Machine Learning Guide for Oil and Gas Using Python

Chapter 6: Neural networks and Deep Learning

Abstract

This chapter initially covers the definition and main elements of artificial neural networks and how they were originally developed from the behavior of biological neurons. Then the theory behind how neural network finds the pattern between input and target variables is explained. In this section, nodes, weights, layers, activation functions, feedforward, backpropagation, and steps required to train a neural network are reviewed. After understanding the basics, a summary of neural network applications in oil and gas industry is illustrated. Two Python applications of data preprocessing, feature ranking and training neural networks for oil and gas–related problems, are presented. In the first ...