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Academia

University partnerships

AR2Tech offers a useful and powerful platform for teaching and research.

Science and lights

We are strongly rooted in the world of academic research and innovation. Our libraries are suited to many facets of geostatistics and can be applied to a wide range of academic research and classroom teaching. Professors, researchers and students have used our software and libraries for journal publications and conferences across several disciplines.

Academic partners

For classes and projects

The basic version of our library SGeMS is free and can be used in classrooms for any project related to spatial statistics. It is currently used in prestigious institutions such as Stanford University, McGill University, Université de Neuchâtel, Universidade Federal do Rio Grande do Sul in Porto Alegre, and many others.

For research and publication

We provide researchers with a geostatistical platform ready for research and publications. SGeMS can easily be used by the non-geostatisticians as a source of standard algorithms such as kriging or indicator simulation on applications as diverse as petroleum reservoir, ore deposit, aquifer characterization or ecological habitat. The researcher aiming to create new algorithms is able to do so by leveraging its powerful libraries containing the necessary building blocks to an algorithm.

For plug-in development

Several innovative components of AR2Gems have been created by the community of developers, fulfilling their particular needs and offering their solutions to the community of users. We are happy to help and work with you to transform your prototype code into a robust, maintained, and integrated part of the geostatistical standard.

Neon Grid

A community of practitioners and developers

Geostatistical libraries have been offered to the scientific community since the publication of GSLib, a suite of Fortran sources offering a base of geostatistical algorithms for the community to use and adapt. The development and deployment of SGeMS started in 2006 by Nicolas Remy a graduate student at Stanford University. The common geostatistical algorithms were coded from scratch in C++ in addition to new algorithms such as Multiple-Point Geostatistics. The next step in innovation came from AR2Tech, with a completely redesigned suite of tools that rely on the best available numerical libraries used in the scientific community. With such a history of development, the community of users is large, comprises a diverse suite of disciplines (oil and gas, mining, environmental, ...), contexts (academia, industry, public sector) and has users around the world. We are currently building a forum, download, and support site for the community to discuss and move forward with innovations.