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3D geomechanical modeling in complex environments using the neural network
Congresso Brasileiro de Mecânica dos Solos e Engenharia Geotécnica
Modern computational tools and Machine Learning algorithms allowed automatic identification of petrophysical and lithological properties using geophysical profiles and seismic data as training set. Once knowing the input data limitation and established the parameters, it is possible to create in an agile and efficient way 1D and 3D models to determine petrophysical, mechanical and geological properties. Our goal is to apply neural networks to develop a 3D goemechanical model of a complexdoi:10.4322/cobramseg.2022.0136 fatcat:zuhppk5elzeoblxn5n3kq56chm