Training
Geological modeling by geostatistics
Objectives
- Unlock the skills to build reliable, realistic, data-driven geological models that capture uncertainty, boosting the credibility of your subsurface interpretations and empowering you to make smarter, more confident decisions.
- Get hands-on with powerful geostatistical methods, such as Indicator Kriging and simulations (SIS, TGS, PGS), and apply them using Isatis.neo’s intuitive tools, including implicit modeling and the Unfolding feature, to tackle complex stratigraphy with confidence.
Target audience
Ideal for professionals in mineral resource evaluation, geological surveys, geotechnical engineering, and petroleum exploration who want to strengthen their geological or facies modeling skills. Whether you’re aiming to build more robust models or integrate uncertainty assessments into your workflows, this training will help you make better-informed, data-driven decisions.
Content
Foundations & Indicator Kriging
─ Discover indicator kriging, how it works, and when to use it.
─ Learn how to apply it in practice in Isatis.neo to build geological models and define domains.
Conditional Simulations
─ Learn about the main facies simulation methods: sequential indicator simulation (SIS), truncated Gaussian simulation (TGS), and multi-Gaussian simulation (PGS).
─ Understand their principles, key steps, and differences.
─ Implement them in Isatis.neo using the dedicated options.
Implicit Modeling
─ Explore how to use potential fields to model stratigraphic units or intrusive bodies automatically.
─ Create consistent and continuous surfaces from geological data.
Unfolding
– Handle geological structures that have been folded or deformed.
– Learn how to “unfold” these structures and convert complex geometries into a flattened space where continuity is more isotropic and easier to model.
What the course includes
- Balanced learning approach. Theory paired with practical applications, so you understand and apply the concepts.
- Hands-on software training. Computer exercises in Isatis.neo, on real datasets.
- Personalized feedback. Individual guidance from experienced trainers throughout the online sessions.
- Comprehensive resources. A temporary software license, course documentation, journal files, and datasets to keep and reuse after the course.
- Certificate of completion issued at the end of the session.
Prerequisites
- A solid understanding of linear geostatistics, such as variogram analysis and kriging, is recommended. The course Mineral Resource Estimation by Linear Geostatistics provides an excellent foundation.
- Prior experience with Turning Bands Simulation is highly recommended.
The trainer
Pedram Masoudi, PhD, HDR
Senior Consultant Geostatistician & Geophysicist
A consultant and trainer at Geovariances, Pedram is skilled in geostatistical modeling and the integration of geological and geophysical data. He supports clients on mineral resource estimation (JORC-compliant), petroleum reservoir characterization, geological facies modeling, geotechnical studies, and contaminated-soil mapping, notably in radiation-protection contexts.
Register, or ask us first
This form handles all three: registration, a quote for yourself or your team, and questions about the content or the prerequisites.
Address
44 Avenue de Valvins, 77210 Avon, France