Prior Applications of Neural Networks in Geophysics

As mentioned previously in the primary sections of chapter one, there are several, and varied applications of neural networks in geophysics; here we give a short list of some of these applications: Modeling of crustal velocity using Artificial Neural Networks (case study: Iran Geodynamic GPS Network (Ghaffari and Mohammadzadeh 2015) Crustal velocity field modeling with neural network and polynomials, SIDERIS, M.G. (Ed.), Moghtased-Azar and Zaletnyik (2009) Artificial neural network pruning approach for modular neural networks (Yilmaz 2013) Modular neural networks for seismic tomography (Barraez et al. 2002) Estimating one-dimensional models from frequency domain measurements Quantifying sand fraction from seismic attributes using modular artificial neural networks Borehole electrical resistivity modeling using neural networks Determination of facies from well logs using modular neural networks (Bhatt and Helle 2002) Inversion of self-potential anomalies caused by 2D-inclined sheets (Hesham 2009). 2D inverse modeling of residual gravity anomalies from Simple geometric shapes using Modular Feed-forward Neural Network (Eshaghzadeh and Hajian 2018)