Isatis.py training – Module 4: Continuous simulations | Training course
Master the development of Python workflows for continuous variable simulation and uncertainty quantification using our geostatistics library, Isatis.py.
Objectives
- Exploit Isatis.py’s simulation and post-processing tools through hands-on practice with a real-world mineral deposit dataset, acquiring skills in coding uncertainty quantification workflows.
- Learn Python coding best practices. Create clear, high-quality Python scripts for easy interpretation.
- Enhance your geostatistical expertise and practical skills.
Module content
- Selection from meshes
- Anamorphosis
- Big data management (through HDF5 files)
- Turning Bands Simulations
- Sequential Gaussian Simulations
- Block versus point simulations
- Simulation validation
- Simulation with local anisotropies
- Uncertainty visualization
Key features
- Receive documentation, training datasets, and reusable Python scripts to apply in your workplace.
- The course is available in French or English, based on participants’ preferences.
Additional modules
The Isatis.py training program comprises a series of 6 modules that can be completed independently:
- Module 1: Introduction to Python
3 hours
Get acquainted with Python and explore how Isatis.py is connected to this programming language. - Module 2: Exploratory Data Analysis
3 hours
Master Exploratory Data Analysis (EDA) to effectively explore data using Isatis.py. - Module 3: Kriging
3 hours
Master kriging using Isatis.py. - Module 5: Multivariate estimation
3 hours
Master multivariate estimation using Isatis.py. - Module 6: Indicators estimation and simulations
3 hours
Master estimation and simulation of indicators and categorical variables using Isatis.py.
Who should attend
Designed for geologists, geoscientists, environmental engineers, and professionals looking to develop their skills in creating customized, flexible, and efficient geostatistical workflows based on Python scripts.
Prerequisites
Prior knowledge of scripting with Python is required to participate, and a solid background in practical geostatistics is recommended.