SGeMS

SGeMS (Stanford Geostatistical Modeling Software) is an open-source software platform for geostatistical modeling and simulation. It provides a modular environment for data management, variography, and conditioning simulations, with a focus on multiple-point statistics (MPS). The software is designed to support both traditional two-point methods and MPS techniques, enabling users to build stochastic geological models from sparse data by using training images to encode complex spatial patterns.

SGeMS offers a graphical user interface and a set of command-line tools to support workflows such as data loading, variogram estimation, training image creation, and conditional simulation. Core features include training-image based MPS simulators (such as SNESIM) alongside standard geostatistical methods. It can handle 2D and 3D grids, supports importing common data formats, and exports models and realizations for visualization or further analysis. The architecture is modular, allowing researchers to extend the platform with new algorithms or components and to customize workflows to specific applications.

Applications of SGeMS span geosciences and engineering, including mineral and petroleum reservoir modeling, groundwater hydrology, and environmental site characterization. By combining conditioning data with geological knowledge embedded in training images, it enables generation of multiple realizations that honor both data and qualitative spatial patterns.

Development and availability: SGeMS is an open-source project supported by a community of users and developers. Documentation, tutorials, and example training images are available on its project pages and repositories, facilitating learning and collaboration.