Technology Focus: EOR Modeling (January 2023)

Abstract

The oil and gas industry is facing unprecedented responsibility and expectations to keep fueling the world’s economies and social developments with reliable, accessible, safe, and affordable energy sources while responding to the global urgency to safeguard natural resources and protect the environment. Most major oil and gas companies have announced decarbonization strategies for low-carbon or net-zero emissions associated with their business operations. Consequently, reducing the carbon intensity of oil production [kilograms of carbon dioxide (CO2) equivalent emitted per produced barrel of oil] will be pivotal to meeting the environmental mandate. On the other hand, approximately 70% of the world’s counties have set targets to reach net zero within the next 3–5 decades, including emissions from burned hydrocarbon, which is a major challenge. Within this exigent mission to transition the industry, a major question arises about the merit and the role of enhanced oil recovery (EOR). With a share below 3% of the global oil production, field-scale EOR deployment and contribution have been modest despite substantial investments made in research and development and piloting in the last 4 decades. This underperformance of EOR has been attributed mostly to competitive alternatives (waterflooding), high cost, complex infrastructure and supply chains, fluctuating oil prices, and others. In the era of thirst for sustainability in our industry, there are reviving opportunities for selective EOR methods that can achieve efficient oil production with low carbon intensity. For instance, CO2 EOR is intuitively a win/win technology. This method may not be feasible everywhere for various reasons, however, including the availability and proximity of CO2 sources and the suitability of reservoir conditions. Chemical EOR methods, such as low-salinity, polymer-, and surfactant-based methods with low chemical usages have the potential to reduce water usage and enhance recovery factors, particularly from tight oil reservoirs. In contrast, EOR methods that are inherently associated with high carbon intensity, such as thermal EOR, will face stricter constraints to perform, including prohibitive costs for carbon offsetting. Advanced modeling and optimization, including guided machine learning and data analytics, will be crucial to maximizing recovery, quantifying uncertainties, and managing risk while preserving resources and reducing costs. The selected papers in this feature include examples of innovative approaches for developing efficient EOR schemes and advanced modeling and optimization. In one inclusion, optimized water chemistry is engineered for various EOR schemes (e.g., polymer, surfactant, CO2) to improve efficiency while reducing chemical usage. The second inclusion demonstrates an integrated core-to-field work flow to design surfactant-based EOR for a tight formation at the laboratory scale and demonstrate its performance using field-scale simulations. An integrated optimization approach for a Permian CO2-EOR field is demonstrated in the third paper, where an advanced Bayesian framework is used to capture uncertainties. Our industry has consistently demonstrated resilience, adaptivity, and creativity. In the era of industry transition to low-carbon operations, opportunities exist for selective EOR methods to revive and contribute. Recommended additional reading at OnePetro: www.onepetro.org. SPE 208121 Polymer Injection To Unlock Bypassed Oil in a Giant Carbonate Reservoir: Bridging the Gap Between Laboratory and Large-Scale Polymer Project by Clement Fabbri, ADNOC, et al. SPE 208127 The World’s First Offshore Gravity-Assisted Simultaneous Water-Alternating-Gas EOR Full-Field Implementation by Ahmad Khanifar, Petronas, et al. SPE 207449 Numerical Optimization of Water-Alternating-Gas Injection in a Sandstone Field Using a Coupled Surface and Subsurface Model by Thaer I. Ismail, Khalifa University of Science and Technology, et al.