Project Abstract

Abstract
The utilization of Artificial Intelligence (AI) in reservoir characterization and simulation for enhanced oil recovery in unconventional reservoirs has emerged as a cutting-edge approach in the field of petroleum engineering. This research project delves into the innovative application of AI techniques to address the complexities associated with reservoir characterization and simulation, particularly in unconventional reservoirs where traditional methods may fall short. The primary objective of this study is to explore how AI can be leveraged to optimize reservoir performance and enhance oil recovery rates in challenging unconventional reservoir environments. The introductory section provides a comprehensive overview of the research topic, highlighting the importance of AI in the petroleum industry and the specific relevance of reservoir characterization and simulation in enhancing oil recovery from unconventional reservoirs. The background of the study delves into the existing literature and research initiatives in the field, laying the foundation for the current research endeavor. The problem statement identifies the gaps and challenges in current reservoir characterization and simulation practices, underscoring the need for advanced AI solutions. The study aims to address these challenges by establishing clear objectives focused on optimizing reservoir performance and increasing oil recovery efficiency. While the study acknowledges certain limitations in the application of AI in reservoir engineering, such as data quality and computational complexities, the scope of the research outlines the specific parameters and boundaries within which the study will operate. The significance of the research is highlighted in terms of its potential impact on the petroleum industry, paving the way for more efficient and sustainable oil recovery practices. The structure of the research delineates the organization of the study, guiding the reader through the subsequent chapters. The literature review section critically examines existing research on AI applications in reservoir characterization and simulation, emphasizing key findings and advancements in the field. Drawing on a diverse range of sources, the literature review provides a comprehensive understanding of the state-of-the-art AI technologies and methodologies relevant to enhanced oil recovery in unconventional reservoirs. The research methodology section outlines the specific approach and tools employed in the study, including data collection methods, AI algorithms, and simulation techniques. Through a detailed analysis of the research findings, the discussion in Chapter Four elucidates the implications of applying AI in reservoir characterization and simulation for enhanced oil recovery. The results of the study are interpreted in the context of reservoir performance optimization and oil recovery efficiency, shedding light on the potential benefits and challenges of integrating AI technologies in petroleum engineering practices. The conclusion and summary chapter encapsulate the key findings of the research, highlighting the significance of AI in revolutionizing reservoir engineering practices and paving the way for more sustainable oil recovery strategies in unconventional reservoirs. In conclusion, this research project contributes to the growing body of knowledge on the application of AI in reservoir engineering, particularly in the context of enhanced oil recovery from unconventional reservoirs. By leveraging advanced AI technologies, the study aims to drive innovation and efficiency in reservoir characterization and simulation, ultimately enhancing oil recovery rates and optimizing reservoir performance in challenging geological environments.

Project Overview