Geostatistical Inversion Using StatMod® and RockMod®


Anyone who wants to learn about principles behind state-of-the-art geostatistical inversion technology using StatMod® and RockMod®


We will review key concepts in statistics and geostatistics required for a deep understanding of the geostatistical inversion technology, in general, and StatMod® and RockMod®. The principle of Bayesian inference used to combine prior probabilities with beliefs and hypotheses to derive posterior probability, will be covered without the need of much mathematics. Important topics on conditioning of multi-disciplinary data for high-level integration in geostatistical inversion for different stages of the workflow, viz. geostatistical modeling, simulation, unconstrained and constrained inversion, uncertainty analysis and co-simulation will be discussed. Special emphasis on QC, analysis and interpretation of results from geostatistical inversion including ranking of multiple realizations to meet specific objectives in exploration, development and production will be included. Lastly, the course will focus on inverting directly for engineering properties using discretized rock physics models as input.

Learning Objectives

Participants will gain the technical and software skills to perform geostatistical inversion using StatMod® & RockMod® modules of JasonWorkbench; QC and analyze & interpret the results with minimal supervision. Participants will have a grasp of the key aspects of the workflow to generate seismically-constrained engineering properties using RockMod®.



Number of Participants


Knowledge of deterministic inversion & proficiency in using Jason Workbench

Software Used

StatMod® and RockMod® Jason Workbench

Course Format

Lecture and practical software exercises

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