Evaluation of Enhanced Oil Recovery Techniques in Mature Reservoirs through Field Data Analysis

Thesis Abstract

The declining production rates of mature oil reservoirs necessitate the evaluation and optimization of enhanced oil recovery (EOR) techniques to prolong field lifespan and maximize hydrocarbon extraction. This study aims to empirically assess the effectiveness of various EOR methods—namely chemical flooding, gas injection, and thermal techniques—by analyzing field data from mature reservoirs within a South Atlantic basin. The specific objectives include quantifying the incremental recovery factor attributable to each EOR method, identifying operational and geological factors influencing EOR performance, and developing a predictive model for EOR success tailored to reservoir characteristics. A quantitative research design was adopted, utilizing a retrospective field study approach. The population comprised 25 mature oil fields with documented EOR interventions over the past decade, from which a stratified random sampling technique selected 10 representative fields encompassing diverse geological settings and operational histories. Data collection involved archival analysis of production logs, EOR implementation reports, core sample analyses, and reservoir simulation outputs, supplemented with interviews with reservoir engineers and field operators to contextualize data and gain insights into operational practices. Standardized data collection instruments included structured data extraction templates and semi-structured interview guides, with validity ensured through expert review and pilot testing. Reliability was maintained via inter-rater consistency checks during data coding. The analysis employed descriptive statistics to characterize reservoir properties and field performance pre- and post-EOR implementation. Inferential statistical techniques such as multiple regression analysis and analysis of variance (ANOVA) were applied to determine the significance of variables affecting EOR efficacy, while principal component analysis facilitated the identification of key factors contributing to successful recovery. Reservoir performance was further evaluated through responsiveness models derived from nonlinear regression frameworks, calibrated with field production data. Theoretically, the study was anchored in the Reservoir Engineering Theory and the General Systems Theory to interpret complex interactions among geological, operational, and technological variables influencing EOR outcomes. Expected findings include a quantifiable increase in recovery factors—averaging 8–15% incremental oil recovery attributable to EOR techniques—with chemical flooding emerging as the most effective method in reservoirs characterized by high permeability and light crude oils. The study anticipates identifying critical variables such as reservoir heterogeneity, injection rates, and fluid properties as significant predictors of EOR success, alongside operational factors like injection pressure and chemical concentration. The development of a predictive model will enable reservoir engineers to forecast EOR performance based on reservoir attributes, thereby optimizing planning and resource allocation. This research contributes novel empirical evidence to the body of knowledge on EOR performance in mature reservoirs, particularly through the integration of field data with robust statistical models. It advances understanding of context-specific EOR effectiveness, emphasizing the importance of reservoir heterogeneity and operational parameters. The study's findings will inform field-specific EOR planning strategies and guide policy development by emphasizing data-driven decision-making. In conclusion, the study underscores the critical role of comprehensive field data analysis in refining EOR techniques and optimizing recovery in mature reservoirs. It recommends enhanced data acquisition protocols, continuous monitoring, and tailored EOR strategies aligned with reservoir characteristics. Future research should explore the long-term sustainability of EOR methods, incorporate economic analyses to inform investment decisions, and expand the scope to include emerging technologies such as nanotechnology-enabled EOR. This work ultimately aims to contribute to more efficient resource utilization and increased economic viability of mature oil fields.