EET 1

Seismic Multiple Removal Techniques: Past, Present and Future

Instructor  Dr Eric Verschuur (Technical University Delft, the Netherlands)
Duration  1 day
Disciplines  Geophysics
Level  Intermediate
Language  English
Book  Available in EAGE Bookshop
CPD Points
 5

 

Introduction video

A short version of this course has been recorded as an E-Lecture. Watching this video will give you a clear introduction of what the course is about and it will help you to prepare yourself if you are going to attend it!

 

 

 

Course description 

The main objective of this course is to give the audience an overview of the techniques in seismic multiple removal, starting with the deconvolution-based methods from the 1960s, via the move-out discrimination techniques of the 1980s and ending up with wave-equation based methods from the 1990s and their 3D extensions as developed in the 2000s. Furthermore, the current challenges in multiple removal and their relation with seismic imaging and inversion are treated. A secondary objective is to discuss more general processing concepts such as high-resolution seismic data transforms (Fourier, Radon), adaptive filtering techniques, wave-equation based forward and inverse wave propagation and the processing of seismic data in different transform domains.

 

Course outline

At the end of each lecture, a list of relevant articles in the open literature will be specified. The course is subdivided in 10 lectures, each of them being approximately 30-45 minutes. Within each lecture, examples of the described concepts on synthetic and field data will play an important role.

Lecture 1: Multiples ... what’s the problem?
Classification of multiple reflections
Characteristics of multiples
Impact on seismic imaging and interpretation
Categories of multiple removal methods

Lecture 2: Multiple removal based on move-out
and dip discrimination

Principle of multiple removal by move-out discrimination
F-K and Radon transforms
Multiple removal by filtering in the FK or Radon domain
Towards high-resolution Radon transforms
Limitations of multiple removal by move-out discrimination
Multiple removal by target-oriented dip filtering

Lecture 3: Predictive deconvolution

Convolution and correlation concept
Designing adaptive filters by least-squares optimisation
Predictive deconvolution basics
Extending the predictive deconvolution concept

Lecture 4: Multiple removal by wave field extrapolation
Forward and inverse wave field extrapolation
Multiple prediction by wave field extrapolation
Application in the wave number and linear Radon domain

Lecture 5: Principles of surface-related multiple elimination
Derivation of SRME for the 1D situation
Including the source characteristics
Iterative implementation of SRME
Formulation of SRME for the 2D and 3D situation
Relation between multiple prediction and subtraction methods

Lecture 6: Practical considerations for surface-related multiple elimination
Effect of missing data on SRME
Interpolation of missing near offsets
Application of SRME in different data domains
Shallow water multiple removal strategy

Lecture 7: Adaptive subtraction of predicted multiples
Least squares and L1-norm subtraction
Pattern recognition and other multiple subtraction techniques

Lecture 8: Towards 3D multiple removal
Multiples in complex 3D environments
3D SRME: theory and practice
3D SRME: solutions via data interpolation

Lecture 9: Internal multiple removal
Internal multiple removal by move-out discrimination
Extending the SRME concept to internal multiples
Internal multiple removal by inverse scattering

Lecture 10: Removing or using multiples?
Transforming multiple into primaries
Estimation of primaries by sparse inversion
Including multiples in the migration process
Including multiples in the inversion process

 

Participants' profile

The target audience is composed of people involved in seismic processing, imaging and inversion. The mathematical content is kept to a minimum level with a strong link with the involved physical concepts, amplified by graphical illustrations.

 

Prerequisites

The audience is expected to have prior knowledge at B.Sc./M.Sc. level on processing concepts as convolution, correlation and Fourier transforms and some basic knowledge on wave theory.

 

About the instructor

Erik VerschuurDirk J. (Eric) Verschuur received his M.Sc. degree in 1986 and his Ph. D degree (honors) in 1991 from the Delft University of Technology (DUT), both in applied physics. From 1992 – 1997 he worked under a senior research fellowship from the Royal Dutch Academy of Art and Sciences (KNAW). In 1997 he became assistant professor and since 1999 he is an associate professor at the DUT at the laboratory of Acoustical Imaging and Sound Control. He is the project leader of the DELPHI research consortium in the area of Multiple Removal and Structural Imaging. His main interests are seismic modeling, processing and migration techniques. In 1997 he received SEG's J. Clarence Karcher award. He is a member of SEG and EAGE.

 

Is your company interested in hosting an EET? 

Hosting an EET course is a great deal! The host company should provide a training room and arrange lunch and coffee breaks. In exchange, EAGE will include your company's logo in our promotional material and allow you to send 10 free participants to the course.
 
If your company would like to host an EET course, write to education@eage.org

Interested in this course?

Check our Calendar of Events to learn when this Tour will visit your region. If you wish to attend but it is not scheduled near you, you can request the course as In-House Training.

 

Go to Calendar