intercept, in 3D.
- The first step is to define your project area – a good start is to import any existing data. This could include a topography surface, any existing drillholes, an aerial photograph or geological map, and GIS data such as lakes, rivers, access roads and tenement boundaries.
- Once you have imported the existing data, you’ll be able to start visualising in 3D where an appropriate location is to place your collar. If you’ve created any geological or grade models, you can also visualise where your potential target is.
- To create a planned drillhole, right click on the ‘Planned Drillholes’ folder, and click ‘Plan Drillhole’.
- There are two options you can choose; you can either specify a collar location or a target location. We’ll specify a collar location as it is more common to have a known point on the topography to place your collar.
By Peter Joynt
It is not often in geology that mineralisation or geological units behave in a consistent planar fashion. The earlier article on interpolation and anisotropy by Kirk Spragg outlined a detailed explanation of Leapfrog’s global trend and how it affects the interpolation of points. This article aims to give users an introduction to the application of structural trends and how they can be applied to a model to handle different situations.
What is a Structural Trend?
A structural trend is a generalisation of the global trend that allows changes in direction of continuity over a defined surface. Instead of being based on a plane like the global trend with the user defining the ellipsoid ratios, the structural trend is based on a surface. This surface can be any shape or orientation usually defined by geological constraints such as faulting, foliation etc. The surface is then effectively down sampled to determine the local trend at each point on the mesh to give the user an anisotropy that varies throughout the defined space. This makes the structural trend perfect for geological units or mineralisation that is not planar. The structural trend does not determine the final surface; this is still done by the interpolant and the data points used. In Leapfrog the default interpolant type is isotropic, which lets us more easily visualise trends that are often hard to pick up when looking at raw data. Figures 1, 2 and 3 show the difference between an isotropic interpolant, global trend and a structural trend.
Welcome to Leapfrog’s blog
I‘m fortunate to be asked to write the first Leapfrog blog and to set the scene for what we hope will be many thought-provoking blogs to come. No pressure then! Seriously though, we want this blog spot to open up a dialogue between anyone interested in geology and geological modelling in particular. So if that’s you, please get involved, we’re interested in what you have to say!