Training courses in mining, oil & gas and environmental geostatistics
Geovariances offers general or business-oriented geostatistics training available worldwide in various languages. Courses cover all aspects of geostatistics for resource estimation, contamination characterization, mapping or risk analysis. We provide a variety of training options, including live public, in-house or online sessions, with standard contents or customized to your team’s unique needs.
Short course training, like the one provided by Geovariances, is an excellent option to acquire relevant knowledge and practical skills quickly and efficiently. Geovariances also supports the 5-week post-graduate training program called The Mining CFSG or Cycle de Formation Spécialisée en Géostatistique (Specialized Training Cycle in Geostatistics) provided by the Center for Geosciences from MINES ParisTech and leading to the award of a post-master degree in geostatistics. More info →
Choose the training best suited to your profile
Whatever your technical level or requirements, you will find a training adapted to your needs in our comprehensive course portfolio. Our courses range from short webinars and half-day introductory seminars to 3-5 day fundamental level training or advanced level workshops. Our programs are specifically tailored to your industry and your specific operational challenges and are conducted either in English, French, Spanish or Portuguese languages.
Develop the geostatistical skills you need
Our programs cover the whole geostatistics workflow, from data analysis and variography to advanced multivariate non-linear methods. With our courses, you can get a “hands-on experience” of the importance of key geostatistical concepts, rapidly develop valuable skills with our niche topics, improve your software practice or just get some insights on the added value of geostatistics. Training can be completed with mentoring for goal-oriented workshops.
Get your geostatistical training at the time you need it
You may pick up a public session from one of our catalogues. Or you can ask us to organize your specific training for you and your colleagues, privately and tailor-made to answer your unique requirements. You will then choose between instructor-led classroom covering 8 hours of content per day or live online solutions limited to 2 hours per session and 2 sessions per day. The choice is yours!
Learn from our experienced trainers
The skills you acquire with our experts help you build more reliable quantitative models and gain confidence in your results. Our trainers are senior geostatisticians, statisticians, geologists, mining or petroleum engineers adding up decades of experience in teaching geostatistics and carrying out consulting projects. They know your business and understand your specific challenges. They are also the ones who train the industry geostatistics experts.
Hear from our clients
Resources
Hydrogeological Facies Modeling
Stochastic Methods for geological modeling and links with fluid flow simulations
Whatever the application domain – oil & gas production, aquifer pollution characterization, uranium production by lixiviation – characterizing the geological parameters and capturing their variability is essential to ensure realistic flow modeling…
Time to Depth Conversion
Time to depth conversion of geological surfaces is critical for structural model building. Quantifying the uncertainty attached to the conversion is also of primordial importance for assessing GRV uncertainties. Traditional velocity models used in time to depth conversion could benefit from geostatistical techniques used in data integration. The advantage of using geostatistical methods is that they fit the data in one step and allow quantifying the uncertainty attached to the prediction by mean of the generation of equiprobable realizations.
Through Geovariances long-lasting experience in geostatistical depth conversion studies, learn how geostatistics helps you improve the accuracy of your reservoir structural model and assess the uncertainties on surfaces.
Mapping with auxiliary data
Through this white paper, discover how you canimprove significantly map reliability and quality by incorporating various sources of information in the interpolation process.
This document details the different methods for assimilating various sources of information, taking into account the reliability of each source and how the uncertainty associated with any mapping result can be estimated and reduced.
Data Quality Control
Before starting an evaluation of the contamination leading to decision-making tools for site clean-up, it is essential to ensure data quality. Thus, based on solid and reliable foundations, uncertainties occurring during the different steps of the decision process will be better controlled and the final quality of the project improved.
The objective of this white paper is to assess at best the validity of the data through visual, statistical and geostatistical basic tools before going further into their analysis.
Which block size for mineral resource estimation
A key aspect of mineral resource estimation (MRE) is the definition of the block dimensions used to estimate the deposit attributes.
A satisfactory compromise is to be found to get an estimate that allows making decisions upon volumes that are representative of the physical reality of the operation while being aware that the density of information available at the time of estimation probably does not warrant the direct estimation of such volumes.
Through this white paper, learn how to choose a relevant support size for mineral resource estimation.
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Contributions of the CETAMA working group n°10 on sampling and radiological characterisation (poster) | Anne Courtadon et Danièle Roudil, CEA Marcoule; Yvon Desnoyers, Geovariances; Didier Dubot, CEA; Guy Granier, IRSN; Catherine Ollivier-Dehaye, EDF
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Use of geostatistical modelling in investigation of soil contamination – working toward a better definition of remedial mass and volume | Per Loll, Ph.D. DMR A/S, T. Tsitseli, C. Larsen, DMR A/S A. Rokkjær, P. Johansen, H. Østergaard, N. Døssing Overheu, Capital Region of Denmark - NORDROCS 2018
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Co-kriging of log ratios: a worked alternative method | Clint Ward, Cliffs, Ute Mueller ECU
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Ramboll Data Management Methodology for Successful Geostatistical Analysis | Integrated Implementation of EQuIS and Kartotrak to Perform Pollution Characterization and to Design the Remediation of Industrial Sites
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Local Uncertainty Benchmarking – A coal case study | Written by C. Mawdesley, D. Barry, O. Bertoli and R. Saha
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Factorial kriging for estimating and mapping the geochemical background from in situ gamma dose rate measurements downstream of a former uranium mine | Journal of Environmental Radioactivity Volume 237, October 2021, 106681
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Use case 3: post accidental site remediation − CEA | EPJ Nuclear Sci. Technol. 6, 13 (2020) | Yvon Desnoyers and Claire Faucheux, Geovariances; and Nadia Pérot, CEA Cadarache
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Development of a user-friendly guideline for data analysis and sampling design strategy | EPJ Nuclear Sci. Technol. 6, 16 (2020) | Yvon Desnoyers, Geovariances and Bart Rogiers, SCK.CEN Belgian Nuclear Research Centre
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Modeling 3D soil lithotypes variability through geostatistical data fusion of CPT parameters | G. Vessia, D. Di Curzio, A. Castrignanò - Science of The Total Environment, Volume 698, 2020, 134340, ISSN 0048-9697
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Application of Pluri-Gaussian simulations and conditional simulation for geological modelling and estimation of a nickel deposit in New Caledonia | Febvey, M C, Desassis, N, Le Guen, M and Isatelle, F, 2019 - Proceedings Mining Geology 2019, pp 135–149 (The Australasian Institute of Mining and Metallurgy: Melbourne)