CFSG 2022: new online format, new teachers for the training program in geostatistics by the Paris School of Mines. Book your seat now!

October 19, 2021

The Geostatistics Team from MINES ParisTech and Geovariances bring together their experts and teachers to offer in 2022 a new online edition of their Specialized Training Cycle in Geostatistics, known as CFSG, a high-level and comprehensive training program in mining geostatistics.

CFSG 2022 is a 10-week comprehensive online training program in geostatistics spread over ten months starting from February 2022. It is meant for mining geologists and engineers who are willing to achieve a high level in geostatistics or refresh their skills.

By attending this training program, participants review all aspects of mining geostatistics, learn the theory behind each technique and put their new knowledge into practice through numerous exercises and a real-life project. They return to work with a solid understanding of the theory and application of geostatistics for mineral resource estimation.

The program is made of 6 modules. The first one is mandatory and lasts 3 weeks. The 5 following modules can be attended à la carte, independently from each other, and last 1 or 2 weeks depending on the topic. The knowledge acquired in each module is validated through an examination. You receive a training certificate for all validated modules.


CFSG Program Content


Price: 4,950 € – Duration: 15 days

Learn the fundamentals of mining geostatistics for resource estimation and build your first block model.

  • Statistics for Mineral Resources
    February 14-18 CET or May 9-13 AWST
    This 1st week will refresh you on regionalized variables and key statistics (univariate and multivariate) for data analysis and quality control, and subsequent geostatistical analysis. You will also learn how to calculate selectivity curves (tonnage, grade, and metal).
    The afternoon practical sessions will introduce you to Isatis.neo Mining Edition and to the management of a project and various types of data sets.
  • Modeling the spatial continuity
    February 28-March 4 CET or June 13-17 AWST
    During this 2nd week, you become acquainted with data spatial behavior. You learn how to quantify the spatial continuity of grades through experimental variograms (one-dimensional, multi-dimensional, anisotropic) and delve into the involved parameters. You are introduced to variogram modeling, review model properties, and modeling pitfalls.
    You learn to achieve exploratory data analysis, compute experimental variograms and adjust variogram models with Isatis.neo Mining Edition.
  • In-situ resources
    March 14-18 CET or June 27-July 1 AWST
    This 3rd week will initiate you to local resource estimation. The course provides a detailed review of standard interpolation techniques (i.e., moving mean, nearest neighbor, inverse distances) and kriging (simple, ordinary, intrinsic) and their properties and pitfalls. You will learn how to define a kriging neighborhood relevant to your data and validate the choice of parameters with cross-validation.
    You will build your first block model with Isatis.neo Mining Edition.


Price: 3,950 € – Duration: 10 days

Learn how to improve estimation with multivariate geostatistics or by constraining the block model with geological trends.

  • April 4-8 CEST or July 18-22 AWST
    During this 1st week, you will become acquainted with multivariate geostatistics. You will be introduced to domaining, point, and spatial correlation, and learn about multivariate statistics (simple and cross variograms), and estimations (cokriging and collocated cokriging).
    During the hands-on sessions, you will learn how to analyze contacts between domains using Isatis.neo Mining Edition, compute and adjust multivariate variograms, and run cokriging.
  • April 25-29 CEST or August 1-5 AWST
    The 2nd week reviews non-stationary phenomena. You will learn to identify trends through swath plots or experimental variograms and take into account these trends through kriging with external drift.
    You will practice kriging with external drift with Isatis.neo Mining Edition.


Price: 3,950 € – Duration: 10 days

Learn how to compute recoverable resources considering mining selectivity and quantify the uncertainties.

  • May 30-June 3 and June 20-24 CEST or September 5-9 and September 19-23 AWST
    These two weeks will detail the techniques for recoverable resource estimation according to cutoff grades: simulations (sequential gaussian and turning bands) for a rigorous analysis of the uncertainties and non-linear models (indicators, top-cut, conditional expectation). You will be introduced to the gaussian transformation, the change of support, and the information effect.
    You will practice point and block simulations, Uniform Conditioning, and Direct Block Simulations with Isatis.neo Mining Edition.


Price: 2,950 € – Duration: 5 days

Learn how to compute realistic geological facies models.

  • September 12-16 CEST or October 3-7 AWST
    During this week, you will be introduced to the categorical variables and get a comprehensive insight into various techniques of geological facies modeling (the sequential methods, the boolean model, the plurigaussian model, the process-based model).
    During the practical sessions, you will learn how to compute a facies proportions model and run Sequential Indicator Simulations and Plurigaussian Simulations with Isatis.neo Mining Edition.


Price: 2,950 € – Duration: 5 days

Get introduced to a powerful machine-learning-based technique for geological domaining.

  • October 10-14 CEST or October 17-21 AWST
    During this week, you will delve into the Geostatistical Hierarchical Clustering techniques to identify domains and classify drill-hole samples into homogeneous classes. You will learn about the potential field method for domain implicit modeling and be introduced to two approaches considering the genesis of the geological deposit: sedimentary or tectonic.
    You will practice sample clustering for automatic domaining and domain modeling with Isatis.neo Mining Edition.


Price: 2,950 € – Duration: 5 days

Learn innovative and machine-learning-based techniques that improve performance.

  • November 14-18 CET or November 21-25 AWST
    This last week will introduce you to innovative and unique methodologies that facilitate handling big data sets and speed-up processes, such as the SPDE simulations.
    You will also get insights into some of the reference Machine Learning techniques which open new avenues for realistic realizations of complex environments.


  • Half of the training program is devoted to methodological presentations, the other half to practical exercises to deepen the understanding of concepts.
    – The methodological courses are given
    by MINES ParisTech professors and are scheduled in order to match the time zone of the audience. For more convenience, these courses are recorded and made available to participants.
    The practical sessions will be driven by Geovariances’ consultants, either from our French office (for those whose time zone is compatible with the French one) or from our Australian and Brazilian offices for the other participants.
  • A typical training week would then be:
    – Monday, Tuesday, and Wednesday: theoretical course (on a half-day) and hands-on practice with Isatis.neo Mining Edition (on the half-day following the theoretical course).
    – Thursday or Friday: Homework using Isatis.neo Mining Edition with compulsory rendering at the end of the day.
    – Friday: Live correction and comments from the teaching team. Validation of prior learning.
  • CFSG 2022 is a certification training. The knowledge acquired in each module is validated through an examination. At the end of each module, you will get a training certificate with a distinction giving official recognition to the full completion of the module.
  • Course material and a temporary software license are provided.
  • Registration to all 6 modules gives you a discount of 25%.
  • A minimum number of 5 participants is required for a module to actually take place.