3D Surface Related Multiple Elimination


The course is designed for anyone wanting a clear in-depth understanding of the convolutional multiple modeling and the wave-field modeling, two 3D Surface Related Multiple Elimination (SRME) methods.


This course begins with a review of multiples, what they are, how and why they are generated and provides a classification for the various types.

It then provides an overview of the 3D SRME technique. The SRME method proposed by Verschurr and Berkhout in 1992 and commonly referred to as the Delft method is outlined theoretically and simplified graphically. The convolutional modeling methodology and workflow are discussed from the preprocessing, binning and regularization through model generation. The alternative wave-field modeling method is explained and the differences between the two methods are discussed. The applicability of the methods is put in context by reviewing the types of survey settings versus the multiple attenuation effectiveness. Adaptive subtraction is presented.

Finally the participants work with a 3D dataset, moving through the data preparation, model generation and subtraction for both methods. Throughout the workflow emphasis is placed on parameter verification and QC.

The main topics covered during the course include

• Review of multiples and their classification
• What is the SRME method commonly known as the Delft method?
• The 3D SRME by convolutional approach, the theory and methodology
• A need for shot location at each receiver location versus 3D acquisition
• The 3D SRME by wavefied modeling, the theory and methodology
• The benefits and drawbacks of the two methods and their applicability
• The multiple model and adaptive subtraction
• The workflow – preprocessing, model generation and subtraction using the two methods
• Parameter testing and QC

Learning Objectives

• Know what surface related multiples are
• Be able to describe the Delft method
• Know the principle for both 3D SRME using convolution and using wave-field modeling
• Be able to list the benefits and drawbacks of the two methods
• Be able to carry out the workflow and generate a multiple model
• Understand the key parameters to be tested
• Be able to apply an adaptive subtraction and quality control the resulting outputs


1 day

Number of Participants



Participants should have a geophysical background and be equipped with a basic proficiency in data processing and using the software

Software Used


Course Format

Classroom, presentations, exercise, demo

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