VDM Verlag Artificial Neural Network inversion in Geoelectrics: Modeling and inversion of geophysical resistivity data using artificial neural network

Modern data processing techniques based on the concepts of Artificial Neural Networks (ANN), which works on the analogy of human brain, has emerged as one of the most powerful alternative perspectives for complex geo-data analysis. ANN based techniques are robust and have many advantages to handle large amount of data sets. The main goal of the present book is to develop, apply and compare various ANN based algorithms to construct subsurface resistivity structure using the Schlumberger resistivity sounding data. This book presents important results of ANN modeling of geoelectrical sounding data from some of the crucial tectonic and geologically important regions such as Barmer District of Rajasthan and Puga Valley of Jammu & Kashmir. These modelling results are important for ground water exploration and geothermal resources. About the Author U. K. Singh is Assistant Professor in the Department of Applied Geophysics, Indian School of Mines, Dhanbad, India where he teaches on a course of geophysical inverse problems. He received his M. Sc. (Tech) degree from Banaras Hindu University, India and doctorate degree from Osmania University of Hyderabad, India.