Basic Concepts of Geostatistics for the Oil & Gas Industry| Training course

Learn the basic concepts and methods underlying the use of geostatistics for data QC, surface mapping, property modeling, and uncertainty quantification.

This training can be delivered online on request, through instructor-led virtual sessions. Contact us for more info.

Learning objectives

  • Get introduced to the different uses of geostatistics for Oil & Gas applications.
  • Learn the theory and practice of classical geostatistics methodologies for reservoir modeling, with their pros and cons.
  • Learn how to integrate various data sources in the interpolation process to improve mapping quality.

Outlines

  • Half of the course is devoted to theoretical and methodological presentations, the second half to practical exercises on real-life cases to deepen the understanding of concepts. The focus is on illustrations and practical contributions of the covered concepts.
  • Computer exercises with Isatis.neo Petroleum Edition.
  • Course material provided (documentation, journal files, training data, worked examples) for re-use in your workplace.

Who should attend

This course aims at any geoscientist or reservoir engineer involved in the building or use of geomodels who want a practical, synthetic, and pragmatic introduction to geostatistical methods for reservoir characterization.

Content

DAY 1 (ONLINE SESSIONS 1 AND 2): DATA VARIABILITY ANALYSIS

  • Introduction
    Overview of geostatistics applications for Oil & Gas.
    Reminders about various statistical graphs and charts (histograms, mean, variance, box-plots, cross-plots, swath-plots, linear regression, etc.).
    – Importance of data sampling, model resolution scales.
    Data quality control. Identification of possible data outliers, anisotropies, trends, etc.
  • Understanding and estimation of the spatial heterogeneity of the studied phenomenon
    – 
    A practical introduction to the concepts of heterogeneity and spatial variability.
    – Quantification of the spatial variability: calculation, interpretation, and modeling of the variogram.

DAY 2 (ONLINE SESSIONS 2 AND 4): MAPPING AND UNCERTAINTY ANALYSIS

  • Mapping of a continuous variable (e.g. depth, porosity)
    – 
    Review of classic deterministic interpolation methods.
    – Kriging (2D/3D). Principles and properties. Map uncertainty.
    – Integration of one or several secondary (i.e. dense seismic data) or fuzzy data in the interpolation. Analysis of the correlations between variables. Multivariate variogram. Co-kriging.
  • Uncertainty quantification
    – Introduction to the conditional simulations for uncertainty quantification.
    – Difference between kriging and conditional simulations.
    – Probabilistic maps.
    – Risk analysis.
  • Non-stationary geostatistics and trend modeling
    Trends and residuals.
    Kriging with external drift.
    – Application to depth conversion and setup of the structural model.

Prerequisites

No prior knowledge about geostatistics is required. The course is ideal for newcomers to geostatistics or for someone wanting a refresher.

These two days may be complemented by one or two of the 3-day modules that delves into some of the most advanced geostatistical techniques, giving hints and pitfalls on how to use them: “Advanced Geostatistics for Geophysicists” and “Advanced Geostatistics for Reservoir Characterization”.