The Impact of Artificial Intelligence and Machine Learning on Reservoir Characterization: A Review of Recent Advances

Abstract

Effective reservoir characterization has been one of the major challenges encountered in the oil and gas industry. Several tools and models have been created to analyze a reservoir accurately to tackle this challenge. This paper reviewed using artificial intelligence and machine learning for reservoir characterization, which has proven an efficient method. With a good understanding of porosity and permeability, reservoir engineers can carefully create a sustainable reservoir development plan, create an effective production system for naturally unproductive reservoirs, determine the drilling optimization, estimate hydraulic flow units, choose the pressure-volume-temperature of reservoirs and reservoir rock properties such as porosity and permeability using well-log data. Support Vector Machines and Artificial Neural Networks from the studies have shown to be vital for a comprehensive reservoir analysis in the future, but there is a need to improve the algorithms for better optimization of new datasets.