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A Deep Learning Approach to the Inversion of Borehole Resistivity Measurements
Once the DNN is built, we can perform the actual inversion of the field measurements in real time.
Error Control and Loss Functions for the Deep Learning Inversion of Borehole Resistivity Measurements
Recently, its use has become attractive for the simulation and inversion of multiple problems in computational mechanics, including the inversion of borehole logging measurements for oil and gas applications.
Design of borehole resistivity measurement acquisition systems using deep learning
In addition, to guarantee an inverse solution, we need a carefully selected measurement acquisition system with a sufficient number of measurements.
Automated machine learning for borehole resistivity measurements
In this work, we propose a scoring function that accounts for the accuracy and size of the DNNs compared to a reference DNN that provides a good approximation for the operators.
