Browsing Computational Mathematics (CM) by Subject "deep learning"
Now showing items 1-5 of 5
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A Deep Learning Approach to the Inversion of Borehole Resistivity Measurements
(2020-04)Borehole resistivity measurements are routinely employed to measure the electrical properties of rocks penetrated by a well and to quantify the hydrocarbon pore volume of a reservoir. Depending on the degree of geometrical ... -
A Deep Neural Network as Surrogate Model for Forward Simulation of Borehole Resistivity Measurements
(2020-01)Inverse problems appear in multiple industrial applications. Solving such inverse problems require the repeated solution of the forward problem. This is the most time-consuming stage when employing inversion techniques, ... -
Design of Loss Functions for Solving Inverse Problems using Deep Learning
(2020-05)Solving inverse problems is a crucial task in several applications that strongly a ffect our daily lives, including multiple engineering fields, military operations, and/or energy production. There exist different methods ... -
Error Control and Loss Functions for the Deep Learning Inversion of Borehole Resistivity Measurements
(2020-11)Deep learning (DL) is a numerical method that approximates functions. Recently, its use has become attractive for the simulation and inversion of multiple problems in computational mechanics, including the inversion of ... -
Error Control and Loss Functions for the Deep Learning Inversion of Borehole Resistivity Measurements
(2020-05)Deep learning (DL) is a numerical method that approximates functions. Recently, its use has become attractive for the simulation and inversion of multiple problems in computational mechanics, including the inversion of ...