Hot Chili Limited · ASX:HCH
Hot Chili — DM Symposium 2023
26 slides from Hot Chili's conference presentation, Oct 22, 2023
Slide 1: An Estimation Workflow: The Parker Challenge Winning Formula
ASX: HCH TSXV: HCH OTCQX: HHLKF An Estimation Workflow: The Parker Challenge Winning Formula Katie Collins, Chris McKie, Kirsty Sheerin, Madeline Wallace DM SYMPOSIUM 22-10-23 | 1 www.hotchili.com.au
Slide 2: Disclaimer & Forward-Looking Statements
Disclaimer & Forward-Looking Statements Disclaimer This Presentation (the "Presentation") is to be used by the recipient for informational purposes only and does not purport to be complete or contain all of the information that may be material to the current or future business, operations, financial
Slide 3: Parker Challenge Overview
Parker Challenge Overview Organised by the AusIMM and using a data set from the Hugo Dummett South project at Rio Tinto’s Oyu Tolgoi operations in Mongolia, the Parker Challenge sought to quantify the variance between resource estimations by different practitioners using the same data set. The Chall
Slide 4: Parker Challenge: Team and Time Spent
Parker Challenge The Hot Chili Ltd. Team Time Spent • Kirsty Sheerin (Resource Development Manager) – 16 years experience • 179 hours on the project (~22 days) • Chris McKie (Senior Resource Geologist) – 14 years experience • 60% outside of normal working hours. • Madeline Wallace (Senior Project Ge
Slide 5: Background Experience
Background Experience Why was the team suited to the Challenge? Hot Chili is currently developing its Costa Fuego Project in Chile, which includes the structurally complex IOCG breccia deposit Productora, high- grade structurally controlled copper deposit San Antonio and Cu-Au-Mo porphyry deposit Co
Slide 6: Activity Breakdown
Activity Breakdown Data Validation: - - Gap analysis of supplied data Determine regional context, local geology and interpretation, structural influences ~1/3 – Geology ~1/3 – Estimation Build Geology Model: ~1/3 – Validation/Reporting - Create 3D lithology and fault models, review late intrusions,
Slide 7: Macro-Driven Estimation
Macro-Driven Estimation A Standardised Approach – With Room For Flexibility 01. Create Database a. Create Database b. Clean Database c. Flag Database 02. Create Model a. Build Prototypes b. Build Volume Model 03. Composite and Top Cap a. Composite Data b. Top Cap Data 04. Run Estimation a. Estimate
Slide 8: Data Validation – Part 1
Data Validation – Part 1 Example of data issue Literature Review rectified before commencing estimate • Establish regional and local context • Utilise all available sources (not just the data provided) Data Validation • Don’t take data quality for granted • Establish 3D context • Standard set of exc
Slide 9: Data Validation – Part 2
Data Validation – Part 2 Detection Limit Issues • Issues with detection limits noted for As and Mo • Researched likely assay technique to ensure no other issues would be present in data set • Assays at lower-detection value set to half detection limit and noted Assumed assay methodology, based on de
Slide 10: Building the Geology Model – Part 1
Building the Geology Model – Part 1 Structural Model Cross-section view of geology and lithology models • Review orientations, movements, timing relationships, and significance of structures within the model area Lithology Model • Review lithology logging and create stratigraphic Ignimbrite column t
Slide 11: Building the Geology Model – Part 2
Building the Geology Model – Part 2 Geochemistry • Analysed Cu grade and sulphide abundance by lithology • Bornite identified in augite basalt • Correlation recognised between arsenic and logged enargite • Confirmed BIGD has stoped out mineralisation; similar to Cuerpo 3 at the Post- Cortadera Proje
Slide 12: Building the Estimation Domains – Part 1
Building the Estimation Domains – Part 1 Iterative Process Essential • Back and forth between Supervisor (exploratory data analysis) and Datamine (visual checks) • Once the geology model was finalised, a geostatistical approach was used to determine suitable cut-off grades for subdomaining of each e
Slide 13: Building the Estimation Domains – Part 2
Building the Estimation Domains – Part 2 Geological Context is Key • Continuity of grade was initiated by the emplacement of the mineralised quartz-monzonite into the easterly dipping host basalt unit • However, the geology does not necessarily constrain mineralisation • A higher-grade ‘core’ exists
Slide 14: Top Capping
Top Capping Domain and Deposit Type Specific • Hard top caps applied where genuine outliers exist • Where histogram tail under-sampled “influence limitation” (IL) top capping applied • IL top caps are applied where apparent outliers exist, likely belonging to the grade population but appearing as ou
Slide 15: Contact Analysis
Contact Analysis Defining and Refining Domains • Geology and timing relationship-driven • Datamine macros allow a new code to be created by using a concatenation of the estimation domain code, lithology code, fault code and weathering code • Previously employed at Productora, due to the complexity o
Slide 16: Bulk Density
Bulk Density A Critical Consideration, Often Overlooked • 11,040 bulk density measurements were included in the data set • Data set flagged with lithologies geology model; outliers excluded • Density estimated by lithology using ‘constructed’ variogram • Estimate validated visually and statistically
Slide 17: Variography
Variography Completed in Supervisor, Validated in Datamine • Variography and a Kriging Neighbourhood Analysis were completed in Snowden Supervisor on the top-capped data set for each estimation domain • Construction of detailed litho-structural model meant variograms for the ore domains were coheren
Slide 18: QKNA
QKNA DOM=3000 15x15x15m parent block DOM=9000 40x40x40m parent block Just Min = 7 samples, Max = 12, right? • Four different parent block sizes have been used • Multiple block sizes are possible in Datamine and were driven by QKNA completed on each of the estimation domain data sets • Sub-blocking c
Slide 19: Block Model Validation – Part 1
Block Model Validation – Part 1 Validation at Each Step • All estimates validated statistically and visually • Use of SAMPOUT file to confirm boundary conditions • Where estimation doesn’t accurately represent input data, return to domaining and raw data analysis • Peer Reviews and ‘sanity checks’ a
Slide 20: Block Model Validation – Part 2
Block Model Validation – Part 2 Estimation of Fe and S • Only two drillholes within the model area had Fe and S assays (although many to the south of the model area had assays) • Used logged pyrite as a proxy for Fe and S values, regression curve by lithology for pyrite logged vs. S%/Fe% • Data set
Slide 21: Classification
Classification Experience and Deposit-Specific Knowledge • Need to define your known unknowns – missing data is just as important as available data • Understand the estimate; domaining, boundary conditions, etc. • Not just reliant on data density, use all variables available • Solids were manually c
Slide 22: Reporting
Reporting Detail and Transparency • No RPEEE constraint provided for resource reporting, a reasonable cut-off grade had to be assumed • GT curve used to assist in resource cut-off grade selection, as well as experience in porphyry mineralisation MREs • 80-page report completed, which included work-f
Slide 23: Key Points
Key Points How/Why do we think we won? • Established geological context early – this became the engine which drove the entire resource estimate • Kept thorough and detailed documentation throughout, helped with reporting and made it easier to pick up errors • Breadth of experience was key – collabor
Slide 24: Thanks
Thanks • To our families, who deal with way too many late nights in the office • To the Hot Chili Executive Management for their encouragement to enter the Challenge • To the Parker Challenge Committee for making this fantastic idea come to life • To Rio Tinto for providing the data set for the chal
Slide 25: Qualifying Statements
Qualifying Statements National Instrument 43-101 (Canadian Reporting Standard) Joint Ore Reserves Committee Code (JORC) 2012 (Reporting Standard ASX) This PEA is preliminary in nature, includes inferred resources that are considered too speculative geologically to have the economic considerations ap
Slide 26: Mr Christian Easterday Harbor Access
Mr Christian Easterday Hot Chili Limited Managing Director ACN 130 955 725 E: admin@hotchili.net.au First Floor, 768 Canning Highway, Applecross, Western Australia 6153 PO Box 1725, Applecross, Harbor Access Western Australia 6953 Investor & Public Relations (Canada) P: +61 8 9315 9009 E: Graham.Far