Optimization of Enhanced Oil Recovery via Polymer Flooding in Heterogeneous Reservoirs with Real-Time Geomechanical Coupling

Project Abstract

In this study, we investigate the optimization of enhanced oil recovery (EOR) through polymer flooding in heterogeneous reservoirs while integrating real-time geomechanical coupling to capture the dynamic interactions between fluid flow and rock deformation. The research develops a coupled multiphase flow and geomechanics model that accounts for spatially varying porosity, permeability, and elastic properties, alongside polymer solution rheology, adsorption, and retention phenomena. By embedding a nonlinear, time-dependent constitutive relationship for reservoir rock, the model simulates how polymer injection alters pressure distribution, sweep efficiency, and reservoir compaction over the production life cycle. We implement a robust numerical framework based on a mixed-finite element approach for displacement fields and a finite-volume method for fluid flow, ensuring mass conservation and stability under large deformations and high polymer concentrations. The polymer rheology is represented using a Carreau or Ellis model to capture shear-thinning behavior, while polymer retention is described through adsorption isotherms and pore-scale clogging effects that influence permeability evolution. A novel aspect of the work is the real-time data assimilation and history matching capability, which updates model parameters using production data, downhole pressure data, and, where available, seismic or microseismic measurements, to reduce uncertainty and improve prediction accuracy. The optimization framework combines adjoint-based sensitivity analysis with a gradient-driven optimization algorithm to identify optimal polymer concentrations, injection rates, and slug sizes that maximize oil recovery while minimizing polymer usage and operational costs. We also explore strategies to mitigate adverse geomechanical responses such as fracturing, subsidence, and reduced injectivity by coupling operational constraints to the objective function. The study performs extensive synthetic case studies to benchmark the model against analytical solutions and high-fidelity pore-scale simulations, followed by a field-scale application to a heterogeneous mature reservoir with stratified permeability and variable mechanical stiffness. Key performance metrics include incremental oil recovery, polymer breakthrough time, pressure decline rate, water cut, sweep efficiency, and geomechanical indicators such as effective stress and porosity/permeability evolution. Results demonstrate that incorporating real-time geomechanical coupling significantly improves the fidelity of recovery forecasts and enables more effective polymer management strategies, especially in reservoirs with pronounced heterogeneity and compressible fluids. The optimized polymer flooding schedules achieve higher volumetric sweep efficiency and extended contact time with oil-bearing zones, while controlling adverse mechanical effects. Sensitivity analyses reveal critical parameters controlling performance, including polymer viscosity, adsorption coefficients, rock stiffness, and reservoir compressibility. The research concludes with practical guidelines for field implementation, data acquisition requirements, and a framework for integrating machine learning with physics-based modeling to enhance predictive capability and decision-making under uncertainty.

Project Overview

What This Project Is About

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A plain-language overview of how polymer flooding can be used to improve oil recovery in uneven (heterogeneous) rock, and how real-time geomechanical data helps adjust the process for better results. The project looks at practical steps a company could take to squeeze more oil out by injecting a thick polymer solution that blocks high-permeability paths, while monitoring how rock movement and stress change during the process to keep the operation safe and efficient.

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The Problem It Addresses

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Many oil reservoirs have rocks with different properties in different areas, so fluids move unevenly and we don’t recover as much oil as we could. Traditional methods may fail to adapt to changing rock behavior under pressure. This project tackles how to use polymer flooding together with live geomechanical feedback to optimize recovery and reduce risks in real fields.

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Objectives of the Project

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1. Explain how polymer flooding works in simple terms and why rock variability matters.
2. Explore how geomechanical data can guide polymer injection decisions in real time.
3. Develop a basic model showing expected oil gain from the method under different conditions.
4. Identify practical data needed to implement this approach in a field setting.
5. Suggest safe operating guidelines to protect the reservoir and surrounding environment.

End Notes

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What You Will Do Step by Step

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1. Review simple literature on polymer flooding and geomechanics at a high level.
2. Explain key terms like permeability, porosity, and polymer viscosity in plain language.
3. Describe a straightforward workflow for collecting field data (pressure, flow, rock movement).
4. Draft a lightweight model or flowchart showing decision points during injection.
5. Analyze example scenarios to illustrate potential outcomes and risks.

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Expected Outcome

A clear, student-friendly outline of how polymer flooding with real-time geomechanical feedback could improve oil recovery, including simple recommendations for when this approach is most beneficial and what data are essential to its success.