Geostatistics for Seismic Data Integration in Earth Models

2003 SEG/EAGE Distinguished Instructor Short Course

by Olivier Dubrule

Duration: One day

Intended Audience: Entry; geoscientists who have been exposed to geostatistics but would like to clarify the basic concepts and assumptions.

Prerequisites (Knowledge/Experience/Education Required): Very basic statistical knowledge, and some exposure to existing geostatistical software and applications.

In recent years the use of geostatistics has spread from the world of reservoir characterization to that of velocity analysis, time-to-depth conversion, seismic inversion, uncertainty quantification, and more generally to that of seismic data integration in earth models. Nevertheless, many geoscientists still regard geostatistics as little more than a statistical black box. By explaining the concepts and applications, this course clarifies the benefits of geostatistics and helps spread its use.

Course Outline:
The course covers the use of geostatistics for interpolation (kriging, etc.), heterogeneity modeling (conditional stimulation), uncertainty quantification, and data integration (cokriging, geostatistical inversion, etc.). A variety of applications and examples are presented, including velocity mapping, construction of realistic heterogeneity models, and seismic data integration in stochastic earth models. The relationships between geostatistics and approaches more familiar to geophysicists, such as filtering or bayesian methods, are also discussed, without entering into mathematical details. A number of case studies are presented, covering examples from various parts of the world.

The short-course presentation, limited to one day, provides an overview of basic concepts and applications. The course notes provide a support to the course and further extend some of the more technical considerations.

Learner Outcomes:
As a result of attending this course, geoscientists, and more specifically geophysicists, will better understand how geostatistics fits into their workflow, what tools and techniques they should use depending on the problem at hand, and what added value may result from its use. More specifically, after attending the course, geoscientists wiil be able to:

  • Define the right variogram to use in order to quantify their geological knowledge
  • Recognize the main assumptions that have been made in a given geostatistical study.
  • Interpret the results of a geostatistical heterogeneity modeling exercise, whether based on kriging or conditional simulation
  • Choose among the various geostatistical modeling methods proposed by earth modeling software

Instructor Biography:
Olivier Dubrule