Isatis.neo - What's New?
Isatis.neo 2026.1 (July 2026)
Isatis.neo 2026.1 introduces practical enhancements across data exchange, data preparation, statistical analysis, interpolation workflows and result visualization. This release helps you export richer datasets, prepare cleaner inputs, extract more insight from charts and simulations, and improve readability across the interface.
More flexible data exchange
The Export Polygons OGR functionality has been enhanced to support exporting associated variables in addition to polygon geometry, whenever such variables are available. Support for the GeoJSON format has also been added, making it easier to exchange polygon data with other tools and workflows while preserving more useful information.
Import Vulcan and Export Vulcan workflows now include a coordinate unit selector. Since Vulcan files do not store coordinate unit information, you can specify the unit used by the Vulcan file at import or the unit to write at export, and Isatis.neo automatically applies the corresponding coordinate and block-size conversions.
Smarter data preparation
The Look for Duplicates task now includes a new Grid sampling algorithm. This mode keeps at most one sample per cell of a regular virtual grid, making it easier to thin dense datasets and avoid preserving several nearby samples in the same area. You can either keep the sample closest to the cell center or select a random sample in each cell, while previewing the grid directly in a 2D or 3D scene to validate the sampling settings.
In Compositing / Well discretization, a new Uniform composite residual spreading mode improves the management of residual intervals when compositing by length. When the residual is greater than half the target composite length, an additional composite can be created and the interval is redistributed evenly, producing strictly uniform composite lengths and more consistent support.
More informative statistical analysis
The Cross Plot now supports iso-frequency classes for the Conditional expectation curve. Each class contains the same number of data points, which gives a more balanced view of the relationship between conditioning and target variables when the data distribution is uneven. As in the regular mode, the related conditional expectation statistics can still be printed in the Messages window and stored in a chart file.
More flexible interpolation and simulation review
Quick Interpolation now supports saving interpolation weights. For each target point, you can store the sum of the interpolation weights used for the selected variable, making it easier to review how the estimate is supported and to keep track of interpolation behavior directly in your output data.
A new Use simple kriging option is now available in both Kriging and Simulations workflows. This makes it possible to perform Simple Kriging even when the input Geostatistical Set is defined with Ordinary Kriging, provided that a strictly stationary model is used. The mean can be defined either as a constant value or as locally varying means, giving you more flexibility to adapt interpolation and simulation settings to your modeling strategy.
Simulation Post-processing has been extended to support categorical simulations in addition to numerical ones. A dedicated Categories tab now provides outputs such as category probabilities, most probable and least probable categories, probability difference, entropy and the Soares uncertainty criterion, allowing you to derive meaningful uncertainty indicators without rerunning the simulations.
In Simulation Validation, the calculation of directional variograms has been enhanced for variables defined on points or sub-blocks, including the simulation macro-variable as well as comparative and auxiliary variables. In addition to the lag and maximum distance, the calculation now also takes into account the Slicing Radius in 3D or the Slicing Width in 2D, providing a more explicit and consistent control of the directional variogram analysis.
In the Upscaling task, the Categorical mode now offers more control over how statistics are organized in the final table. Results can be displayed by variable or by category, making the output easier to read and better aligned with your reporting needs.
Clearer tables across the interface
New Table Styling preferences let you customize the default appearance of tables displayed in Isatis.neo. You can define the header background and text colors, cell background and text colors, as well as the border color and width, with a preview available before applying the settings. This improves readability for statistics shown in the interface, including results displayed in the Messages window and in tasks such as Grade Tonnage Curves and Tables.
