Fundamentals of Geostatistical Reservoir Modeling | Training course

Get a comprehensive overview of commonly geostatistical methods applied to geophysical and geomodeling workflows, from seismic data QC to reservoir characterization


The course objective is to present the basic concepts and methods underlying the use of geostatistics for Oil & Gas in general but with a particular focus on Reservoir Characterization.

Key Features

The course presents the theoretical background of Geostatistics. The main tools are introduced and their use in geological modeling is detailed. At the end of the training, participants will be able to:

  • Understand the main assumptions of classical geostatistical algorithms, with their pros and cons,
  • Have a critical point of view about probabilistic reservoir characterization projects,
  • Attend courses dedicated to advanced geostatistical topics.

Who should attend

Any geoscientist or reservoir engineer involved in the building or use of geomodels. No prior knowledge about geostatistics is required.

Course content

  • General overview of geostatistics for Oil & Gas applications:
  • Reminders about basic probability and statistics: distributions, mean, variance, correlation coefficient, linear regression, Monte-Carlo simulations.
  • Importance of data sampling, model resolution, scales.
  • The basic tool of geostatistics: quantifying spatial correlation with the variogram.
  • Model fitting, classical variogram models.
  • Interpolation of data: kriging theory. 2D-3D examples.
  • Factorial kriging and its applications for the removal of seismic noise/artifacts.
  • Multivariate geostatistical framework for regionalized variables (Model of coregionalization) and collocated cokriging. Application to property mapping.
  • Non stationary geostatistics and trend modelling: trends and residuals, kriging with external drift. Application to depth conversion and setup of the structural model.
  • Geostatistical simulations of continuous variables (surfaces, petrophysical variables): sequential Gaussian and turning bands.
  • Simulation post-processing.
  • Volumetrics (GRV, HCPV …). Spill point analysis.
  • Facies simulations: pixel-based approaches (SIS, PGS) and MPS, object based, process-based (Flumy) methods.