Machine Learning Guide for Oil and Gas Using Python

Chapter 9: Evolutionary optimization

Abstract

This chapter mainly covers two well-known evolutionary algorithms: genetic and particle swarm. Initially, genetic algorithm's brief history and its applications in the oil and gas industry are illustrated. Next, genetic algorithm workflow is explained including population, fitness function evaluation, parent selection, crossover, and mutation. All the mentioned definitions are explained for a maximization example using Python. Then “genetic algorithm” library in Python is used to maximize well estimated ultimate recovery by optimizing some well design parameters. In the second part of this chapter, particle swarm algorithm is introduced with a brief background, its applications in the oil and gas industry, ...