Model Enhances Extra-Heavy Oil Recovery Predictions
A new numerical model developed by Skoltech and Khalifa University aims to improve the prediction of enhanced oil recovery methods for Venezuela's challenging extra-heavy oil fields.
Researchers from Skoltech and Khalifa University of Science and Technology, in collaboration with Venezuelan oil industry experts, have created a validated numerical model to better predict the effectiveness of enhanced oil recovery (EOR) techniques in Venezuela's extra-heavy oil fields. This development is crucial for enabling informed decisions regarding the exploitation of these vast, yet difficult-to-extract, reserves.
Venezuela possesses significant extra-heavy oil reserves, but their extraction is hindered by the oil's high viscosity and other properties, resulting in a low recovery factor of approximately 4%, compared to 60% for light oil and up to 20% for heavy oil. Traditional EOR methods, such as steam injection and in-situ combustion, are technically challenging in these fields due to thin oil-bearing formations and heterogeneous, water-logged zones.
The research team proposed an alternative approach combining two chemical recovery methods without the use of environmentally harmful alkalis. This alkali-free strategy aims to mitigate risks associated with corrosion, scale buildup, polymer instability, and difficult-to-separate emulsions. The study explored various injection sequences for polymers and surfactants, including sequential and simultaneous introduction.
To overcome the limitations of physical experiments, which are constrained by the scarcity and cost of real rock samples, the researchers developed a numerical model. This model was calibrated against experimental data using both field-representative and actual core samples. The validated model was then integrated with the oil company's hydrodynamic field model, allowing for the comparison of a wide range of EOR scenarios, including non-chemical methods.
Numerical experiments indicated that simultaneous injection of polymer and surfactant yielded the most promising results, potentially tripling the recovery factor to 12%. While further economic viability assessments are needed, this model could be adapted for other extra-heavy oil fields globally, aiding in the forecasting of EOR effectiveness and economic feasibility.
This development focuses on creating a predictive tool for enhanced oil recovery in challenging geological conditions. By leveraging numerical modeling and experimental validation, it addresses a critical need for efficient resource extraction. The ability to simulate various chemical EOR strategies without extensive physical testing is significant for optimizing production and potentially adapting similar modeling approaches to other complex hydrocarbon reservoirs.
Edited by the news editor with AI from the original report — please refer to the original source.