An Introduction to Paradise 3.2
Deborah Sacrey, Owner and Geophysicist of Auburn Energy, provides a review of the various attribute categories and their possible machine learning application to solve problems in seismic interpretation.
Machine Learning is a subset of Narrow AI that does pattern classification. It’s an engine – an algorithm that learns without explicit programming.
Dr. Tom Smith explains “What is Big Data” and it’s impact on the oil and gas industry in this short concept video.
A review of the various attribute categories and their possible application.
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.
Latest Technology for Seismic Interpretation: Direct detection & delineation of facies architecture in the Eagle Ford Group or How did the Eagle Ford GP get Made? A presentation by Patricia Santogrossi at the 2016 SEG Annual Convention.
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.