Geostatistical Filtering of Seismic Data

Learn how to design a data driven filter to remove noise and footprints.

Objective

This course will help you understand the geostatistical filtering key principles for seismic cubes cleaning. At the end of the course, you will know how to build an optimal filter for each dataset.

Session 1

Seismic filtering for univariate case:

  • Presentation of factorial kriging and kriging with filtering
  • Demonstration with Isatis: Velocity and amplitude filtering

Session 2

Seismic filtering for bivariate case:

  • Presentation of multi-acquisition factorial kriging
  • Demonstration with Isatis: application to 4D signature enhancement

Session 3

Filtering enhancement with Local Geostatistics:

  • Determining local values for kriging parameters
  • Impact of the use of local parameters

Session 4

Link between geophysics and geostatistics:

  • The covariance and the power spectrum
  • The spline interpolation and kriging

Introduction to stochastic inversion

Prerequisites

Knowledge of Kriging theory and practice.


IMPORTANT

The course is delivered in one-to-one 4×2-hour online training sessions over 4 consecutive days by our experienced instructors.

You only need an internet connection and headphones with a microphone.

Although examples are given with Isatis software, the concepts and methodologies that will be addressed can easily be applied using your usual geomodeling software package.

This course is part of a live online training program to quickly get acquainted with the essential concepts and methodologies of geostatistics applied to reservoir characterization and modeling​.

Courses are given as one-to-one sessions for quality content, better suited to your needs and issues, and facilitated exchange between trainee and trainer.

Note that if the provided scheduled dates are not compatible with your agenda, we invite you to contact us to arrange your own schedule. Course content may also be adapted to your needs on demand.

To learn the fundamentals of geostatistics:

To go further with geostatistics: