HampsonRussell Emerge Workshop (HR-240)
- 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.
Geophysicists, geologists, engineers and technical staff who want to understand the theory and learn how to apply these increasingly critical techniques.
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.
Software used: Emerge
Course Format: Workshop
Number of Participants: