Document Type : Review Paper

Authors

• Noor Faek Hameed ¹
• Rwaida Kaiser Abdul- Majed ²

¹ Petroleum Department, College of Engineering, University of Baghdad, Baghdad, Iraq

² petroleum department, university of Baghdad

Abstract

One of the most crucial phases in creating an accurate and ideal field development plan for oil and gas projects is evaluating the formation and characterizing the reservoir. Many different types of data are required for reservoir characterization and modeling, including wireline logs, LWD logs, SCAL data, geology and seismic data. Furthermore, sufficient understanding of the underlying physical interactions between each parameter. Recent developments in artificial intelligence and neural network-based petroleum exploration technology have opened up new possibilities for the sector in terms of reservoir characterization, that is more affordable, effective, and precise. Several research works pertaining to the application of artificial neural networks (ANNs) in the petroleum sector were examined, synthesized, and categorized into four main categories: applications in exploration, drilling, production, and reservoir engineering. An overview of applications of artificial neural networks in petroleum engineering was presented. An established process for using ANNs in any petroleum application was performed and displayed through a flowchart that may be used as a useful guide to implement ANNs for any petroleum application.

Keywords

• Artificial Neural Networks
• Petroleum Industry
• Exploration