Geophysical Insights is featuring two new off-the-shelf, deep learning applications in the Paradise® AI workbench
Seismic Facies Classification and Fault Detection
STOP BY BOOTH #1038 FOR A DEMONSTRATION
SEG 2019, 15-20 September
Booth #1038
Solving interpretation problems with deep learning and machine learning technologies
Visit booth #1038 to hear industry thought leaders present applications of machine learning and deep learning technologies to seismic interpretation in different geologic settings. Learn how technologies like GPU processing will change and enable geoscience workflows. Here are a few of the topics:
- Seismic facies classification using deep learning
- Net reservoir discrimination through multi-attribute analysis
- Thin bed detection with unsupervised machine learning
- Case studies of machine learning in geologic settings
- GPU processing for attribute generation
Geophysical Insights will be hosting daily lunch & learns at booth 1038 with featured talks by Fabian Rada, Dr. Tom Smith, and Dustin Dewett. Register for the lunch & Learns with the form on this page.
Gain Access to 2019 SEG Booth Presentations or Register for a Lunch & Learn
Speakers & Presentations
Dustin Dewett
Product Manager, Geophysical Insights
Seismic Facies Classification and Fault Detection using Deep Learning
Mike Dunn
SVP of Business Development, Geophysical Insights
Generating Attributes on GPUs
Reynaldo Gomez
Energy Account Manager, NVIDIA
Generating Attributes on GPUs
Dr. Bob Hardage
Geoscience Adviser, Geophysical Insights
Machine Learning Geobodies in the Wolfberry Play of the Permian Basin
Exposing Karst Topography in the Deep Ellenberger of the Permian Basin through Machine Learning
Dr. Carrie Laudon
Senior Geoscientist, Geophysical Insights
Machine Learning Improves Stratigraphic Resolution in the Niobrara
Dr. Ivan Marroquin
Senior Research Geophysicist, Geophysical Insights
Studies in Automated Optimization for Multi-Attribute Classification
Fabian Rada
Senior Adviser to PEMEX, Petroleum Oil & Gas Services
Net Reservoir Discrimination through Multi-Attribute Analysis at Single Sample Scale
Rocky Roden
Senior Geophysicist, Geophysical Insights
Comparing Machine Learning Methods and the Black Box Perception
Machine Learning on the Geoscience Technology Adoption Cycle
Deborah Sacrey
Senior Geoscientist, Geophysical Insights
A Journey through Paradise – Case Histories in Different Depositional Environments
Dr. Tom Smith
Thin Bed Detection with Unsupervised Machine Learning
Mathematical Foundation for Machine Learning of Multi-Attribute Seismic Surveys
For a printable version of the schedule, click here
Presentation Schedule
Time | Monday, 16 Sep | Tuesday, 17 Sep | Wednesday, 18 Sep |
---|---|---|---|
9:30-10:00 | Exhibition opens at 10 AM | Deborah Sacrey: A Journey through Paradise – Case Histories in Different Depositional Environments | Deborah Sacrey: A Journey through Paradise – Case Histories in Different Depositional Environments |
10:30-11:00 | Bob Hardage: Machine Learning Geobodies in the Wolfberry Play of the Permian Basin | Rocky Roden: Comparing Machine Learning Methods and the Black Box Connotation | Carrie Laudon: Machine Learning Improves Stratigraphic Resolution in the Niobrara |
12:00-1:00 | Fabian Rada: Net Reservoir Discrimination through Multi-Attribute Analysis at Single Sample Scale | Tom Smith: Thin Bed Detection with Unsupervised Machine Learning | Dustin Dewett: Seismic Facies Classification and Fault Detection using Deep Learning |
1:30-2:30 | Mike Dunn and Reynaldo Gomez: Generating Attributes on GPUs | Carrie Laudon: Machine Learning Improves Stratigraphic Resolution in the Niobrara | Rocky Roden: Machine Learning on the Geoscience Technology Adoption Cycle |
3:00-4:00 | Tom Smith: Mathematical Foundation for Machine Learning of Multi-Attribute Seismic Surveys | Dustin Dewett: Seismic Facies Classification and Fault Detection using Deep Learning | Bob Hardage: Exposing Karst Topography in the Deep Ellenberger of the Permian Basin through Machine Learning |
4:30-5:30 | Dustin Dewett: Seismic Facies Classification and Fault Detection using Deep Learning | Ivan Marroquin: Studies in Automated Optimization for Multi-Attribute Classification | Exhibition closes at 4:30 PM |