Utilization of Artificial Intelligence in Reservoir Characterization for Enhanced Oil Recovery

Thesis Abstract

Abstract
The oil and gas industry has witnessed a significant transformation in recent years with the integration of advanced technologies to optimize operations and increase efficiency. One such technology that has gained prominence is Artificial Intelligence (AI), which offers innovative solutions to enhance reservoir characterization for improved oil recovery. This thesis explores the utilization of AI in reservoir characterization to optimize oil recovery processes, focusing on its application in enhancing productivity in the oil and gas sector. The introduction section provides an overview of the research, highlighting the background, problem statement, objectives, limitations, scope, significance, and structure of the thesis. The background of the study discusses the importance of reservoir characterization in oil recovery and the potential benefits of integrating AI technologies in this process. The problem statement identifies the gaps in existing reservoir characterization methods and the need for more advanced solutions to improve oil recovery efficiency. The literature review chapter critically evaluates existing research on AI applications in reservoir characterization and oil recovery. It explores ten key areas including AI algorithms, machine learning techniques, data analytics, and modeling approaches used in reservoir characterization. The review also discusses case studies and industry applications to provide a comprehensive understanding of the current state of AI in oil and gas operations. In the research methodology chapter, the study outlines the methods and techniques employed to investigate the utilization of AI in reservoir characterization. The chapter covers data collection, analysis, modeling, and simulation processes, as well as the tools and software used to implement AI algorithms for reservoir characterization. The methodology section also discusses the research framework and criteria for evaluating the effectiveness of AI in enhancing oil recovery processes. The discussion of findings chapter presents a detailed analysis of the results obtained from applying AI technologies in reservoir characterization. It highlights the key findings, trends, and insights gathered from the study, focusing on the impact of AI on reservoir modeling, data interpretation, and decision-making processes in oil recovery operations. The chapter also discusses the challenges, limitations, and implications of utilizing AI in reservoir characterization for enhanced oil recovery. Finally, the conclusion and summary chapter provide a comprehensive overview of the research findings and their implications for the oil and gas industry. The study concludes with recommendations for further research and practical applications of AI in reservoir characterization to optimize oil recovery processes. The summary highlights the key contributions of the research and its potential to drive innovation and efficiency in oil and gas operations through the utilization of AI technologies. Overall, this thesis contributes to the growing body of knowledge on the application of Artificial Intelligence in reservoir characterization for enhanced oil recovery. By leveraging AI algorithms, machine learning techniques, and data analytics, the study demonstrates the potential of advanced technologies to revolutionize oil and gas operations and drive sustainable growth in the industry.