1. Geological Modelling Techniques , Lance
Project, Wyoming
A.Gillman
J.Scyphers
International Atomic Energy Agency
Technical Meeting on Origin of Sandstone Uranium Deposits
Vienna, 29 May - 1 June 2012
2. Overview
Company and Projects Introduction
Wyoming ISR Project
Geological Setting
Data Management
Modelling Techniques
Geological
Resource
3. Introduction
• Perth-based, ASX-listed uranium explorer/developer
• Flagship project - Lance (ISR) Wyoming
• July 2009: no code-compliant resource
no permit application
large historic database
• April 2010: initial code-compliant resource estimate
announced
• Jan 2011: NRC (Nuclear Regulatory Commission)source
materials licence application delivered
• May 2011: NRC acceptance of licence application
• May 2012: final RAI’s (Request for Additional Information) deemed
satisfactory by the NRC
• Currently raising finance for construction for the Lance ISR Project
• 51.5Mlb U3O8 JORC-compliant resource in Wyoming, US
• Initial exploration target of 30M lbs at ~1,000ppmU3O8 in the Karoo, South
Africa
4. Projects Overview
Wyoming Mining Association
Karoo Basin, South Africa Powder River Basin, Wyoming
Sandstone-hosted Sandstone-hosted
Channel-fill, organic associated U (+Mo) Roll-front style U (+V)
Conventional open-pit +/-UG In Situ Recovery (ISR)
5. Regional Geological Setting
Montana
South Dakota
Alladin
Bighorn Powder River
Idaho Jackson Hole
Pumpkin
Copper Buttes
Mountain
Wyoming Southern
Wind River
Powder River
Gas Hills
Silver Cliff
Shirley
Shirley Basin
Green River Great Divide
Great Divide Nebraska
Hanna
Utah Laramie Denver-
Cheyenne
Washakie
Colorado
100km
6.
7. Tectonic Setting
• Black Hills Monocline Powder River Basin
• Undeformed, flat to gently
dipping Devil’s Tower
Black Hills Uplift
Sundance
Tertiary Cretacous Jurassic Triassic Permian
15km
8. Lance Project – Exploration History
• Explored by Nuclear Dynamics and Bethlehem
Steel (NuBeth) 1971-1980
• 5,000 historic drill holes (gamma logs)
• >300 line km of redox fronts
• Identified 13 separate project areas
• >2,000 holes drilled 2009-2012 (PFN)
9. Objectives
Permitting
• Provide accurate geological models for hydrological simulations
• recovery from exertions
• restoration
• Demonstrate confinement of production aquifers
• Demonstrate absence of faulting
Resource Estimation
• Collect and digitize all available data as the basis of a robust resource
model
• Validation of historic data for inclusion in JORC resource
Exploration/Development
• Create a tool for better exploration planning
• Ability for detailed well-field planning
11. Database vs NuBeth QAQC
Database Compositing NuBeth Hand Calcs
Thickness Grade GT Thickness Grade GT
No. Average Weighted Final Average Weighted Final GT
100 12.97 412 0.53 10.84 490 0.53
Difference 2.13 -78 0.00 -2.13 78 0.00
Percentage 16 -19 0 -20 16 0
12. Software
SQL Server Database – Maxwells Geoservices
Gems geological & resource modeling
Surpac polygonal calculations
Leapfrog 3D isosurfacing of gamma data
ArcGIS drill planning, mapping
Rockworks conversion of gamma point data to grade
interval data, cross sections
Surfer contouring
22. Resource Modeling
Polygonal/GT
Wireframe-constrained block model
Unconstrained block model
Grade isosurfacing
23. Resource Modeling –Polygonal
• Polygonal estimation constrained by manually-
interpreted GT boundary
• GT points classified and reported by horizon
• Each polygon attributed with volume, grade and
contained U3O8
• Useful drill-planning tool
• Traditional and accepted methodology
25. Resource Modeling
Geologically-constrained
Block Modeling
• Accurate volumes
• Application of geostatistics/kriging
• Wireframing is time consuming
• Updates are time-consuming
26. Resource Modeling
Partially-constrained
Block Model
• Speed
• Accuracy
• Flexibility in reporting
• Efficient updates
• Difficult to integrate into a
GT world
27. Resource Modeling
Partially-constrained
Block Model
• Speed
• Accuracy
• Flexibility in reporting
• Efficient updates
• Difficult to integrate into a
GT world
28. Iso-surfaces
• Speed – overcomes need
for manual wireframing
• Geostatistical
characteristics can be
modeled
• Accuracy
• Efficient updates
• Highlighting trends