Paper Information

Title: 

INVERSE MODELING OF RESISTIVITY SOUNDING DATA USING ARTIFICIAL NEURAL NETWORKS

Type: PAPER
Author(s): KARIMI A.,MORADZADEH A.,KAMKARROOHANI A.,ALLAMEHZADEH M.
 
 
 
Name of Seminar: CONFRANCE ZHEOFIZIKE IRAN
Type of Seminar:  CONFERENCE
Sponsor:  ANJOMANE MELI ZHEOFIZIK IRAN
Date:  2006Volume 12
 
 
Abstract: 

INVERSE MODELING OF GEOELECTRICAL DATA IS AN IMPORTANT METHOD EXPLORATION AND UNDERGROUND WATER STUDIES. INTRINSIC NONLINEAR NATURE OF GEOPHYSICAL DATA IS OBSTACLE IN MODELING PROCEDURE. HERE WE DESCRIBE A STUDY OF THE APPLICABILITY OF NEURAL NETWORKS TO SOLVING SOME GEOPHYSICAL INVERSE PROBLEMS. IN PARTICULAR, WE STUDY THE PROBLEM OF OBTAINING FORMATION RESISTIVITIES AND LAYER THICKNESSES FROM VERTICAL ELECTRICAL SOUNDING (VES) DATA.

 
Keyword(s): 
 
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