Application of Artificial Intelligence in Reservoir Characterization for Improved Oil Recovery

Thesis Abstract

Abstract
The application of artificial intelligence (AI) in reservoir characterization for improved oil recovery has garnered significant interest in the petroleum engineering field. This thesis explores the utilization of AI techniques to enhance reservoir characterization processes and ultimately optimize oil recovery operations. The study begins by providing a comprehensive introduction to the research topic, highlighting the background of study, problem statement, objectives, limitations, scope, significance, and structure of the thesis. Chapter two presents a detailed literature review that examines existing studies on AI applications in reservoir characterization and oil recovery. The review covers various AI techniques such as machine learning, neural networks, and data analytics, emphasizing their effectiveness in enhancing reservoir modeling, fluid flow simulations, and production optimization. Chapter three outlines the research methodology employed in this study, including data collection methods, AI algorithm selection, model development, and evaluation criteria. The methodology section also discusses the integration of AI technologies with traditional reservoir engineering techniques to achieve more accurate and efficient results. In chapter four, the findings of the research are extensively discussed, showcasing the outcomes of applying AI in reservoir characterization for improved oil recovery. The discussion covers the impact of AI on reservoir property estimation, fluid behavior prediction, and well placement optimization, highlighting the benefits of incorporating AI in oil field development projects. Finally, chapter five presents the conclusion and summary of the thesis, emphasizing the key findings, contributions, and implications of the research. The study concludes by highlighting the potential of AI technologies to revolutionize reservoir characterization practices and drive significant improvements in oil recovery efficiency and profitability. In conclusion, this thesis provides valuable insights into the application of artificial intelligence in reservoir characterization for improved oil recovery. The findings underscore the transformative potential of AI technologies in optimizing oil field operations and maximizing hydrocarbon production. This research contributes to the ongoing efforts to leverage cutting-edge technologies for sustainable and efficient oil exploration and production practices.