Training courses, events and seminars: Deep Learning Inversion of Borehole Resistivity Measurements. Part I: Choice of Loss
GROUNDWATER HYDROLOGY GROUP SEMINAR (UPC-CSIC)
By: David Pardo (UPV/EHU, BCAM, and Ikerbasque Research Professor)
Day: Thursday 17 October
Time: 12:15 h
Place: Department of Civil and Environmental Engineering, Modulo D2-CIHS Classroom, Ground Floor
Abstract:
In geosteering operations, it is necessary to invert (interpret) borehole resistivity measurements in real-time. Recently, Deep Neural Networks (DNNs) have arisen as an alternative to perform such a complex task due to their unique ability to approximate different unknown functions.
In this presentation, we describe the application of interest and the need for real-time inversion. Then, we review basic concepts of DNNs when applied to inverse problems. Thereafter, we focus on the selection of proper loss functions for solving geosteering inverse problems. Some numerical results illustrate the performance and limitations of various loss functions.
Most derivations and ideas contained in the presentation are directly applicable to other inverse problems across different areas of engineering.