HR-230 Emerge Workshop

Audience

Geophysicists, geologists, engineers and technical staff who want to understand the theory and learn how to apply these increasingly critical techniques.

Content

This course covers the theory and practical use of Emerge, an interactive program that is fully linked within HampsonRussell software and performs multi-attribute seismic analysis for seismic reservoir characterization using multivariate statistics and neural networks. Topics covered include:

  • Theory of seismic attributes, linear, non-linear and neural network methodologies for attribute selection, cross-validation and attribute ranking
  • Application of attributes to convert seismic data volumes into geological or petrophysical volumes
  • Application of attributes to predict missing log data
  • Attributes exercises using seismic data and well logs

Learning Objectives

  • A comprehensive overview of the generation of seismic attributes
  • Understanding how to recognize reliable attributes when estimating reservoir parameters
  • Application of neural network technology in well log prediction, petrophysical volume generation and seismic lithology classification

Duration

1-day

Prerequisites

None

Software Used

Emerge

Course Format

Workshop

Audience

Geophysicists, geologists, engineers and technical staff who want to understand the theory and learn how to apply these increasingly critical techniques.

Content

This course covers the theory and practical use of Emerge, an interactive program that is fully linked within HampsonRussell software and performs multi-attribute seismic analysis for seismic reservoir characterization using multivariate statistics and neural networks. Topics covered include:

Theory of seismic attributes, linear, non-linear and neural network methodologies for attribute selection, cross-validation and attribute ranking Application of attributes to convert seismic data volumes into geological or petrophysical volumes Application of attributes to predict missing log data Attributes exercises using seismic data and well logs

Learning Objectives

A comprehensive overview of the generation of seismic attributes
Understanding how to recognize reliable attributes when estimating reservoir parameters
Application of neural network technology in well log prediction, petrophysical volume generation and seismic lithology classification

Duration

1-day

Number of Participants

Prerequisites

None

Software Used

Emerge

Course Format

Workshop

Find Out More

CGG GeoTraining offers the most comprehensive industry training based on years of practical experience acquired by our personnel.

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.