Paradise uses robust, non-linear machine learning technology to classify patterns in multiple attributes simultaneously, thereby extracting more information from the seismic response, even below classic seismic tuning. Use Paradise to:
Test drive Paradise
What is Machine Learning?
Coined in 1959 by Arthur Samuel, “Machine learning (ML) is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to “learn” (e.g., progressively improve performance on a specific task) from data, without being explicitly programmed.”
Are you new to Paradise?
Machine Learning is changing the way interpretation is done. Find out how these geoscientists are using machine learning to reveal unprecedented levels of detail in seismic data.
New Tools for Interpretation
Select an icon below to learn more about powerful, straightforward workflows in Paradise
Identify attributes that have the greatest contribution to the region according to their relative variance
Probe, analyze, and understand classification results in the Universal Viewer to refine an interpretation
Run different SOM configurations to extract greater information from multiple attributes simultaneously
Display 2D and 3D views of data while using the 2D Colormap to gain understanding of classification results
“…machine learning software in Paradise is applied to seismic attributes to find patterns and important geology… [and] Self-Organizing Maps are used to analyze data at single sample resolution.”
— American Oil & Gas Reporter
Paradise enables every interpreter to use powerful machine learning processes through straight forward, left-to-right guided workflows. Learn more about how to set up and generate a PCA chart of attributes and SOM classification results, then use the unique 2D Colormap with the 3D Viewer to interpret geobodies.
“Paradise distills a variety of information from many attributes simultaneously at single sample resolution… This is one of the many differences in the application of machine learning and pattern recognition methods available in Paradise.”
— GEO ExPro
Read case studies on the application of machine learning processes, including Self-Organizing Maps (SOM’s) and Principal Component Analysis (PCA), as applied to seismic attributes in various geologic settings, including onshore – conventional and unconventional – and offshore.