Course overview
Geological data is spatial and sparse: a few boreholes have to stand in for vast volumes of rock. Geostatistics is the science of making the most of that data, estimating values between samples, quantifying how properties vary across space, and putting honest numbers on the uncertainty. Combined with modern data analytics, it turns scattered measurements into models that support real decisions.
This course covers geostatistics and data analytics for geology. It runs from the fundamentals through data collection and management, variography and spatial correlation, kriging and interpolation, simulation and uncertainty, and data analytics and visualization, ending with case studies. It is built for geoscientists and technical professionals who work with geological data and want to analyze it rigorously.
Why this matters
Decisions in mining, oil and gas, and the environment rest on estimates made from limited data, and getting the geostatistics wrong means resources over- or under-estimated and money misallocated. Ignoring uncertainty is especially dangerous, since it hides how much the estimate could be off.
Geostatistics matters because it extracts the most from scarce, expensive data and quantifies the uncertainty that decisions depend on. Professionals who can apply it make sounder estimates and better decisions. This course builds that capability.
What you will be able to do afterwards
By the end of the course, participants should be able to:
- Explain the principles of geostatistics.
- Collect, clean, and manage geological data.
- Use variography to describe spatial correlation.
- Apply kriging and interpolation methods.
- Use simulation to quantify uncertainty.
Course outline
Unit 1: Introduction to geostatistics and geological data
The course opens with the fundamentals.
- What geostatistics is.
- The nature of geological data.
- Spatial data concepts.
- Applications across sectors.
Unit 2: Data collection, cleaning, and management
This unit covers the data foundation.
- Data sources and quality.
- Cleaning and validating data.
- Managing geological datasets.
- Preparing data for analysis.
Unit 3: Variography and spatial correlation
This unit covers describing variation.
- The variogram.
- Spatial correlation and continuity.
- Modeling variograms.
- Interpreting spatial structure.
Unit 4: Kriging and interpolation methods
This unit covers estimation.
- Kriging principles.
- Types of kriging.
- Other interpolation methods.
- Producing estimates.
Unit 5: Simulation and uncertainty analysis
This unit covers the honesty of the numbers.
- Geostatistical simulation.
- Quantifying uncertainty.
- Multiple realizations.
- Using uncertainty in decisions.
Unit 6: Data analytics and visualization tools
This unit covers the toolkit.
- Analytics for geological data.
- Software and workflows.
- Visualization.
- Communicating results.
Unit 7: Case studies
The final unit applies it.
- Documented geostatistics case studies.
- Lessons and pitfalls.
- Best practices.
- Applying it to your work.
How the course is delivered
The course is led through structured explanation, worked technical examples, documented case studies, and group discussion. Participants examine spatial data, variograms, and estimation outputs and work through how estimates and uncertainty are produced. For the spatial-data angle, it connects to GIS and Spatial Data Analysis for Geoscientists.
Who should attend
This course suits geoscientists and geologists, mining and reservoir professionals, and technical staff who work with geological data. It works for those new to geostatistics and for experienced staff who want to strengthen their estimation and uncertainty skills. A scientific or technical background helps.
About EuroQuest International Training
EuroQuest International Training was founded in 2015 by a team with more than 25 years of combined experience in professional training. The institute has delivered over 1,000 courses to more than 15,000 participants, and is headquartered in Bratislava, Slovakia, with training hubs in Dubai, London, Barcelona, Istanbul, Vienna, Paris, and Geneva. Courses are designed and reviewed by practitioners and updated to reflect current practice in each field.
Frequently asked questions
Do I need a strong mathematics background?
A technical background helps, since geostatistics is quantitative, but the course builds the concepts as it goes and focuses on applying and interpreting methods rather than deriving them.
Does it cover kriging and simulation?
Yes. Dedicated units cover kriging and interpolation and geostatistical simulation, including quantifying and using uncertainty.
Is it tied to one industry?
No. Geostatistics applies across mining, oil and gas, and environmental geology, and the course draws examples across them.
Related courses
- Geospatial Analytics and Predictive Modeling
- Seismic Data Analysis and Interpretation
- Petroleum Reservoir Characterization and Modeling
- Big Data Analytics and Predictive Modeling
Register for this course
To reserve a place or ask about scheduling and city options for the Geostatistics and Data Analytics in Geology course, use the registration and enquiry options on this page and the EuroQuest team will follow up with the details you need.
All Course Dates & Locations
31 dates · 14 cities · Sep 2026 – Jul 2027