Isatis.neo Fundamentals | Training course

Learn how to get started with Isatis.neo and quickly get to grips with software use.

Objective

Isatis.neo is Geovariances’ comprehensive software solution in geostatistics. Designed for every business dealing with spatialized data, the software enables thorough data analysis and visualization, produces high-quality maps and models, and allows you to carry out extensive uncertainty and risk analyses that optimize your decision-making process.

By attending this course, you will:

  • Get introduced to Isatis.neo functionalities for data analysis and estimation,
  • Understand how to get started with the software and quickly get to grips with its use.

Key Features

  • Computer exercises using Isatis.neo and real-life datasets. Depending on the participants, datasets of various origins can be used for the training: air quality, soil pollution, oil reservoir, mine orebody.
  • Course material provided (documentation, journal files, training data, worked examples) for re-use in your workplace.
  • Depending on the participants, the course will be held in French or English.

Who should attend

Geologists, geoscientists, environmental engineers, anyone wishing to gain the skills needed to start using Isatis.neo with confidence or find out more about the many capabilities of the software.

Course content

1| OVERVIEW OF ISATIS.NEO TOOLS AND CONCEPTS

  • User interface and data management. Become familiar with the software interface, the application menu, and data organization. Learn how to set up a project.
  • 3D Viewer. Visualize, explore, and gain an understanding of data. Control every detail of your model.
  • Reporting. Quickly produce and edit your study report using the software’s integrated word processor.
  • Calculator (based on Python syntax). Modify or create new variables from a set of various functions and operators.
  • Introduction to batch scripting for workflow automation. Record your actions and store your parameter settings in a script file. Rerun the whole study in a single click with new data.

 

2| DATA LOADING

  • Import point, grid, boreholes data through dedicated interfaces. Identify variables according to their type for proper use (coordinates, properties, etc.).

 

3| DATA ANALYSIS

  • Statistics. Generate various statistical graphs and charts (histograms, box-plots, cross-plots, swath-plots, etc.) and control the quality of your data. Identify possible data outliers, anisotropies, trends, etc.
  • Variography. Quantify the spatial variability of a variable through the calculation, interpretation, and modeling of the variogram (2D and 3D). Get acquainted with the various parameters (lag, sills, one or several directions, one or several variables) and the model reaction to changes in the settings.

 

4| ESTIMATION

  • Grid creation. Define a suitable grid and cell size for output estimates.
  • Kriging Neighborhood Analysis. Evaluate the quality of a neighborhood to select the most adequate one regarding the actual input dataset and variography.
  • Kriging. Be introduced to the different kriging options available in Isatis.neo (point or block, simple or ordinary, universal or with external drift, univariate or multivariate).
    Become familiar with the involved parameters.
  • Cross-validation. Validate and select the variogram model that provides the best estimates.

 

5| GEOSTATISTICAL SIMULATIONS (optional part, depending on participants’ requirements)

  • Data pre-processing. Transform a raw dataset into a gaussian-distributed one. Model an anamorphosis function. Calculate and model the related gaussian variogram.
  • Simulations. Run Turning Bands simulations on gaussian transformed data. Obtain a set of possible realizations of a variable in the raw space.
  • Post-processing. Learn how to derive various statistics for proper uncertainty and risk analysis.

Prerequisites

This course is dedicated to practical exercises with Isatis.neo, and no theoretical reminders about geostatistics will be provided. Participants are then required to have a fundamental knowledge of geostatistics, including variography and kriging.