Optimizing Enhanced Oil Recovery Techniques in Greening Petroleum Fields: A Case Study of PetroChem Industries

Thesis Abstract

This study addresses the critical need for sustainable and efficient enhanced oil recovery (EOR) techniques within the petroleum industry, focusing on PetroChem Industries' operations in the Greening Petroleum Fields, where declining production rates have necessitated innovative interventions to optimize resource extraction while minimizing environmental impact. The primary aim is to evaluate current EOR methods employed by PetroChem Industries and identify optimal strategies that enhance oil recovery while aligning with green principles. Specific objectives include assessing the performance of various EOR techniques, analyzing their environmental implications, developing an integrated model for selecting optimal EOR approaches, and proposing actionable recommendations for industry adoption. The research adopts a mixed-methods approach, integrating both quantitative and qualitative data. The quantitative component utilizes a descriptive survey design targeting technical personnel, operations managers, and environmental officers within PetroChem Industries, with a total population of 150 relevant staff members. A sample size of 112 respondents is determined through stratified random sampling to ensure representativeness across departments. Data collection instruments comprise structured questionnaires validated through content validity checks and pilot testing, supplemented by plant operational data records obtained from company archives. Qualitative data are gathered through semi-structured interviews with senior engineers, environmental specialists, and industry experts, with thematic analysis employed to interpret insights. For data analysis, multiple regression analysis is utilized to evaluate the relationship between different EOR techniques and recovery efficiency, while ANOVA tests compare environmental impacts among methods. The research also employs a Decision Support System (DSS) model, integrating findings to formulate an optimized EOR selection framework aligned with environmental sustainability goals. The theoretical foundation of the study draws on the Resource-Based View (RBV) theory, emphasizing the strategic deployment of technological innovations and environmental management practices, andthe Diffusion of Innovations Theory, which explains the adoption dynamics of green EOR techniques within industrial settings. Expected findings indicate that combining chemical, thermal, and gas injection methods with environmentally friendly additives significantly improves recovery rates by an average of 15%, reduces chemical usage by 20%, and minimizes greenhouse gas emissions by 12%, compared to traditional EOR processes. The study anticipates confirming that integrated approaches, supported by robust decision models, are most effective in achieving both economic and ecological objectives. It is also expected to reveal organizational, technical, and regulatory barriers impeding environmentally sustainable EOR deployment, providing a comprehensive understanding of challenges and enablers. The contribution to knowledge lies in developing a context-specific, integrated decision framework for optimizing green EOR techniques that balance productivity and environmental sustainability, thus filling a significant gap in operational research within the petroleum sector. The findings aim to inform industry best practices, enhance strategic planning, and support policy formulation aimed at sustainable resource management. The main conclusions underscore that adopting an integrated, data-driven approach to EOR selection can substantially improve petroleum recovery efficiency in a manner consistent with environmental preservation. Recommendations include implementing the proposed decision framework across similar fields, increasing investment in green EOR technologies, and fostering organizational capacity for sustainability transitions. Lastly, the study advocates for further research into the long-term environmental and economic impacts of emerging green EOR methodologies and their scalability within diverse geological and operational contexts.