Comparative Study of Enhanced Oil Recovery Across Field Types

Thesis Abstract

In the face of fluctuating crude prices and aging reservoirs, the comparative effectiveness of Enhanced Oil Recovery (EOR) across distinct field types remains inadequately quantified, hindering optimized deployment and investment decisions. The study addresses the problem of inconsistent EOR performance evaluation due to heterogeneity in reservoir characteristics, operational constraints, and data quality across conventional, heavy oil, and tight oil fields. The aim is to elucidate how EOR performance indicators vary by field type and to identify the most effective EOR strategies under specific geological and operational conditions. Specific objectives are (1) to compare incremental oil recovery, energy efficiency, and CO2 utilization across field types; (2) to evaluate the influence of rock and fluid properties on EOR performance using multivariate analyses; (3) to assess the relative economies of different EOR methods (thermal, chemical, and gas) within each field type; (4) to develop a cross-field decision framework for selecting EOR techniques; and (5) to propose guidelines for data acquisition and monitoring to improve cross-field comparability. The methodology adopts a mixed-methods research design integrating quantitative performance analysis with qualitative expert input. The population comprises mature oil fields that implemented one or more EOR techniques in the last two decades, categorized into three field types conventional light/medium oil, heavy oil, and tight oil reservoirs. A stratified random sample of 60 fields (20 per type) is selected from global industry databases, operator records, and publicly accessible field reports. Data collection instruments include standardized data extraction templates for reservoir and process variables, production and injection logs, recovery factors, energy consumption metrics, and project economics. Validity and reliability are addressed through triangulation of volumetric data, cross-checking with independent reserves data, and pilot-testing the data templates with five representative fields. The analytical framework employs ANOVA and multivariate regression to quantify differences in oil recovery and energy intensity across field types, followed by post-hoc tests to identify pairwise distinctions. A hierarchical linear model captures nested effects of field, operator, and EOR method on performance metrics. Economic viability is analyzed using net present value (NPV) and levelized cost of oil recovery (LCOR) computations, incorporating a sensitivity analysis on oil price scenarios and CO2 credit assumptions. The study also integrates qualitative insights from 18 industry experts through structured interviews and thematic analysis to contextualize quantitative findings and reveal operational constraints and data quality issues. The theoretical underpinning draws on the theory of technology adoption in energy systems and the resource-based view, complemented by the diffusion of innovations framework to interpret cross-field variability in EOR uptake and success. Expected findings indicate that conventional fields exhibit the highest incremental oil recovery from chemical and gas EOR under moderate temperatures, while thermal methods deliver superior performance in heavy oil reservoirs; tight oil fields show limited gains from thermal EOR due to rapid heat losses and fracturing constraints, but chemical surfactant-polymer systems may offer favorable recovery with manageable costs. Energy intensity and CO2 utilization are anticipated to be favorable in gas-based EOR for conventional and heavy oil fields, whereas chemical EOR may present lower emissions intensity in tight formations when coupled with optimized surfactant systems. The study contributes to knowledge by delivering a rigorously quantified cross-field comparison of EOR performance, a decision-support framework for method selection, and actionable guidance on data collection and monitoring practices to enhance cross-field comparability. The main conclusion is that field-type context fundamentally conditions EOR effectiveness and economic viability; consequently, a tailored, field-type-specific EOR portfolio with standardized data protocols yields the most reliable performance and investment outcomes. Recommendations include adopting standardized data templates across operators; prioritizing chemical EOR in tight and conventional fields with robust surfactants and polymers; applying gas-based EOR in conventional and heavy oil fields with attention to gas availability and environmental constraints; and establishing integrated field pilots to continuously refine the cross-field decision framework under evolving market and regulatory conditions.