Meta-attributes and Artificial Networking: A New Tool for Seismic Interpretation - Couverture rigide

Sain, Kalachand; Kumar, Priyadarshi Chinmoy

Couverture rigide

ISBN 10 : 1119482003 ISBN 13 : 9781119482000

Editeur : American Geophysical Union, 2022

Synopsis

Applying machine learning to the interpretation of seismic data

Seismic data gathered on the surface can be used to generate numerous seismic attributes that enable better understanding of subsurface geological structures and stratigraphic features. With an ever-increasing volume of seismic data available, machine learning augments faster data processing and interpretation of complex subsurface geology.

Meta-Attributes and Artificial Networking: A New Tool for Seismic Interpretation explores how artificial neural networks can be used for the automatic interpretation of 2D and 3D seismic data.

Volume highlights include:

• Historic evolution of seismic attributes
• Overview of meta-attributes and how to design them
• Workflows for the computation of meta-attributes from seismic data
• Case studies demonstrating the application of meta-attributes
• Sets of exercises with solutions provided
• Sample data sets available for hands-on exercises

The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.

A propos du livre

À propos de l'auteur

Kalachand Sain, Wadia Institute of Himalayan Geology, India

Priyadarshi Chinmoy Kumar, Wadia Institute of Himalayan Geology, India

Détails de l'édition

• Éditeur: American Geophysical Union
• Date d'édition: 2022
• Langue: anglais
• ISBN 10: 1119482003
• ISBN 13: 9781119482000
• Reliure: Relié
• Nombre de pages: 288
• Coordonnées du fabricant: Easy Access System Europe Oü, 16879218; gpsr.requests@easproject.com; ; Mustamäe tee 50, 10621, Tallinn, Estonia; Tallinn; 10621; Estonie