Modeling extra-deep EM logs using a deep neural network

05/18/2020
by   Sergey Alyaev, et al.
0

Modern geosteering is heavily dependent on real-time interpretation of deep electromagnetic (EM) measurements. This work presents a deep neural network (DNN) model trained to reproduce the full set of extra-deep real-time EM logs consisting of 22 measurements per logging position. The model is trained in a 1D layered environment and has sensitivity for up to seven layers with different resistivity values. A commercial simulator provided by a tool vendor is utilized to generate a training dataset. The impossibility of parallel execution of the simulator effectively limits the permissible dataset size. Therefore, the geological rules and geosteering specifics supported by the forward model are embraced when designing the dataset. It is then used to produce a fully parallel EM simulator based on a DNN without access to the proprietary information about the EM tool configuration or the original simulator source code. Despite a relatively small training set size, the resulting DNN forward model is quite accurate for synthetic geosteering cases, yet independent of the logging instrument vendor. The observed average evaluation time of 0.15 milliseconds per logging position makes it also suitable for future use as part of evaluation-hungry statistical and/or Monte-Carlo inversion algorithms.

READ FULL TEXT

page 3

page 7

page 10

research
10/05/2018

A Deep Learning Approach to the Inversion of Borehole Resistivity Measurements

We use borehole resistivity measurements to map the electrical propertie...
research
10/27/2022

Strategic Geosteeering Workflow with Uncertainty Quantification and Deep Learning: A Case Study on the Goliat Field

The real-time interpretation of the logging-while-drilling data allows u...
research
07/20/2022

Automated machine learning for borehole resistivity measurements

Deep neural networks (DNNs) offer a real-time solution for the inversion...
research
01/12/2021

Design of borehole resistivity measurement acquisition systems using deep learning

Borehole resistivity measurements recorded with logging-while-drilling (...
research
03/22/2022

NNReArch: A Tensor Program Scheduling Framework Against Neural Network Architecture Reverse Engineering

Architecture reverse engineering has become an emerging attack against d...
research
10/31/2018

A Mixture of Expert Approach for Low-Cost Customization of Deep Neural Networks

The ability to customize a trained Deep Neural Network (DNN) locally usi...

Please sign up or login with your details

Forgot password? Click here to reset