Discover applications of Paradise
The accurate interpretation of DHI characteristics has proven to significantly improve the success rates of drilling commercial wells. In this webinar, Rocky Roden looks at seismic multi-attribute analysis using Self-Organizing Maps (SOMs), a machine learning approach that distills information from numerous attributes to provide an accurate assessment of DHI characteristics.
This international webinar describes how multi-attribute seismic analysis is applied using the Paradise software to visualize thin beds and facies below classical seismic tuning thickness. The material is presented by Mr. Rocky Roden, an industry thought leader and Senior Consulting Geophysicist for Geophysical Insights.
Dr. Kurt Marfurt of the AASPI Consortium at The University of Oklahoma presents an example of how interpreters are using machine learning to enhance understanding of the seismic response.
A presentation by Patricia Santogrossi at the Houston Geological Society (HGS) North American dinner covering seismic facies in the Eagle Ford.
The origins of seismic attributes and the theory behind how they are calculated.
A review of the various attribute categories and their possible application.
Latest Technology for Seismic Interpretation: Direct detection & delineation of facies architecture in the Eagel Ford Group or How did the Eagle Ford GP get Made? A presentation by Patricia Santogrossi at the 2016 SEG Annual Convention.
Paradise is multi-attribute analysis software that uses machine learning processes to extract more information from the seismic response, even below seismic resolution. Using Paradise, interpreters are able to analyze multiple attributes simultaneously and calibrate results to wells quickly.
Machine learning techniques apply statistics-based algorithms that learn iteratively from the data and adapt independently to produce repeatable results. This video gives a quick introduction to machine learning.