Resource Library

Paradise 3.2 Brochure Seismic Interpretation-min

Paradise 3.2

Geophysical Insights
/
Paradise 3.2 announcement ...
Read More
Image with text for solving interpretation problems using machine learning on multi-attribute, sample-based seismic data

Solving Interpretation Problems using Machine Learning on Multi-Attribute, Sample-Based Seismic Data

Geophysical Insights
/
Deborah Sacrey, Owner and Geophysicist of Auburn Energy, provides a review of the various attribute categories and their possible machine ...
Read More
Solving Exploration Problems with Machine Learning Figure 7

Solving Exploration Problems with Machine Learning

First Break
/ and
Geoscientists Deborah Sacrey and Rocky Roden solve exploration problems using Paradise, machine learning software for seismic interpretation in the June ...
Read More
Honeycomb Default

Machine Learning Terms

Geophysical Insights
/
A glossary defining essential machine learning terms within the seismic interpretation and geoscience community from Principal Component Analysis (PCA) to ...
Read More
conventional-well_opt

Thin Beds and Anomaly Resolution in the Niobrara

Geophysical Insights
/
Using machine learning to classify a 100-square-mile seismic volume in the Niobrara, geoscientists were able to interpret thin beds below ...
Read More
what-is-machine-learning Small

What is Machine Learning?

Geophysical Insights
/
Machine Learning is a subset of Narrow AI that does pattern classification. It’s an engine – an algorithm that learns ...
Read More
Oil & Gas Big Data

What is Big Data?

Geophysical Insights
/
Dr. Tom Smith explains "What is Big Data" and it's impact on the oil and gas industry in this short ...
Read More
Seismic Attribute Essentials classifying seisimic attributes using machine learning SOM classification

Attribute Essentials: Categories of Attributes

Geophysical Insights
/
A review of the various attribute categories and their possible application ...
Read More
wiggle trace seismic data

Significant Advancements in Seismic Reservoir Characterization with Machine Learning

SPE Norway
/ and
Geophysicists, Rocky Roden & Patricia Santogrossi, discuss machine learning applications enabling refined assessment of thin beds and DHI characteristics ...
Read More
  • Registration confirmation will be emailed to you.

  • We're committed to your privacy. Geophysical Insights uses the information you provide to us to contact you about our relevant content, events, and products. You may unsubscribe from these communications at any time. For more information, check out our Privacy Policy

    Scroll to Top