Introduction

Geostatistics for Resource Estimation Training Course is designed to equip professionals with advanced skills in mineral resource modeling, ore body estimation, spatial data analysis, and mining geostatistics workflows. In today’s data-driven mining and exploration industry, accurate grade estimation, mineral reserve classification, and uncertainty quantification are critical for optimizing project value and reducing operational risk. This training integrates modern geostatistical methods, machine learning integration, variography, kriging techniques, and 3D geological modeling to support decision-making in exploration and mining projects.

Participants will gain hands-on expertise in applying Ordinary Kriging, Indicator Kriging, Sequential Gaussian Simulation, spatial interpolation, and resource classification standards. The course is tailored to bridge theory and practice using real mining datasets, ensuring professionals can confidently deliver high-precision resource models, grade control strategies, and mine planning inputs. With a strong focus on industry applications, this program empowers geologists, mining engineers, and data scientists to improve resource confidence levels, optimize drilling strategies, and enhance economic valuation of mineral deposits.

Programme Curriculum

Geostatistics for Resource Estimation Training Course

Introduction

Course Duration

5 days

Course Objectives

Master geostatistical theory and spatial data analysis
Apply variogram modeling and structural analysis
Perform ordinary and universal kriging for resource estimation
Implement indicator kriging for ore/waste classification
Develop 3D geological and block models
Conduct grade estimation and mineral resource modeling
Understand uncertainty quantification in mining datasets
Apply conditional simulation techniques
Interpret drillhole data and compositing methods
Integrate mining software workflows
Ensure compliance with JORC and NI 43-101 reporting standards
Optimize drill spacing and sampling strategies
Build capability in data-driven mine planning and decision support systems

Target Audience

Exploration geologists
Mining engineers
Resource geologists
Geostatisticians and data scientists
Mine planning engineers
Geological modelers
Metallurgists involved in grade control
Graduate students in mining and earth sciences

Course Modules

Module 1: Foundations of Geostatistics in Mining

Introduction to spatial statistics and mining datasets
Random variables and spatial continuity
Sampling theory and support effect
Data distribution and transformation techniques
Introduction to mining data structures
Case Study: Iron ore deposit sampling variability analysis and spatial trend interpretation.

Module 2: Exploratory Data Analysis (EDA) & Data Conditioning

Drillhole data validation and cleaning
Compositing techniques and declustering
Statistical summaries and outlier detection
Grade population analysis
Data domaining and geological control
Case Study: Gold deposit drillhole dataset cleaning and compositing for estimation readiness.

Module 3: Variography & Spatial Structure Modeling

Experimental variogram construction
Nugget, sill, and range interpretation
Anisotropy modeling in ore deposits
Variogram fitting techniques
Nested structures in mineralization
Case Study: Copper porphyry deposit variogram modeling for directional continuity.

Module 4: Kriging Techniques for Resource Estimation

Ordinary Kriging fundamentals
Block Kriging and point estimation
Kriging efficiency and validation
Search ellipsoid design
Neighborhood parameters optimization
Case Study: Nickel laterite deposit estimation using Ordinary Kriging.

Module 5: Advanced Geostatistical Simulation

Sequential Gaussian Simulation (SGS)
Conditional simulation principles
Indicator simulation for categorical data
Uncertainty modeling in ore grades
Multiple realization analysis
Case Study: Diamond deposit grade uncertainty modeling using SGS.

Module 6: 3D Geological Modeling & Resource Classification

Wireframing and geological domains
Block model construction
Density and tonnage calculations
Resource classification
Reporting standards compliance
Case Study: Platinum group metals (PGM) resource classification for JORC reporting.

Module 7: Mine Planning Integration & Optimization

Linking resource models to mine planning
Cut-off grade optimization
Production scheduling inputs
Grade control strategies
Economic evaluation of ore bodies
Case Study: Open-pit coal mine optimization using block model outputs.

Module 8: Industry Applications & Digital Mining Transformation

Machine learning in geostatistics
Automation in resource estimation
GIS and spatial analytics integration
Cloud-based geological modeling
Real-time mine data integration
Case Study: Smart mining project integrating geostatistics with AI-driven ore prediction.

Training Methodology

Interactive lectures and presentations.
Group discussions and brainstorming sessions.
Hands-on exercises using real-world datasets.
Role-playing and scenario-based simulations.
Analysis of case studies to bridge theory and practice.
Peer-to-peer learning and networking.
Expert-led Q&A sessions.
Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@fineskilltrainingcenter.org or call +254769199797

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to Fineskill Training Center account, as indicated in the invoice so as to enable us prepare better for you.

Skills & Software Covered

Kriging Variogram analysis Resource modeling Spatial statistics

Programme Fee

Duration: 5 Days

Method: Online or Physical

Online Price: $1,000

Physical Price: $1,500

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Nov 02 2026

02 Nov — 06 Nov 2026

💻 Online / Virtual session

Online $1,000