A powerful new Estimation Manager enables more efficient estimation of multiple domains or variables and rapid parameter testing.

It automatically combines the estimation tasks (quick interpolation or kriging) you have defined in a single interface. Then, you can effortlessly duplicate the tasks, switch input data, output tables and selections, define new output file names, and rerun one or more estimations with new settings in a single click. Ultimately, this allows you to automate estimations without coding a batch process and thus improve your efficiency.

A new lag slider lets you quickly check visually how the experimental variogram and related variogram model behave when changing the lag value.

This helps you choose the optimal lag for capturing the spatial behavior of your data. This new tool is available for omnidirectional, multidirectional, and downhole variograms.

A new tool allows you to easily load the variogram models from a Supervisor project into Isatis.neo.

You can import all the variograms associated with a Supervisor dataset at once or select which one to import in your 2D or 3D project.

• You can now fully customize your color palettes by entering RGB values or importing them from a CSV file.
• Isatis.neo data explorers now have “expand” and “collapse” options to quickly show or hide associated objects.
• In EDA, you can choose to display the experimental variogram only, the model only, or both of them.
• The 3D Viewer Explorer allows you to organize displayed items into folders for easier visibility.

A new Local Parameter Fitting tool allows for local adjustment of variogram and neighborhood parameters to improve estimation accuracy.

It uses a cross-validation method to derive local variograms and neighborhoods on a coarse grid from a given variogram and neighborhood set. These local parameters can be used in various Isatis.neo applications, such as kriging, conditional simulations, proportion modeling, Plurigaussian simulations, and Sequential Indicator Simulations.

The local parameters are the rotations of all structures of the variogram model, the sill and range factors applied to all structures of the variogram model, and the rotation and the radius of the neighborhood.