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  • Introduction to Resource Estimation with Python

Introduction to Resource Estimation with Python

  • 23 Nov 2018
  • 8:30 AM - 5:00 PM
  • Canada Learning Code, Unit 501, 129 Spadina Avenue 501, Toronto, Ontario M5V 2L3, Canada
  • 0


  • A student ID will be required at the door

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Adrian Martinez Vargas, Senior Resource Geologist, CSA Global


Are you a professional geologist hoping to gain new confidence in using the powerful Python programming language or a student looking to develop fundamental skills in resource estimation?

The TGDG is delighted to host an interactive workshop covering the fundamentals of Python for resource estimation with Adrian Martinez Vargas.

This training will provide you with an introduction to Python and other powerful Open Source software tools* for analysing geological data. Using these tools, we will dive into mineral resource estimation using Pygslib – a python module for mineral resource estimation and geostatistics.

During this 1-day practical workshop you will undertake key resource estimation tasks:

  • import drill hole exploration data,
  • create and display drill hole objects,
  • model a geological unit,
  • select samples within the geological model,
  • statistically analyse and process drill hole assay values,
  • generate a block model and code it with geology,
  • estimate block model values,
  • validate the estimation results,
  • and report the mineral resource estimate.

Bonus: Your resource estimation workflow will be recorded as an interactive Python script providing a complete record of the training exercise. For resource geologists this script has two valuable features: 1. It is auditable, allowing chosen parameters and assumption to be reviewed in future; and 2. It can be used to reproduce the estimate or update the estimate with new data.  

In addition to learning the fundamentals of Python for mineral resource estimation, you will acquire useful Python skills that can be applied to a variety of other tasks. For example: working with common data and 3D model formats used in exploration and mining, accessing files that are too big for Excel to handle and visualizing geological data in 3D using Open Source software*.

We hope this training will spark an interest in Python, a tool that has an enormous number of applications in Geology ranging from mining to machine learning.

* Open source software will include: Jupyter Notebook, NumPy, Pandas, and ParaView.

Speaker Bio:

Adrian is both a geologist and a geostatistician. He produces open source software for geostatistics and mineral resources in Python, Fortran, Cython, C and SQL. He has worked as a consultant since 2002 covering many commodities including gold, copper, nickel, chromium, and industrial minerals.

Adrian has considerable experience using multiple indicator kriging for resource estimation of gold deposits with high nugget and domaining issues; with non-linear geostatistics and with conditional simulations for resource estimation and model validation.

Adrian has previously worked as an Assistant Professor in Cuba and Ethiopia, teaching geology and geostatistics.

Intended Audience:

This course is designed for students and young mining professionals looking to learn the basics of geological data manipulation with the user friendly computational language, Python.  No previous experience in resource modelling or using Python is necessary.  Participants should have an understanding of drill hole database construction and basic methods for statistical analysis of exploration data. 

This is an incredible opportunity that the TGDG is pleased to offer at a very economical rate as part of their commitment to support valuable and resume building educational events for students and young mining professionals.


Student: $50

Member: $100

Non-member: $150 (Registration for non-TGDG members - includes annual TGDG membership for remainder of 2018-2019 season.)

Course fees include lunch and refreshments.


Registrants will need to bring their own laptops.  Software will be provided. Registrants will be notified by email with download and installation instructions.

This event will not be broadcast


Maximum Capacity: 38

Student Cap: 15

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