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E-241C - Advanced Multivariate Geostatistics Certification

5 days GRE/GEOSTAT
Level
Advanced
Audience
  • Experienced geoscientists involved in data interpretation and management.
  • Recommended for geologists, geophysicists and reservoir engineers involved in integrated reservoir studies.
Purpose
  • This course provides participants with a comprehensive technical knowledge and to get familiar with geostatistical methods used in Geophysics, Reservoir Characterization and modeling studies.
Learning Objectives
  • Upon completion of the course, participants will be able to:
  • have 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,
  • 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.
Prerequisite
  • Engineering or geoscience degree, or equivalent professional experience.
Ways and means
  • Lectures and hands-on activities
  • Practical examples and laboratory exercises will be performed using dedicated software Isatis™

Multivariate data analysis 1 day
  • Statistics: distributions, mean, variance, correlation coefficient, linear regression
  • Multivariate statistical analysis: PCA, canonical analysis
  • Variograms and cross-variogram: the linear model of coregionalization
Cokriging & its variations 1 day
  • 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 1 day
  • 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
Factorial kriging & factorial cokriging 1 day
  • 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 1 day
  • 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