Seismic data filtering and depth conversion with geostatistics

Understand and master the use of geostatistics for reliable time-to-depth conversion and comprehensive uncertainty analysis of reservoir volumes.

Objective

  • Understand and implement geostatistics to build robust reservoir structural models.
  • Improve seismic data quality with geostatistical filtering.
  • Make the best use of all available data to achieve robust time-to-depth conversion.
  • Perform quantified uncertainty analysis on traps and reservoir volumes.

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 with workflow.
  • Individual work reviewed and corrected by the trainer during online courses.
  • Course material provided (documentation, journal files, training data, worked examples) for re-use in your workplace.

Who should attend

This course aims at geophysicists involved in data interpretation and mapping of surfaces limiting the reservoirs.

Content

SESSION 1: QC AND FILTERING

  • Quality control of seismic data
    – Identify possible data outliers, anisotropies, trends, etc.
  • Understanding and filtering of several artifacts (noise, footprints, acquisition artifacts)
    – Quantification of the spatial variability: calculation, interpretation, and modeling of the variogram.
    – Seismic filtering by kriging (2D/3D): principles and properties.

SESSION 2: TIME-TO-DEPTH CONVERSION

  • Multivariate geostatistics for time-to-depth conversion
    – Integration of seismic data or velocity model parameters and wells information in the interpolation. Analysis of the correlations between variables. Multivariate variogram. Co-kriging.
    – Multi-layer approach and Bayesian techniques to reduce the uncertainties.

SESSION 3: UNCERTAINTY ANALYSIS

  • Uncertainty quantification
    – Introduction to the conditional simulations for uncertainty quantification.
    – Difference between kriging and conditional simulations.
  • Trap analysis and volumetrics
    – Probabilistic maps.
    – Risk analysis.
  • How to find the best model
    – Introduction to Geostatistical Inversion.

SESSION 4: EXERCISES WITH ISATIS.NEO AND CONVERSIONS & UNCERTAINTIES WORKFLOW

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 “Data Analysis and Property Modeling with Geostatistics” covers the fundamental concepts of geostatistics for Oil & Gas and provides an ideal basis to this course.

You can practice further with Isatis.neo Conversions & Uncertainties Workflow by attending the course “Seismic Time-depth Conversion in Practice”.