RCM/MGEOSTAT

## Who should attend?

• This course provides participants with a comprehensive technical knowledge and to get familiar with geostatistical methods used in Geophysics, Reservoir Characterization and Modeling studies.
Audience :
• This certification is designed for experienced geoscientists involved in data interpretation and management. Recommended for geologists, geophysicists and reservoir engineers involved in integrated reservoir studies.

## Course Content

• ### MULTIVARIATE DATA ANALYSIS

• Statistics: distributions, mean, variance, correlation coefficient, linear regression.
• Multivariate statistical analysis: PCA, Min-Max autocorrelation factor.
• Variograms and cross-variogram: the linear model of coregionalization.
• ### COKRIGING & ITS VARIATIONS

• Kriging theory: building the kriging system of equations, kriging weights behavior, cross-validation.
• Generalization of kriging to the multivariate case: cokriging.
• Particular case of collocated cokriging.
• ### KRIGING WITH AUXILIARY VARIABLES

• Kriging with trend: universal kriging formalism.
• Kriging with external drift.
• Comparison between collocated cokriging and kriging with external drift.
• Kriging with Bayesian drift.
• Kriging with fuzzy data.
• ### GEOSTATISTICS & CLASSIFICATION

• Clustering methods for ElectroFacies calculation.
• Enhancing clustering by integrating spatial constraints.
• Pitfalls in ElectroFacies calculation and characterization.
• ### FACTORIAL KRIGING & FACTORIAL COKRIGING

• Multi-components variograms (univariate and multivariate cases).
• Factorial kriging theory.
• Application to data filtering.
• Seismic filtering with multiple acquisitions.
• ### GEOSTATISTICAL SIMULATIONS IN THE MULTIVARIATE CASE

• Reminder about geostatistical simulations, comparison with kriging.
• Theoretical overview of co-simulations of continuous variables.
• A multivariate facies simulation method: truncated Pluri-Gaussian Simulations (PGS).
• Complex sedimentary patterns modeling with PGS.
• ### SUMMARY & TEST

• Summary of the studied methods and their applications: Q&A session.
• Final examination.

## Learning Objectives

• Upon completion of the course, participants will be able to:
• acquire a practical approach to the industrial methodology of reservoir characterization and modeling, in particular with geostatistical tools and methods,
• use geostatistical tools and methods (variograms, kriging, cokriging, external drift, simulations),
• use geostatistical methods for seismic data filtering and Time-to-Depth conversion,
• use geostatistical methods for enhancing classification for ElectroFacies determination,
• choose ways for property simulations using geostatistical algorithms: facies (pixel and object methods); petrophysics (gaussian methods),
• constrain 2D or 3D properties distribution using various information (e.g. geology, seismic and dynamic data) of different nature and accuracy,
• use industrial software dedicated for geostatistics.

## Ways & Means

• Lectures and hands-on activities. Practical examples and laboratory exercises will be performed using dedicated software: Isatis™.
• Software used during workshops: with courtesy of Geovariance.

## Certification

• An international recognition of your competencies.
• A Advanced Certificate is delivered.
• An expertise confirmed in Advanced Multivariate Geostatistics .