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

Libro 15 di 16: Special Publications

Sain, Kalachand; Kumar, Priyadarshi Chinmoy

 
9781119482000: Meta-attributes and Artificial Networking: A New Tool for Seismic Interpretation
Rilegato
ISBN 10: 1119482003 ISBN 13: 9781119482000
Casa editrice: Amer Geophysical Union, 2022

Sinossi

Meta-Attributes and Artificial Networking

Meta-Attributes and Artificial Networking
A New Tool for Seismic Interpretation

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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sull'autore

Kalachand Sain, Wadia Institute of Himalayan Geology, India

Priyadarshi Chinmoy Kumar, Wadia Institute of Himalayan Geology, India

Dalla quarta di copertina

Meta-Attributes and Artificial Networking
A New Tool for Seismic Interpretation

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Amer Geophysical Union
Data di pubblicazione
2022
Lingua
Inglese
ISBN 10 
1119482003
ISBN 13 
9781119482000
Rilegatura
Copertina rigida
Numero edizione
1
Numero di pagine
400
Contatto del produttore
non disponibile
Persona responsabile
non disponibile