Categorical workflow · Facies model · PGS & SIS scripting
Need a repeatable categorical-modeling pipeline? Script Isatis.py operations for indicator kriging, PGS and SIS, then generate and review facies models.
Workflow automation · Large dataset · Anisotropy configuration
Need reproducible simulation pipelines? Script Isatis.py operations for continuous realisations, HDF5 files, support options, local anisotropy and validation.
Need to automate spatial estimation? Configure Isatis.py workflows for variograms, simple and ordinary kriging, validation and polygon-based domain handling.
Need a repeatable data-preparation pipeline? Script Isatis.py operations for vizualisation, declustering, drillhole compositing, PCA, and contact analysis.
Custom calculations · Python libraries · Data processing
Go beyond built-in formulas. Use the Isatis.neo Python Calculator to create custom data treatments, integrate Python libraries and turn project-specific logic into reusable calculations.
Build realistic geological models that reflect complexity and uncertainty. Apply indicator kriging, SIS, TGS, PGS and implicit modeling through hands-on workflows in Isatis.neo.
Build realistic geological models that reflect complexity and uncertainty. Apply indicator kriging, SIS, TGS, PGS and implicit modeling through hands-on workflows in Isatis.neo.
Deep Kriging · Geometallurgical domains · Lithology classification
Put machine learning to work on real geoscience and mining challenges. Build, evaluate and apply classification and regression models by connecting scikit-learn with Isatis.neo.
Model complex geological patterns beyond traditional two-point methods. Learn MPS simulation with DeeSse in Isatis.neo, from training images to realistic uncertainty-aware realizations.
Turn spatial data into sound decisions. Learn to analyze datasets, map surfaces, model subsurface properties and quantify uncertainty with practical geostatistical workflows.
Deep Kriging · Geometallurgical domains · Lithology classification
Put machine learning to work on real geoscience and mining challenges. Build, evaluate and apply classification and regression models by connecting scikit-learn with Isatis.neo.
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