Training
Isatis.py training – Module 6: Indicators estimation and simulations
Where this module sits
The Isatis.py course is delivered in six 3-hour modules that you can take separately or in sequence:
– Module 1: Introduction to Python. Get acquainted with Python and explore how Isatis.py is connected to this programming language.
– Module 2: Exploratory Data Analysis. Master Exploratory Data Analysis (EDA) to effectively explore data using Isatis.py.
– Module 3: Kriging. Master kriging using Isatis.py.
– Module 4: Continuous simulations. Master simulations and uncertainty quantification using Isatis.py.
– Module 5: Multivariate estimation. Master multivariate estimation using Isatis.py.
– Module 6: Indicators estimation and simulations. Master estimation and simulation of indicators and categorical variables using Isatis.py.
Objectives
Categorical modeling workflows must coordinate estimation, simulation, and output generation in a reproducible script. Using a synthetic mineral deposit dataset, you will implement Isatis.py operations for indicator kriging, Plurigaussian Simulation, and Sequential Indicator Simulation. The hands-on workflow brings the three configured operations together to generate and review facies models.
Target audience
Company developers, geoscientists, and data scientists with Python scripting experience and a recommended practical geostatistics background who implement categorical and facies workflows with Isatis.py.
Content
Configure categorical estimation
– Configure and run indicator kriging on categorical data through Isatis.py.
Script categorical simulations
– Configure and run Plurigaussian Simulation (PGS).
– Configure and run Sequential Indicator Simulation (SIS).
Generate and review facies outputs
– Combine the three operations in a hands-on Python workflow based on the confirmed mineral deposit dataset.
– Generate and review facies models from categorical variables.
What the course includes
- Hands-on software training. Computer exercises in Isatis.py, using real datasets.
- Personalized feedback. Individual guidance from experienced trainers throughout the online sessions.
- Ready-to-reuse resources. A temporary software license, course documentation, journal files, and datasets to keep and use after the course.
- Certificate of completion. Issued at the end of the session.
Prerequisites
Python scripting experience is required. If needed, start with Module 1, Introduction to Python. Practical geostatistics knowledge is also recommended, as this course focuses on implementing workflows rather than teaching the methods.
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
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