Isatis.neo | Geostatistics made accessible
Go Beyond Geostatistics with Isatis.neo
Unleash the full power of your spatial data with Isatis.neo, the most advanced and comprehensive geostatistical software available today.
Isatis.neo empowers you to explore, analyze, and visualize your data with unmatched precision. Build robust, high-confidence models, generate insightful and impactful maps, and perform sophisticated uncertainty analyses to support confident, data-driven decisions.
Trusted across industries, Isatis.neo is transforming spatial data workflows in:
– Mining: Optimize resource estimation and mine planning with greater certainty and precision.
– Oil & Gas: Enhance reservoir modeling and deepen your understanding of uncertainties to maximize production efficiency.
– Subsurface and Geological Surveys: Accurately assess subsurface conditions to inform construction and energy infrastructure projects.
– Bioresources: Improve sustainable management of fish stocks, forests, and other natural resources.
– Air Quality Monitoring: Strengthen environmental risk analysis and human exposure models through more accurate and reliable spatial modeling.
Why choose Isatis.neo
– Simplify complex geostatistics — Isatis.neo transforms intricate geostatistical processes into streamlined workflows, enabling you to focus on insights rather than software complexities.
– Tailored for your industry — Available in Standard, Mining, and Petroleum editions, Isatis.neo addresses specific industry needs with specialized tools. A preconfigured workflow enables efficient seismic time-to-depth conversion with comprehensive uncertainty analysis.
– Leverage cutting-edge technology — With advanced algorithms and machine learning integration, Isatis.neo ensures high-performance analysis and modeling.
Key features
– Intuitive interface — User-friendly design for efficient navigation and operation.
– Comprehensive toolset — From exploratory data analysis to advanced simulations.
– Automation & customization — Automate tasks and customize workflows with Python scripting.
– High compatibility — Supports various data formats and integrates seamlessly with other software.
– Robust reporting — Generate detailed reports with integrated word processing tools.
– Read more →
Hear from our customers
Discover Isatis.neo at our upcoming events
Training
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July 7-11, 2025CFSG Module D: Facies simulations
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1er sept. 2025Estimation des ressources récupérables avec la géostatistique non-linéaire – Module 1 : Conditionnement Uniforme
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2-3 sept. 2025Estimation des ressources récupérables avec la géostatistique non-linéaire – Module 2 : Krigeage d’Indicatrices Multiples et Espérance Conditionnelle
Resources
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Isatis.neo – Reveal the true nature of the subsurface. Gain a reliable understanding of subsoil structure and heterogeneity | Integrate geostatistics into your modeling workflow to uncover deeper insights, reduce uncertainty, and make smarter, risk-informed decisions with confidence.
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Isatis.neo Standard Edition (version française)
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Isatis.neo Mining Edition
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Isatis.neo Standard Edition
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Conversions & Uncertainties Workflow – Isatis.neo Petroleum Edition
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Enhancing environmental radionuclides tracking: High-resolution isotopic analysis using NanoSIMS | Presented at Goldschmidt Pragues 2025 - Louise Darricau (IRSN)
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Application de la géostatistique dans l’analyse de risque géotechnique lié à la liquéfaction du sol (vidéo) | Gestion des Données et Nouvel Environnement numérique en Géotechnique - Journée technique CFMS 15 nov 2022
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Amélioration de l’estimation des teneurs en alumine d’un gisement de kaolin à l’aide des simulations par bandes tournantes | XVe Journées de géostatistique 2021 - V. Bouchet (Imerys), M.C. Febvey (Geovariances), Hélène Binet (Geovariances), Armand Dubus (Geovariances)
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Utilisation d’un algorithme de classification par Machine Learning pour la caractérisation géomécanique des sols | CFMS 2020 - par Marie-Cecile Febvey
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Co-kriging of log ratios: a worked alternative method | Clint Ward, Cliffs, Ute Mueller ECU
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Coherent modeling of mineral grades and zones by coupling cokriging and Support Vector Machine | Authors: P. Masoudi, J. Langanay , R. Rolo - Presented at MMME’25 (www.international-aset.com)
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Using multiple-point geostatistics for geomodeling of a vein-type gold deposit | A. Zhexenbayeva, N. Madani, (School of Mining and Geosciences, Nazarbayev University, Astana, Kazakhstan), P. Renard, J. Straubhaar (Stochastic Hydrogeology Group, University of Neuchatel, Neuchatel, Switzerland) - Applied Computing and Geosciences 23 (2024)
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Mapping Groundwater Level by Geostatistical Methods: Ordinary Versus Universal Kriging; Alongside a Discussion on Neighbourhood | P. Masoudi (Geovariances), C. Faucheux (Geovariances), H. Binet (Geovariances) - 85th EAGE Annual Conference & Exhibition, Jun 2024, Volume 2024, p.1 - 5
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3D Modelling of Standard Penetration Test in the Framework of Assessing Liquefaction Risk | P. Masoudi (Geovariances), H. Binet (Geovariances), C. Simon (EDF-DI-TEGGM), B. Pelletier (EDF-DI-TEGGM), C. Faucheux (Geovariances), F. Rambert (Geovariances), Y. Assy (Geovariances) - EAGE GeoTech 2024 Fourth EAGE Workshop on Distributed Fibre Optic Sensing, Apr 2024, Volume 2024, p.1 - 5
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Plurigaussian conditional simulation (PGS) of the Budenovskoe uranium roll-front deposit, central Kazakhstan: 3D model of the host sedimentary sequence | M. Abzalov, D. Renard - Applied Earth Science. 2023;132(3-4):227-235