Thesis Abstract

Abstract
The optimization of enhanced oil recovery (EOR) techniques in offshore reservoirs presents a significant challenge in the petroleum industry due to the complex nature of reservoirs and the high cost involved in extraction processes. This research focuses on leveraging artificial intelligence (AI) technologies to optimize EOR techniques in offshore reservoirs, with the aim of increasing oil recovery efficiency and reducing operational costs. The study involves the development and implementation of AI algorithms to analyze reservoir data, predict reservoir behavior, and recommend optimal EOR strategies. Chapter one provides an introduction to the research topic, background information on EOR techniques, a statement of the problem, research objectives, limitations, scope, significance of the study, structure of the thesis, and key definitions. Chapter two is a comprehensive literature review that covers ten key areas related to EOR techniques, offshore reservoirs, artificial intelligence applications in the petroleum industry, and previous studies on similar topics. Chapter three details the research methodology, including data collection methods, AI algorithm selection, model development, simulation techniques, validation procedures, and performance evaluation metrics. The chapter also discusses the ethical considerations and limitations of the research methodology. Chapter four presents a thorough discussion of the research findings, including AI-driven optimization results, comparison with traditional EOR techniques, sensitivity analysis, and potential implementation challenges. Finally, chapter five offers a conclusive summary of the research outcomes, highlighting key findings, implications for the petroleum industry, recommendations for future research, and the overall contribution of the study to the field of petroleum engineering. The study concludes that the application of artificial intelligence in optimizing EOR techniques in offshore reservoirs shows promise for improving oil recovery rates, reducing costs, and enhancing operational efficiency in the petroleum industry.

Thesis Overview