Meta-attributes And Artificial Networking Av Kalachand (csir-national Geophysical Research Group Hyderabad India) Sain, Priyadarshi Chinmoy (csir-nati

<p><b>Applying machine learning to the interpretation of seismic data</b></p><p>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.</p><p><i>Meta-Attributes and Artificial Networking: A New Tool for Seismic Interpretation</i> explores how artificial neural networks can be used for the automatic interpretation of 2D and 3D seismic data.</p><p><b>Volume highlights include:</b></p><ul><li>Historic evolution of seismic attributes</li><li>Overview of meta-attributes and how to design them</li><li>Workflows for the computation of meta-attributes from seismic data</li><li>Case studies demonstrating the application of meta-attributes</li><li>Sets of exercises with solutions provided</li><li>Sample data sets

Pris: kr 1629.00 fra Norli