ISATIS, THE REFERENCE SOFTWARE IN GEOSTATISTICS
Isatis is the most comprehensive and advanced general purpose geostatistics toolbox. First released 25 years ago, it is widely recognized as the reference geostatistical software solution.
Isatis addresses very different issues from various industries, enabling thorough data analysis and visualization, quality mapping, accurate resource estimation, advanced geomodeling, risk analysis. It offers a robust and sound geostatistical technology which is continuously improved, year after year.
Isatis connectivity with premier software packages makes it easy to integrate in your day-to-day workflow.
Get trusted results
Adopting Isatis means you take advantage of a tried and tested software solution by more than 5000 users from various industries, including mining, oil & gas and environment, but also a bunch of fields like hydrogeology, oceanography, forestry, agriculture or archeology. You enjoy efficient and reliable algorithms originating from the Center of Geostatistics (Mines ParisTech) and that have been benchmarked and constantly improved since Isatis 1st release.
Boost your productivity
You need to gain time with repetitive tasks. With Isatis, you benefit from an integrated environment in which all operations can be stored and reproduced in an automatic way. You are able to set up production workflows through scripting procedures that can be run in a click for a fast and easy updating of your models. Besides, Isatis optimized and parallelized algorithms make you save time on heavy computations.
Benefit from a leading technology
Your needs change over time. We are listening to your concerns and ideas and make Isatis continuously evolve. Each year, you enjoy innovative methodologies derived from our research consortia for enhanced geostatistical models. This is one reason why 95% of our customers renew their software maintenance contract year after year. Other ones are the top-level technical support provided and the free access to comprehensive technical resources.
Solve any problem, even the unusual ones
Your data is unique and your modeling objectives too. Isatis gives you access to the most exhaustive set of proven and state of the art geostatistical methodologies, with an impressive number of available kriging and simulations algorithms, giving you the means to address all your issues. And Isatis being a workflow-free flexible toolbox, it is easy for you to design your own process, standard or original.
Hear from our customers
“I used Isatis for optimizing drillhole spacing. This saved considerably on drilling costs and on time.”
"Minestis is revolutionary in that it completely democratizes advanced geostatistics at the mine site with minimal input from a consultancy or head office. Combined with Isatis,these two software packages can add immense value to any company with concomitant minimization of risk"
"Isatis maintenance contract gives us easy access to innovation which improve our day-to-day work and the possibility to guide the software developements according to our needs. Ore valorization, selective exploitation,..."
"O Isatis permite uma abordagem científica para a analíse exploratoria de dados, avaliação e classificação de recursos minerales que permite confiabilidade e consistencia."
"O Isatis é um software de geoestatística completo, o qual possui um pacote integrado de ferramentas em que nenhum outro disponível no mercado possui."
Discover Isatis at our upcoming events
Can you afford to bypass advanced geostatistics for the sake of productivity? Is it really a smart business decision?
A little extra time and human resources devoted to the use of above standard geostatistical procedures will prove highly beneficial from a...
With the "Sampling Density Variance" tool, Isatis proposes an innovative methodology allowing robust resource classification, independant ...
Geovariances is pleased to provide Isatis licenses to all participants of Dr. Abani Samal's geostatistics short course at SME Annual Confe...
Vous souhaitez en savoir plus sur la pertinence de la géostatistique pour vos projets de démantèlement et d'assainissement ? Venez en d...
You wish to learn more about a new workflow to handle Time-Depth Conversion? Come and listen to David Garner presentation on behalf of Ge...
Attend our oral presentations while at the conference to better understand the major role of geostatistics in decommissioning projects...
Du 24 au 26 septembre 2018L’Estimation des Ressources Minérales : Les Fondamentaux
Sept. 24-27, 2018 9:00 am to 11:00 am CETBasic Concepts of Geostatistics for the Oil & Gas industry – Data Analysis and Variography
Du 27 au 28 septembre 2018L’Estimation des Ressources Minérales : Perfectionnement
Co-kriging of log ratios: a worked alternative method | Clint Ward, Cliffs, Ute Mueller ECU
Local Uncertainty Benchmarking – A coal case study | Written by C. Mawdesley, D. Barry, O. Bertoli and R. Saha
Sensitivity study of the estimation variance approximation of a quotient | Comparison with Conditional Simulations in the Mn Deposit of Bangombé (Gabon)
Key Functionalities new module Studio RM 2016 | Presented by Olivier Bertoli at the UC2016 event organized in the UK by Datamine
Fitting cross-variogram models and Pesky negative Eigen values | David Barry, Geovariances
Interpolation of GPS and Geological Data Using InSAR Deformation Maps: Method and Application to Land Subsidence in the Alto Guadalentín Aquifer (SE Spain) | Remote Sens. 2016, 8, 965; doi:10.3390/rs8110965 | www.mdpi.com/journal/remotesensing | Keywords: InSAR; aquifer; subsidence; interpolation; kriging with external drift
Updated Radiological Inventory of G1 Reactor Thanks to a Strengthened Data Processing | Y. Desnoyers (Geovariances), M. Da Costa (CEA), M. Magnin (CEA), V. Lerat (CEA) | Presented at WM2017 Conference
Spatial variability of soil nitrogen forms and the activity of N-cycle enzymes | J. Długosz, A. Piotrowska-Długosz
Space-Temporal Variation in Underground Water Some Quality Parameters in Klodzko Water Intake Area Using Statistical and Geostatistical Methods (SW Part of Poland)
Recoverable resource estimation for an underground manganese project using multivariate conditional simulation with scenario reduction