Utilization of Artificial Intelligence for Enhanced Oil Recovery in Mature Oilfields

Thesis Abstract

Abstract
The utilization of Artificial Intelligence (AI) in the petroleum industry has gained significant attention in recent years, particularly in the context of enhancing oil recovery in mature oilfields. This thesis explores the application of AI techniques to optimize production and recovery processes in mature oilfields, with a focus on improving reservoir characterization, well performance, and overall field productivity. The research investigates how AI technologies such as machine learning, data analytics, and predictive modeling can be leveraged to extract valuable insights from complex reservoir data and make informed decisions that lead to increased oil recovery rates. Chapter One provides an introduction to the research topic, outlining the background of the study and presenting the problem statement, objectives, limitations, scope, significance, structure of the thesis, and definitions of key terms. The chapter sets the foundation for understanding the importance of utilizing AI in enhancing oil recovery in mature oilfields. Chapter Two consists of a comprehensive literature review that examines existing studies, methodologies, and technologies related to AI applications in the petroleum industry, specifically focusing on enhanced oil recovery techniques in mature oilfields. The review covers ten key areas, including reservoir characterization, well performance optimization, production forecasting, and intelligent decision-making systems. Chapter Three outlines the research methodology employed in this study, detailing the research design, data collection methods, AI algorithms used, model development, validation processes, and performance evaluation metrics. The chapter presents eight key components that guide the implementation of AI techniques for enhanced oil recovery in mature oilfields. Chapter Four presents a detailed discussion of the findings obtained from the application of AI technologies in optimizing oil recovery processes in mature oilfields. The chapter analyzes the impact of AI on reservoir management, well performance, production optimization, and overall field productivity, highlighting the benefits and challenges associated with implementing AI solutions in the petroleum industry. Chapter Five offers a comprehensive conclusion and summary of the thesis, summarizing the key findings, implications, and contributions of the research. The chapter also discusses future research directions and recommendations for further exploration of AI applications in enhancing oil recovery in mature oilfields. In conclusion, this thesis emphasizes the significant potential of AI technologies in revolutionizing the petroleum industry by enhancing oil recovery in mature oilfields. The research findings underscore the importance of leveraging AI for improving reservoir management practices, optimizing well performance, and maximizing oil production rates. By integrating AI solutions into existing oilfield operations, operators can achieve higher recovery efficiencies, reduce operational costs, and make more informed decisions to sustainably extract valuable hydrocarbon resources from mature oilfields.