Advanced Geostatistics for Reservoir Characterization

Learn the state-of-the-art in reservoir characterization and property and facies modeling using the stochastic simulations.

Learning objectives

  • Generate robust 3D reservoir static models using standard and advanced geostatistical simulation techniques. Discuss their pros and cons.
  • Improve model quality by integrating various data sources in the interpolation process and filtering seismic data.
  • Perform facies modeling with a focus on the analysis of proportion curves and the role of the stratigraphic reference surface.
  • Learn simulation techniques to populate the model with petrophysical properties constrained by the facies distribution.

Outlines

  • Introduction to the different concepts through a step by step workflow analysis and description.
  • 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 geologists, geophysicists and reservoir engineers involved in reservoir characterization.

Content

DAY 1: HORIZON MAPPING AND GEOPHYSICAL RESERVOIR CHARACTERIZATION

  • Overview of the standard geomodeling workflow
  • Data integration techniques (kriging in the multivariate case, kriging with external drift and kriging with Bayesian drift, kriging with uncertain data) with application examples in Time-to-Depth conversion and regional integration of seismic data
  • Introduction to geostatistical filtering of seismic data with factorial kriging
  • Application of geostatistical simulations for assessing uncertainty on maps

DAY 2: POPULATING A GEOLOGICAL MODEL WITH FACIES

  • Facies definition from logs with a geostatistical clustering technique
  • Presentation of facies distribution modeling concepts
  • Common simulation algorithms for categorical variables (facies)
    – Indicator simulations (SIS)
    – Truncated Gaussian (TGS) and Plurigaussian (PGS) simulations
    – Boolean simulations (object-based)
    – Multiple-Point Statistics (MPS)
    – Process-based approaches (Flumy)
  • Accounting for structural constraints in facies modeling

DAY 3: POPULATING A GEOLOGICAL MODEL WITH PROPERTIES – CONNECTIVITY INTEGRATION

  • Advanced analysis of petrophysical properties in facies
  • Common simulation algorithms for petrophysical properties
  • Volumetrics and quantification of the associated uncertainty
  • Accounting for dynamic data (honoring connectivity information)

Prerequisites

As the course refers to advanced geostatistical concepts, it is highly recommended that attendees have a reasonable knowledge of variography and kriging.

The course “Basic Concepts of Oil & Gas Geostatistics” covers the fundamental concepts of geostatistics for Oil & Gas and provides an ideal basis to this course.

CONTACT US

training@geovariances.com
Europe - Middle East - Africa - USA - Canada: +33 1 6074 9090
Asia-Pacific: +61 8 9321 3877
Latin America - The Carribean: +61 8 9321 3877