Seismic data filtering and depth conversion with geostatistics

• 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.

• 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.

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

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

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”.