CFSG Module B: Recoverable resources with nonlinear methods

The CFSG (Specialized Training Cycle in Geostatistics) is a high-level training program in mining geostatistics delivered by the Geostatistics Team from Mines Paris and Geovariances. This program aims to equip you with an in-depth understanding of geostatistics for mineral resource estimation, enabling you to create block models your company needs for confident mine planning when you return to work. Throughout the training, you will learn the theoretical aspects of the techniques presented and practice them through various exercises and a real-world project.

CFSG is intended for individuals whose time zone is aligned with Europe (France) and the Americas (Brazil). It will be delivered online in 6 modules over 9 weeks throughout 2024, starting in February.

This module is the second one of the CFSG series. At the end of it, you will be able to estimate recoverable mineral resources accounting for mining selectivity.

THEORY

• Selectivity curves for recoverable resources
  Reminders:
  – Rules for selection: cutoff and support (sample vs. Selective Mining Unit)
  – Tonnage, Average Grade, Metal and Conventional Benefit
  – Support effect of the variable
  – Information effect
  Limitations of Linear Kriging
  Non-linear estimation vs. simulations

• Non-linear models
  The indicator approach:
  – Coding data into indicators
  – Indicator properties
  – Simple models (mosaïc, diffusive)
  – Simple and cross-variograms of indicators
  – Transition probabilities (border effect)
  – Cokriging of indicators and post-processing
  The Top-Cut Model:
  – Splitting the input variable into three parts: the capped grade, the exceedance, and the indicator of the exceedance
  – The modeling stage: choosing the threshold for capping and variogram fitting
  – Cokriging the three ingredients
  The Gaussian approach:
  – Translating the Anamorphosis function into Hermite polynomials
  – Conditional Expectation, Multi-gaussian Ordinary Kriging
  – Example: lognormal kriging
  Change of support:
  – Global viewpoint:
  . Change of support and Information  Effect
  . Selectivity curves at different support sizes
  – Local viewpoint:
  . Discretizing the orebody into small blocks
  . The multi-support model (panel, block, and point)
  . Processing: Conditional Expectation, Direct Block Simulation, Uniform Conditioning

PRACTICE

Several exercises to learn how to run Uniform Conditioning,  Direct Block Simulations and post-processing (statistics, simulation reduction, grade-tonnage curves) with Isatis.neo Mining Edition.

Each module can be attended independently of each other. However, it is important to note that completion of Module A or having experience in geostatistics and Isatis.neo is a prerequisite for participation in any of these modules.

• Module A: Geostatistics Fundamentals (mandatory)
  May 13-24 & June 3-14, 2024 – 20 days
  Learn the fundamentals of mining geostatistics for block modeling.
• Module C: Non-stationary geostatistics (optional)
  Sept. 16-20, 2024 – 5 days
  Learn how to constrain the block model with geological trends.
• Module D: Facies simulations (optional)
  Sept. 30 – Oct. 4, 2024 – 5 days
  Learn how to achieve reliable and realistic facies modeling.
• Module E: Domaining (optional)
  Nov. 18-22, 2024 – 5 days
  Get introduced to a powerful machine-learning-based technique for geological domaining.
• Module F: Coupling Machine-Learning and geostatistical techniques using Python (optional)
  Dec. 9-13, 2024 – 5 days
  Learn how to implement Machine Learning techniques in Python code for data classification.

• 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 Paris professors.
  – Geovariances consultants will drive the practical sessions from our French office.
  – For more convenience, these courses are recorded and made available to participants during the session and until one month after the end of the course.

• A typical training week would then be:
  – Monday, Tuesday, Wednesday, and Thursday: theoretical course (on a half-day) and hands-on practice with Isatis.neo Mining Edition (on the half-day following the theoretical course).
  – Friday: homework using Isatis.neo Mining Edition with compulsory rendering at the end of the day. Live corrections and comments from the teaching team. Validation of prior learning.
• CFSG is a full-time training. You are required to be present/connected for the duration of the sessions.
• CFSG 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 that officially recognizes the full completion of the module.
• Course material and a temporary software license are provided.
• A minimum number of 8 participants is required for a module actually to take place.

The CFSG training program is meant for mining geologists and engineers willing to achieve a high level of geostatistics and boost their careers.

Module A is ideal for newcomers to mining geostatistics. Modules B and F are designed for individuals who wish to delve into more advanced geostatistics.

The course is delivered in English and requires a good level of this language. Sound notions of mathematics are also recommended.

As the course is online, a good quality internet connection is required. We also appreciate that the participant’s camera is turned on for the session.​

Benefit from the trainers’ high expertise in geostatistics

From Mines Paris – PSL

From Geovariances

What alumni say about CFSG