3D Surface Related Multiple Elimination

Audience

Geophysicists with 2-3 years marine processing experience already familiar with multiple attenuation basics and binning/regularization processing.

Content

This course is composed of one of the main methodologies used in 3D Surface Related Multiple Elimination (SRME): Convolutional modeling.

This course discusses principles and fundamentals of the convolutional modeling module. It also addresses generalities, multiple attenuation toolbox, and understanding multiples.

Some overviews of 3D SRME techniques, an overview of Delft SRME principle are examined.

Theory and principles of the 3D SRME is the core module, supported by the 3D SRME by convolutional modeling user guide.

Further study into; pre-processing of input data, binning and mapping files, 3D regularization, convolutional modeling and model subtraction concludes the course.

Learning Objectives

  • Understand 3D SRME principles methodology of convolutional modeling
  • Confidently replicate the practical exercises from the course
  • Comprehend the theoretical aspects of 3D SRME

Duration

1-day

Number of Participants

6 - 8

Prerequisites

Previous lectures about this topic are recommended. Please consult SEG Technical Journals on the CGG University web-page (e-Geophysical library)

Software Used

geovation

Course Format

Classroom, presentations, exercise, demo

Audience

Geophysicists with 2-3 years marine processing experience already familiar with multipleattenuation basics and binning/regularization processing.

Content

This course is composed of one of the main methodologies used in 3D Surface RelatedMultiple Elimination (SRME): Convolutional modeling.

This course discusses principles and fundamentals of the convolutional modeling module. Italso addresses generalities, multiple attenuation toolbox, and understanding multiples.

Some overviews of 3D SRME techniques, an overview of Delft SRME principle are examined.

Theory and principles of the 3D SRME is the core module, supported by the 3D SRME byconvolutional modeling user guide.

Further study into; pre-processing of input data, binning and mapping files, 3D regularization,convolutional modeling and model subtraction concludes the course.

Learning Objectives

Understand 3D SRME principles methodology of convolutional modeling
Confidently replicate the practical exercises from the course
Comprehend the theoretical aspects of 3D SRME

Duration

1-day

Number of Participants

6 - 8

Prerequisites

Previous lectures about this topicare recommended. Please consultSEG Technical Journals on the CGGUniversity web-page (e-Geophysicallibrary)

Software Used

geovation

Course Format

Classroom, presentations, exercise, demo

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Our proprietary courses are fully customizable and can be offered at a time and location convenient to you. Please request a course for more information.